Buying a new car is no small feat, it’s a rather long-term investment. So you’re still carefully weighing the pros and cons.

Want our advice?

As a forward-thinking company, we would go for option two without a doubt. What will count, in the end, is not a pretty bodywork or trendy colour. The question is whether the car’s design and concept will keep up with social, economic, and environmental challenges that will ultimately determine future advancements in the automotive industry.

The same applies to investing in technology in any other discipline of life, whether it’s health care, education, or financial services. However, in this day and age, with practically endless choice possibilities, how does one know which technology will stand the test of time?

We’ve asked ourselves the same question. And we’ve found some answers in a recently published study.

THE TALENT.IO REPORT

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Talent.io is a French recruitment company for tech profiles. It was established in 2014 and has been rapidly growing in Europe ever since.

Some of the most recognisable start-ups advertising jobs on its platform are BlaBlaCar (long-distance ride-sharing), Deezer (music streaming), and N26 (online-first banking). Talent.io claims that over 150,000 developers and 3000 companies have already signed up to use its services.

The company has just published its “European Tech Salary Report”. Apart from the earnings, it contains useful insights into the most sought-after technologies today.

The document’s findings are well-documented, and it has to do with the concept behind talent.io in general. It’s called reverse recruitment, which means that it’s the employers who “apply” to candidates selected for them by the platform. Those so-called “contact requests” include a detailed specification of technologies needed to perform the offered position. Cross-referencing those documents for the whole of 2021 is the report’s foundation.

Over 100,000 jobs in France, Germany, Amsterdam, Brussels, and London advertised on talent.io’s platform in 2021 have been reviewed. They include the ver more popular freelancing and remote work options as well. So it’s safe to say that the results are based on solid grounds. And they allow us to draw fairly accurate conclusions related to the future trends and market needs in the IT world in Europe.

Front-end vs back-end

While the report talks about web development jobs as a whole, in the context of most sought-after technologies it is divided into front-end and back-end. That is because the two sides of programming require the knowledge of different languages and frameworks.

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Front-end refers to clients’ perception of any website or application. It’s everything that has to do with the text, colours, images, navigation menus, etc. that the user interacts with while surfing the web. An example of a front-end language is HTML.

The second one as the name itself suggests, the back-end is not visible directly to the user’s eye. It’s the storage, arrangement, and maintenance of data on the servers that “host” the front-end. In other words, it’s the “how everything works” part of any website or application that the user is not concerned with at all. C++ is one of the languages used for building the back-end side, for example.

Three key takeaways from the talent.io report.

1. Regardless of the socio-economic circumstances of the respective markets, the same technologies seem to be in demand in the whole European continent.
   
   
2. The most sought-after front-end technologies are React.js, Vue.js, and Angular2, in this particular order. Except only for France, where Angular2 comes before Vue.js. This is on trend with other global studies, which place the first two frameworks in the top most popular amongst developers.
   
   
3. The most coveted back-end technologies are JavaScript (Node.js), Java (Spring), and Python (Django). Here, apart from France, Go comes in fourth place. PHP (Symfony) takes that spot in the French market instead.

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Which technology is the right one for me?

As a CEO of a start-up looking to upgrade your website, for instance, you don’t necessarily need to be versed in coding. And all those fancy names and statistics might still sound like Chinese to you. So you’d probably want to do some research first to know where your ROI will be most probable.

Alternatively, if you’re a software developer wanting to upskill, you’d probably want to know where most job opportunities lie.

Since the Talent.io report has already cut down the possibilities to a handful of highly regarded technologies job candidates should know, let’s look at some other considerations associated with them.

You’ve probably heard that before, but whichever programming framework you go for depends largely on your business needs and the project you’re working on.

Going back to our car purchasing analogy, it makes no sense to get an off-road SUV if you have a laptop-fixing service based in the city centre. But it does when you run a construction company in a remote area. You should approach choosing the right technology for your project with the same mindset.

Some other important aspects are related to the level of interactivity of the targeted website or technology, and the code’s maintenance by its respective community.

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In the case of the front-end, for instance, developers generally describe Vue as the simplest one to use and the easiest one to learn. Whereas, React is the most flexible one, offering the ability to integrate with other frameworks. On the other hand, Angular is perceived as the most “experienced” one of the three and recommended for companies with large teams already familiar with TypeScript.

Another difference stems from the frameworks’ origins. Vue is the “independent” one. While React and Angular are backed by some major players in the tech game (Meta and Google respectively).

If your business model is similar to Uber’s, maybe you should consider using React, etc.

When it comes to the back-end, each of the frameworks has its pros and cons as well, as reported by some programmers. For example, Django offers high security but works better for bigger apps. Writing code in Node.js is fast and easy, while it’s slightly less secure. And despite being a lightweight framework, working with Spring apparently requires a higher degree of expertise.

Conclusion

There’s no universal framework or programming language that fits all projects and users. But the talent.io report shows interesting trends in the job market today. The sought-after technologies it highlights come directly from hiring managers and indicate actual future needs in the field of software development.

If you’re considering investing in any of them, we are here to advise you.

Last but not least, don’t buy that company car because it’s sleek, elegant and black. Buy it because the company that makes it stays on top of the future tech game in the automotive industry.

Deliver high quality software solutions

Work with us and turn your idea into a great software solution for your company’s needs.

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A few facts about Quality Assurance (QA)

In today’s highly competitive world, the success of every business depends on the quality of the products or services it offers. The research proves that high-performing product teams (meaning those that work with QA early on) spend 22% less time fixing issues, which in turn gives them more time for research and add-value work.

Some time ago the importance of Quality Assurance has been underlined by The World Quality Report which recommended that companies should keep the QA budget to 25% of development costs, saying such an amount was crucial for maintaining quality, security and better customer experience.

So, what exactly is Quality Assurance?

One of the best definitions of quality was given by Henry Ford who once said: “Quality means doing it right, when on one is looking”. But doing it right is never as simple as it sounds and requires standards, processes, and ways of making sure things are always going according to the plan.

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This is exactly what Quality Assurance is all about – ensuring the products or services offered by a company are always of the highest standards and that those standards can be met consistently. Such an approach allows to prevent problems before they happen, or to spot them as soon as they arise.

Why is Quality Assurance so important?

There are several reasons of why Quality Assurance is so important in every kind of business. It saves time and money, improves customers’ confidence in the offer, makes the user experience better and promotes efficiency and productivity. In short, it allows businesses to make products that meet clients’ needs, requirements, and expectations.

What are the risks of neglecting Quality Assurance activities?

The list of QA benefits is long and doesn’t leave any doubts of why QA processes are so important. Today, let’s look at another list – the one that highlights risks related to neglecting Quality Assurance activities. Here it is:

Increased costs and more time spent on developing products

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When working on developing software, Quality Assurance allows you to spot problems early on. Without it, developers often need to fix issues and introduce changes at a later stage, which significantly increases costs and may mean exceeding deadlines. It is estimated that finding and fixing a software problem after delivery of a product is often 100 times more expensive than doing it during the requirements and design phase.

Increased risk of security breaches

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If you don’t have QA processes in place, meaning you don’t test your products as a part of their development process, you face a huge risk of cybersecurity breaches, which in turn may lead to huge reputational damage and potential loss of money if a cyberattack ever occurs.

Unstable performance and undetected errors

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In March 2016, Amazon experienced a service disruption: for 20 minutes users could only see the message: “We’re sorry! An error occurred when we tried to process your request”. This was enough for Amazon to lose $3.75 million! This is a great example of what an unstable performance may mean. Quality Assurance allows to test products and services throughout the development process, which minimises the occurrence of such incidents.

Decreased customer satisfaction

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IT products and services should be created with the end-user in mind. Statistics show that clients are merciless: they stop using the website if it doesn’t load properly, they change a supplier after just one bad experience. Without Quality Assurance activities printed into your projects, you cannot meet the customers’ satisfactions levels, as you don’t test your products and don’t gather relevant feedback about them.

Reputational damage and lack of consistent results

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If you company does not provide clients with consistently good products or services, its reputation will suffer, which in turn will impact your financial results.

Team that is less efficient and less productive

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Bugs and errors are always a problem, but if they are found on time, they can be dealt with immediately. Left unnoticed, fixing them takes longer and requires more people. This may mean delays and communication problems, which always prevent companies from working smoothly.

Conclusion

Times when Quality Assurance was just a catchy phrase are long gone. Today, it’s one of the most important parts of every software development process – an indispensable one if your company wants to grow and attract new customers.

If you don’t take it seriously, it can cost you dearly. Why risk it?

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Global cloud market share: AWS vs Azure vs GCP vs Alibaba Cloud

The leading players in the cloud services industry are Google, Amazon, and Microsoft. Amazon’s AWS is, by far, the most popular, with about 31% market share of cloud services.

Above all, this means that, in the IaaS (Infrastructure as a Service in Cloud) segment, AWS gets as much as 50% of revenue. Microsoft Azure is second with 20%, and Google Cloud Platform takes third place with 6%. Bringing up the rear is Alibaba with another 6%. The market is quite unstable, though, with relatively a lot of fluctuations.

As one of the most dynamic industries, cloud services grow by about 30% annually.

Jeff Bezos explains the domination of the American giant AWS. Essentially, it results from the headstart Amazon got compared to its competitors: 

AWS had the unusual advantage of a seven-year head start before facing like-minded competition. As a result, the AWS services are by far the most evolved and most functionality-rich.

Jeff Bezos

While AWS is definitely the largest player on the market at this point in time, you can clearly see that Microsoft Azure and the smaller ones represented by Google and Alibaba are growing relatively rapidly.

It’s especially observable when looking at data from the last few years:

The relatively high interest in the lesser-known Alibaba Cloud is primarily the result of its strong position in China. 

Top cloud providers: the titans of the cloud industry

The Google Trends Map illustrates the popularity of each query by highlighting particular regions. The darker colours indicated the places where there’s a higher possibility of somebody searching for the specific phrases.

The distribution is especially visible when it’s presented this way:

The AWS solution has dominated the US, South America, most of Europe, India, and plenty of other smaller regions.

Microsoft Azure is quite prominent in Northern Europe in the Scandinavian region, as well as Poland, Switzerland, Netherlands, and Portugal.

As for Alibaba, it’s definitely the most popular in China, where it has more than 40% of the market share.

Google Cloud Platform is not the most popular in any part of the world. Hence, we can assume that it’s more or less equally popular in each region.

Cloud computing services: offer comparison

Let’s take a closer look at the leading cloud providers revolutionising the digital world by changing how organisations store, process, and retrieve data. See how their offers compare.

Amazon Web Services (AWS): a comprehensive review

Amazon is, by far, the leader here. Many years of market domination allowed AWS to develop freely and, in turn, provide the most features out of the three. Apart from the variety of operations AWS provides, there’s also their vast array of data centers all over the world.

Having such a well-connected network allows AWS to deliver the data extremely quickly and without disruptions. The service is divided into Availability Zones, Edge Locations and Regions. There are 14 AZ’s, 114 Edge Locations and 22 Regions.

The Availability Zones are situated far away from one another so that they encompass as much space as possible. If one of them goes down for some reason, the Edge Locations act as caches close to the location of customers. This allows for quick response time and little to no downtime.

It’s tough to name all of the services provided by AWS. In fact, there are more than 18,000 of them, and this number keeps growing.

The main services AWS provides include:

• Computing,

• Cloud Storage,

• Database,

• Migration Services,

• Application Discovery Services,

• Networking & Content Delivery,

• Hybrid Cloud,

• Developer Tools,

• Management Tools,

• Recovery Services,

• Security,

• Big Data Analytics,

• AI and Machine Learning,

• Mobile Services,

• Automated Cloud Management Services,

• IoT,

• Robotics Development,

• Testing.

While GCP and Microsoft Azure share most of the features with AWS, AWS’s variety definitely wins here. There are far more possibilities with Amazon, and the scope of operations is massively larger.

For example, no other cloud service provider has automated management, robotics development, desktop application streaming, and a large data transfer solution on an exabyte scale.

It’s not perfect, though. The way of how the costs work is not entirely clear and can be confusing. Especially for enterprises using lots of AWS’s cloud services, it’s hard to manage the costs as well as to understand them thoroughly.

Read more about cloud computing:

• Choosing the ideal cloud service provider for your business
• Explore AWS AI and machine learning software solution
• Cloud strategy: the essential guide for planning and implementation

Google Cloud Platform (GCP): an in-depth look

Being a relatively new cloud service industry player, Google has some tricks up its sleeve. The primary specialisations of GCP include Big Data and Machine Learning. As for its infrastructure, Google also has a large potential with its worldwide network of data centres.

In fact, Google has quite a bit more than AWS, with 24 Regions, 73 Zones, and 144 Edge Locations. Their services’ availability is also impressive, boasting more than 200 countries.

Of course, Google shares most of the services that AWS has to offer, although with less variety. Being the third in the market, it doesn’t yet have the recognition to gather those high-level enterprise companies.

GCP often becomes the go-to provider for customers that directly compete with Amazon. Because of its quick growth and the abundance of data centres, Google is a considerable player that has the potential to outperform the competition.

Microsoft Azure: a deep dive into features and service

Azure Cloud, similarly to Google, had quite a late entry to the cloud service business. They’ve quickly grown due to the abundance of Windows, basing all their features on already finished software. Azure has 58 regions worldwide, with over 100 data centres, and is available in 140 countries.

The main reason for Azure’s success is definitely the popularity of Windows. Enterprises know the product; they’re familiar with the software and know the possibilities. For this reason, the management of Azure becomes easier. So many companies run on Microsoft’s software that sticking to one solution is more convenient. You can also count on some great discounts if you use Windows’ other products.

The primary pain point of Azure is that it doesn’t feel like it can perform well with enterprise-level businesses. Some reported difficulties include problems with support, documentation and instructions.

Alibaba Cloud: emerging player in the cloud computing market

Alibaba Cloud is a major player in the field of cloud computing, operating not just in China but around the world. The company introduced some of its top technology products to the global market, including a versatile database that integrates effectively with cloud systems and services which cover a wide range of tasks.

Alibaba Cloud has partnered with over 11,000 businesses from various countries across the globe, including industry giants like Salesforce, VMware, Fortinet, IBM, and Neo4j. The company operates in 29 regions worldwide and 88 availability zones. Each region is named after the city where its data centre is located.

Moreover, Alibaba Cloud’s network of Content Delivery Network (CDN) nodes and deployment regions is continuously expanding. This includes pioneering public cloud data centre regions in Dubai and Indonesia, strategically positioned data centres throughout Asia, and a robust presence across North America, Europe, and Australia

Cloud providers: unique features and differences

The described top cloud service providers offer exceptional scalability, flexibility and efficiency.

We will explore their distinctive features, market dominance, and their significant impact on shaping the digital future.

Pricing models: AWS vs. Azure vs. GCP vs. Alibaba Cloud

When it comes to cloud services, pricing can be complex and difficult to navigate.

Amazon Web Services (AWS) offers a cost calculator to help estimate expenses, but the number of variables involved can make it challenging to figure out precise figures. Businesses may need to use third-party cost management tools for better clarity. However, AWS’s Free Tier, which includes over 100 products that can be customised to individual needs, is a useful solution.

Microsoft Azure also implements a pay-as-you-go structure, which, however, includes a complex system of software licensing choices and discounts. Navigating Azure’s pricing structure can be challenging without help or experience. Still, Microsoft offers a number of services on a permanent free basis and extends popular services through a 12-month free trial period.

On the other hand, Google Cloud (GCP) offers deep discounts and highly flexible contracts and aims to deliver customer-friendly pricing that makes them stand out on the market. Additionally, GCP follows a user-friendly pay-as-you-go model with no upfront fees.

Finally, Alibaba Cloud aligns its pricing structure with that of AWS and Azure. Offering both pay-as-you-go and monthly subscription options, Alibaba Cloud responds to various user preferences.

Read more about the costs and expenses associated with cloud services:

• Cloud cost optimisation: how to reduce your cloud spend and maximise ROI
• The cost of cloud migration: things to know before the Big Data transfer

Range of services: who offers what?

With an extensive collection of over 200 services, AWS covers a wide range of services, including computing, storage, databases, analytics, and machine learning.

Azure (Microsoft Azure) is quite similar to AWS, offering computing, storage, databases, analytics, and machine learning. Azure’s strength lies in its seamless integration with the Microsoft technology ecosystem, making it a preferred choice for organisations deeply rooted in Windows-based systems.

Google Cloud Platform proposal highlights offerings like BigQuery and TensorFlow, as GCP is often picked for projects revolving around data-driven insights and advanced AI/ML solutions. Its expertise in these domains sets it apart in the cloud market.

Alibaba Cloud’s services include computing instances, storage solutions, databases, networking tools, artificial intelligence and machine learning capabilities, IoT platforms, blockchain services, and specialised e-commerce solutions.

Scalability: comparing the giants

When evaluating the scalability of leading cloud providers, it’s clear that they all prioritise on-demand scalability, which means that they enable users to swiftly adjust resources in response to varying workloads and demand spikes.

These providers offer auto-scaling features that automate resource allocation to optimise performance and cost-effectiveness. Each platform includes infrastructure and tools for efficient resource management:

• AWS highlights its scalable infrastructure and Elastic Load Balancing

• Azure offers both manual and auto-scaling options with Azure Autoscale

• Google Cloud Platform is supported by Google Cloud Load Balancing

• Alibaba Cloud boasts its Server Load Balancer.

Ultimately, businesses must choose the provider that best fits their unique needs and preferences for scalable cloud solutions.

Cloud security features: who tops the list?

When it comes to cloud computing, different providers offer various security features and compliance certifications.

For instance, AWS provides Identity and Access Management (IAM), Virtual Private Cloud (VPC), and AWS WAF for web application firewall. Additionally, AWS offers encryption through services such as AWS Key Management Service (KMS) and AWS Certificate Manager and has received certifications such as ISO 27001 and SOC 2.

Similarly, Azure offers Azure Active Directory (AD), Azure Firewall, and Azure Security Center and has encryption options like Azure Key Vault and Azure Disk Encryption. They have also obtained certifications like GDPR and HIPAA.

GCP, on the other hand, emphasises Google Cloud Identity and Access Management (IAM), Virtual Private Cloud (VPC), and Cloud Security Command Center. Encryption services like Google Cloud Key Management Service (KMS) and Google Cloud Storage encryption are available, along with certifications including PCI DSS and ISO 27001.

Finally, Alibaba Cloud provides Anti-DDoS protection, a Web Application Firewall (WAF), and adheres to security standards like ISO 27001 and GDPR.

To determine which cloud provider is most secure for your needs, you should evaluate your specific security requirements, necessary compliance certifications, ease of use and integration capabilities.

Cloud storage and capacity requirements

Cloud providers have options for various storage needs. Here’s what each of these providers offers:

Amazon has options like Elastic Block Store (EBS) for complex, high-performance tasks, Simple Storage Service (S3) for keeping data safe, Glacier for long-term storage, and Elastic File System (EFS) for scalable file storage.

Microsoft’s Azure provides Blob Storage for large-scale data, Azure File Storage for shared files, Archive Storage for long-term safekeeping, and StorSimple for a mix of cloud and on-site storage.

Google’s Cloud Storage works for many types of data and needs, Filestore is good for network-attached files, and Cloud SQL and Cloud Spanner help manage databases.

Alibaba offers different ways to store data based on how fast you need to get to it. They also have a Cloud Storage Gateway tool that helps connect your on-site data with what’s in the cloud.

All of these choices mean you can pick the storage that fits what you’re doing, whether that’s working with big projects, saving things for a long time or managing databases.

AWS Vs. Azure: why is Azure the main contender for AWS?

Launching four years later than AWS, Azure did have quite a distance to cover. The main advantage of Azure over the competition is the fact that Microsoft has plenty of other software to offer. No other provider can say that about themselves. There’s no software Amazon or Google has built that runs on Azure.

When Satya Nadella became the third boss of Microsoft, he decided to flip the company on its head. Windows stopped being the main selling point of the company. Instead, he chose to put Azure on a pedestal. With the growth of Facebook and Google, Microsoft was deemed to lose its position by some, as the price of actions was at a standstill, and they were stagnating.

By focusing on Azure’s growth, Nadella managed to double the revenue and achieve a market capitalisation of $1.6 trillion. Other companies such as IBM and Oracle tried to follow in Microsoft’s footsteps, though unsuccessfully.

Azure’s shares have been steadily growing during the past few years. With the constantly evolving market of cloud environment, the abundance of Windows, and Microsoft’s focus on their cloud platform, one can assume that Azure may well overtake AWS.

The same conclusions can be drawn when looking at the past. Microsoft’s Office software definitely wasn’t the first to appear. Excel wasn’t the first spreadsheet, and Word wasn’t the first text editor. Nevertheless, Microsoft was so good at commercialising their products that Office soon became the most popular software.

In fact, according to Gartner, Microsoft controls more than 87% of the market of Office-like software. Google is second with just over 11.5%.

Microsoft has the advantage of possible discounts, too. By bundling Azure with Windows and other software, they can reach way more customers. Windows operating systems are used by nearly 4 in 5 computers and comprise 72% of the servers. Because it’s so common, it becomes a huge advantage. AWS doesn’t have that, and neither does Google.

Azure is certainly not perfect, as their infrastructure is sometimes unstable due to the data centres being spread over a wider area but more thinly than AWS’s. This can lead to disruptions of service, where uptime is essential. Perhaps, with cloud being Microsoft’s focal point, we’re going to see improvements in that area. We know that Microsoft aims to either match or even overtake AWS in the cloud service market.

Which cloud provider is best for my business?

Cloud solutions are the fastest-growing sector of the IT market. Annual growth of 30% results makes the expected value of the cloud market $500bn by 2023. The pandemic situation only allowed cloud services to develop more rapidly as the demand increased.

The recent increase in demand has emphasized the power of cloud technology and demonstrated its crucial role in modernizing and securing businesses across various industries.

Whether you want to explore the potential of cloud technology for your business or improve your existing systems, consider cloud solutions to stay agile and innovative in the constantly changing technological environment.

Do you want to know more about Cloud and how your business can benefit, or do you want to improve your existing system? Contact us for more details.

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Secure software development is a holistic approach to creating software applications that prioritises security throughout the entire development lifecycle. This methodology integrates security practices, tools, and principles into every phase of software creation, from initial planning to deployment and maintenance.

At its core, secure software development begins with thorough security requirements gathering, identifying potential threats and security needs early in the planning stage. This is followed by secure design, where the software architecture incorporates robust security mechanisms such as proper authentication, authorisation, and data protection.

To perform secure software development, it is crucial to have a secure software development policy that outlines guidelines for processes, people, and technology.

A secure software development framework, such as NIST SSDF, provides a structured approach to software practices. Secure software development practices are essential for addressing various vulnerabilities and threats in application security.

The secure software development lifecycle emphasises the integration of security at every phase, from planning and design to deployment and maintenance. As development progresses, secure coding practices are implemented to mitigate common vulnerabilities like buffer overflows, injection flaws, and cross-site scripting.

Regular code reviews – both manual and automated – are conducted to identify and address security flaws. Security testing is integrated throughout the development process, including penetration testing and vulnerability assessments.

Check out other articles on software security:

• Security architecture 101: understanding the basics
• Why is security important in software development?
• How do you choose a software security consultant for an IT project?

What are common security vulnerabilities and threats in software?

Currently, software development does not just include the coding that is used to create specific programs or apps but also other types of projects such as self-driving cars and AI interfaces. This requires a new way to address cybersecurity because it’s hard for one person (or team) to stay on top of everything.

Cybercriminals come up with new ways to attack software systems and a lot of the solutions are not perfect, as they introduce new software vulnerabilities that need to be addressed in the context of secure software development.

Social engineering and malware

Attacks like phishing and ransomware are the most prominent forms of social engineering.

Phishing is when someone tries to scam you into giving them sensitive information, such as your credit card number or social security number with a fake email message that seems legitimate.

Ransomware is malware that locks up all of the data on your computer and requires payment in order for it to be unlocked again.

Now, the factor that is mostly responsible for such attacks is our proneness to human error. Since our reasoning and mentality is flawed, we can easily be tricked by a social engineering attack. Even seasoned developers can be deceived.

We have created two extensive posts on this topic:

• The human factor in cybersecurity: part I
• The human factor in cybersecurity: part II

The other common mistake is to install software without reading the end-user license agreement (EULA) that you agree to when installing it and granting access or rights to your computer system, thereby creating vulnerabilities in your system.

It’s not just humans who are vulnerable; computers, machines, and other forms of infrastructure are likely to be attacked as well. Having a well-defined incident response plan is crucial to effectively manage security incidents.

Hardware attacks

Power grids, control stations, and heavy machinery can all fall victim to hacker attacks. Most commonly, these methodologies are used to create diversions or distractions. For example, a power grid can be overloaded with thousands of demands for electricity all at once in order to cut the line and cause a blackout.

In 2015, the three most prominent energy suppliers in Ukraine suffered an attack that resulted in 73MWh of energy loss.

Of course, it’s not only governments that can suffer from such attacks, it’s corporations as well.

IoT attacks

IoT attacks mostly consist of data breaches. Information that corporations keep is most often sensitive and valuable to the company itself. The most popular way of hacking IoT networks is by infecting the device with malware and then using that to steal data.

What’s more, because devices are often just storage or gateways for remote servers, an attack on a single point can result in all data security being compromised. This means hackers don’t need even physical access to the machines to wreak havoc.

The most famous example of such an attack is the Dyn DDoS incident in 2016, which took down a number of popular websites including Netflix and Twitter. In this case, hackers had compromised IoT devices to mount their assault on the servers controlling them remotely.

According to Tech Republic, DDoS attacks increased by 91% due to the adoption of IoT on an unprecedented scale. For this reason, mobile security should be one of the top priorities.

A deficit in cybersecurity professionals

This leads to an increased risk of attacks, as there simply isn’t enough staff to assess protocols and secure development practices. The cybersecurity industry’s struggle to scale up with demand has led to extensive use of farshore resources like freelancers or third parties who have little expertise.

AI-based attacks

While Artificial Intelligence can be incredibly helpful, it can also be the main source of vulnerabilities for organisations. AI is still evolving and hackers can utilise that technology, if not well implemented, to teach their malicious software based on previous successful attacks.

Instead of looking into vulnerabilities and security issues manually, they could “simply” program a bot to scan the available data and identify entry points and establish the attack surface.

You can read more on the future of AI in cybersecurity.

Malicious data injection

More and more companies rely on AI/ML solutions for their business decisions.

Every new opportunity for companies will inevitably lead to more vulnerabilities, and with data being produced in real-time, if not well protected, cybercriminals can use this as an advantage and inject the servers with information to skew the results.

Remote work dangers

Increase in remote work forced stakeholders to use decentralised networks, i.e. network edge, which facilitates attacks. On top of that, employees have grown more comfortable with working remotely.

People are more likely to fall victim to cyber-attacks or fraud when they’re not physically at the office, so it’s crucial that companies pay extra attention to security measures and protocols for remote work. A well-configured software system is crucial in preventing unauthorised access and securing valuable databases.

Find out how to increase your protection against cyber dangers:

• How to develop a cybersecurity strategy in 6 steps?
• What is Defense in Depth (layered security)?
• The future of security operations (SecOps): trends and disruptions

How can developers integrate security into the software development lifecycle?

Seeing that there are so many threats and software security is one of the biggest concerns, the security requirements are getting more and more strict. Integrating static code analysis tools into the secure software development process is critical, as many security defects arise at the source code level.

These tools help developers identify vulnerabilities early in the code writing phase, enhancing code quality and ensuring compliance with secure coding standards.

• Code quality: what is it and how to improve your code?
• 10 software code quality metrics that you should measure in your projects

Software developers play a critical role in maintaining security in the software development lifecycle (SDLC). They should adopt secure development frameworks and stay current with industry trends to mitigate vulnerabilities.

Here’s a list of security principles and concepts to ensure a secure development process and suitable application security program from an expert point of view.

Software Security policy and secure coding practices

A well-established security policy should be the beginning of any project. Erik Nielsen, Senior DevOps Engineer at Infosec notes that:

Implementing proper security controls can further diminish this risk.

Patch management

Instead of using possibly compromised systems, you should go for libraries that are known to be secure.

elaborated Nielsen.

Sometimes, a software developer might slip and use a framework that has weak points.

Static and dynamic analysis

Instead of simply developing the application and leaving it be, it should be subject to constant analysis. According to Nielsen:

Threat modelling

Getting a grip on what threats your application can fall victim to is crucial to the success of your product. Threat modelling can help you identify the security vulnerabilities of your application very early in the software development lifecycle.

Heinrich Long of Restore Privacy remarks that:

SDLC (Software Development Life Cycle) and SDL (Secure Development Lifecycle)

Nowadays, these two concepts are or should be, mostly synonymous. Security measures ought to be an integral part of development. Of course, SDLC is a much broader idea, but SDL is necessary to be incorporated in there as well. Erik Nielsen says,

Adding on to that, Nikisha Shah of Simform describes the difference further:

If you are interested in SDL assistance or consultation, take a look at the dedicated page: Security Development Lifecycle.

Penetration testing and monitoring

After you’ve done developing the application, you need to assume that threats will change. Frequent penetration testing and continuous monitoring are necessary to ensure security.

Nielsen agrees,

Security awareness training

To best prepare for future challenges, businesses will need to collaborate not only internally but also externally with other security experts and IT specialists who have a wide range of experience. They can share their expertise with one another to strengthen the company’s security.

Qualified professionals should be equipped with the knowledge of how to avoid cyber-attacks in order to protect data and comply with legislation.

Diversity in secure software engineering

A robust system will need to be able to deal with multiple types of attacks, both online and offline because an organisation can never predict when a cyber-security attack could happen. Diversity is important in that it gives stakeholders more opportunities for defense as well as an offense against threats.

Cloud Computing

If you’re not already using it, cloud computing could save your company money in terms of both hardware as well as application development.

For example, multi-cloud strategies are known to provide a higher degree of security than using a single provider. Since you diversify your processes between different platforms, cloud computing security is better.

There are also numerous advantages to cloud computing including scalability, faster deployment of resources among many others. If you’d like to find out more, here’s our cloud service provider comparison.

Read more about security in cloud computing:

• Cloud security architecture: which model is best for security?
• The complete guide to cloud security management
• The future of cloud security: trends and areas of concern

Want to implement the best security solutions for your software?

The security market will continue to grow at a rapid pace due to the ever-increasing security risks and damages caused by cyberattacks. Companies should not only be on guard for attacks but also look to invest in the right security solutions, train their staff, and look out external Software Development Services when needed.

In order to stay ahead of cybercriminals, it is now more important than ever for companies to invest in advanced cybersecurity solutions and keep staff up-to-date on the latest trends. Educate your employees about identifying design flaws, using the best coding practices, business risks, web application security principles, as well as protection mechanisms to ensure that all components of your software are safe and secure.

Looking for software audits?

Is your software safe? Run an audit with experienced cybersecurity experts and find out.

Let’s talk

Thanks to digital transformation, almost every business needs improvement or extension of their existing software. The software encodes what companies do, how they manage different tasks, and their services to their users. That means one thing – software development has become a strategic function for all.

The COVID-19 pandemic only speeded up the inevitable tech changes as companies needed innovative solutions and broad support from IT experts. 2022 will be focused on developing ways to quickly deliver digital capabilities and create dynamic and anticipatory experience for customers.

Focus on event-driven architecture

As Gartner states:

As a software pattern or model that enables an organisation to detect events or crucial business moments (e.g. web site visits, transactions), EDA helps to act on them in real-time or near-real-time. The Forrester Research “Predictions 2022: Software Development” report shows that at least one-third of enterprises will focus on EDA in 2022. The same publication revealed that in 2020, 12% of global developers said their organisations were concentrated in EDA.

In 2021 the number grew to 20% and is predicted to reach 35% in the following year as more IT companies want to place a significant emphasis on EDA. As API management extends beyond REST to include EDA, leading API management vendors will adapt their products to have more event management capabilities with AsyncAPI support.

Consolidated DevOps tools & analytics

As Forrester report shows, 50% of enterprise development teams will shift to consolidated DevOps toolchains and pipelines. These new DevOps systems will be hosted, becoming platform-as-a-service. It will help teams automate whole development cycles.

Another interesting idea comes from Google’s DORA (DevOps Research and Assessment) team. Their research shows that technology organisation performance is closely linked to business outcomes. Companies with brilliantly performing engineering organisations are twice as likely to fulfil their organisational challenges and achieve a 50% higher growth rate over three years. Software development teams will have to ensure their processes and tools are as polished as possible to deliver new functionality quickly and reliably without developers burning out.

Developer productivity is becoming an area that will get increased attention. More and more companies plan funding to build developer analytics platforms to highlight bottlenecks.

IoB to boost personalisation

Software trends, for the last few years, have been heading towards personalisation, particularly with the ​​Internet of Behaviour (IoB). Simply, IoB is the extension of the Internet of Things (IoT) and helps track and analyse users’ behaviour patterns, interests or preferences when they interact with apps and different devices. Sounds interesting? The data gathered via IoB (BI, Big Data, CDPs, etc.) is incredibly useful to create a personalised UX.

Gartner predicts that 40% of the global population will have their behaviours tracked by 2023. We can observe the examples of IoB in social media in the form of personalised video feeds based on users’ reactions (YouTube) or ads displayed to increase users’ engagement (Facebook).

Low-code development

Simplification has been a popular trend in software engineering for a few years. No wonder why low-code development gains the upper hand over the software industry. Businesses have increased their adoption of low code applications to build applications faster, improve their competitive edge, and continue integrating digital technologies to transform the business.

Choosing low-code development means developing products without applying well-known coding. Instead, specialists will take advantage of configuration and graphical user interface. Such environments have the incredible potential of implementing ideas into digital products without the advanced development skills required.

Remote work and cloud services

Since 2020, remote work has become a new normal for many specialists. Managing different company tasks should happen in good conditions; thus, cloud services develop rapidly and gain popularity worldwide. According to Gartner, spending on public cloud services will reach $396 billion in 2021 and grow 21.7% to $482 billion in 2022. By 2026, public cloud spending will exceed 45% of all enterprise IT spending, up from less than 17% in 2021.

Microsoft and Amazon have both been working hard on addressing the most significant challenges. In August 2021, Microsoft released GitHub Codespaces to general availability. GitHub Codespaces offers full development environments that can be accessed using just a web browser that can start in seconds. The service allows technology teams who store their code in Microsoft’s GitHub service to fully develop using their Visual Studio Code editor in the cloud. 2022 will be the year of increased adoption of cloud technologies.

Software outsourcing gains popularity

Finding the right software experts outside the company instead of establishing an in-house team becomes an optimal move for many businesses. As Deloitte shows in “How much disruption? Deloitte Global Outsourcing Survey 2020” 770% of respondents claimed that cost reduction is a major reason to outsource.

For example collaborating with an IT partner is a great way to fulfil software development needs without being burdened by salaries and IT costs. An IT partner offers expertise and support on many different levels thus it is easier to find the right talents without paying for the whole in-house recruitment process.

To learn more about software development outsourcing, check Future Processing’s guide.

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2022 will keep us busy

The world seems to have changed forever since March 2020, especially in the tech industry. Businesses are more willing to go digital; IT companies are outdoing each other to offer software that meets the needs, and brand new tech solutions are here to make developers’ work more efficient. Specialists around the globe are ready for new challenges and opportunities in the new year. 2022, we are coming!

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Poland has noted a tremendous increase in startup VC funding. In fact, 2020 was the year with an all-time highest amount of money raised by investors.

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According to PFR Ventures’ report, €477 million has flown into Polish startups. Tim Draper, a billionaire Silicon Valley venture capitalist agrees and told Sifted that:

What is more, Poland ranks #4 in Europe in terms of most STEM graduates. The country itself is a great place for big companies to invest, which is seen on the example of Google, Microsoft and Intel. It is also the one attractive for tech startups as they can count on public funding.

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There are roughly 10,000 Eastern European startups that have won first funding rounds and are ready to go international. For this reason, Future Processing has decided to compose a list of the top ten Polish startups to watch out for in 2021.

Zowie

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Zowie is an innovative self-learning AI chatbot that allows a portion of customer service requests to be automated. Currently serving brands such as L’Oreal, InPost, and Aviva, Zowie has experienced rapid growth, mostly due to their cutting-edge product, as well as angel investor funding and venture capital.

The main advantages of Zowie are its versatility with 56 supported languages, integrations with any customer service system, and an effortless setup. Zowie boasts automating as many as 30% requests on day one, with InPost noting 92% after some time.

• Founded in – 2019
• Founders – Maja Schaefer and Matt Ciolek
• Funding – $620K
• Largest round – Seed Round – Zowie Inc.
• Investors – Inovo Venture Partners
• Number of employees – 19
• Business model – B2B SaaS

KP Labs

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KP Labs is a Gliwice-based space startup whose main mission is to “bring autonomy into demanding space missions” by using sophisticated computer software and Artificial Intelligence.

KP Labs offers numerous services, having completed multiple projects in the fields of hyperspectral imaging, advanced vision-based systems, flight software & mission automation, flight testing and simulation, high-performance computing, flight computers, computer vision, and machine learning.

KP Labs’ largest ongoing project is the hyperspectral Earth observation satellite that will allow for automatic processing of imagery. This will involve in-orbit calculations, segmentation, and classification, which will facilitate analysing the images. The entire project is based on deep neural networks.

Michał Zachara COO of KP Labs talks about Space Industry in Poland:

• Founded in – 2016
• Founders – Krzysztof Pacan
• Funding – PLN32,800,000
• Largest round – PLN13 926 303,05 for the Innovative hyperspectral Earth observation system 
• Investors – European Union, Silesian Voivodeship, The National Centre for Research and Development, Republic of Poland 
• Number of employees – 36
• Business model – B2B R&D

Symmetrical

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Symmetrical is an innovative platform that lets employees pay out a portion of their salary they’ve already earned. Instead of waiting for the end of the month, they can almost instantly transfer their earnings in a safe and secure way, without high-interest rates. Employers may adapt this to their payroll system to increase employee happiness and loyalty. 

Founded in 2019, Symmetrical has won considerable funding from prominent investors, adding up to €7.3 million over the two years of its existence. 

• Founded in – 2019
• Founders – Piotr Smolen, Daniel Wartolowski, Maciej Noga
• Funding – €7,300,000
• Largest round – 2020 Symmetrical Seed Round — €5,600,000
• Investors – Global Founders Capital, Finch Capital, Market One Capital, Plug And Play, Partech
• Number of employees – 36
• Business model – B2B SaaS

Linker

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Linker Cloud Fulfillment Platform is a Warsaw-based startup whose main mission is the facilitation of logistics for eCommerce businesses. With its vast network of locally-managed storehouses, Linker can provide a seamless delivery in Poland, Spain, The United Kingdom, Romania, France, and Germany. Still, this is a new feature, only introduced at the beginning of 2021.

Still, Linker’s unique selling point is its software. Namely, an order management system that lets you handle everything in real time. It integrates with the biggest eCommerce platforms like Amazon, eBay, Magento, Shopify, and WooCommerce, as well as delivery companies like UPS and DHL. The application lets you streamline the process by synchronising with all sales channels, verifying past transactions, picking and sorting support, packing, and finally shipment & delivery conveniences.

• Founded in – 2017
• Founders – Daniel Kierdal, Wojciech Ciołko
• Funding – N/A
• Largest round – N/A
• Investors – Market One Capital, Kogito Ventures
• Number of employees – 28
• Business model – B2B SaaS & fulfillment network

Autonomous Systems

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Founded in 2019 by the hands of former Future Processing CEO Jarosław Czaja, Autonomous Systems is making a name for itself in the field of vehicle autonomy. This Gliwice-based startup, while young, has already accomplished major projects. For one, Autonomous Systems have devised a neural network that maps the surroundings of a vehicle. Another significant project is the system of facilitating specific maneuvers for bus drivers based on deep neural networks and data retrieved from sensors.

Their mission is to use cutting-edge technology to make the process of handling a fleet easier, and the automation of drivers’ tasks.

• Founded in – 2019
• Founders – Jarosław Czaja
• Funding – PLN5,400,000
• Largest round – PLN3,100,000 for a system mapping the vehicle surroundings’ depth via the analysis of imagery from heterogenic cameras by convolutional neural networks.
• Investors – Republic of Poland, European Union, Silesian Voivodeship, The National Centre for Research and Development
• Number of employees – 15
• Business model – B2B R&D

Brand24

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Born in 2010, Brand24 is one of the leading social listening tools that allows you to gather mentions of specific keywords and use the data to your advantage. The main features include media monitoring, sentiment analysis, mention analytics, influence score, alerts, and filtering.

With the use of social listening, brands can always stay on top of current trends, avoid PR blunders, and conduct successful data-driven market research. Currently, Brand24 has been trusted by brands such as Uber, Intel, and McCann. Michał Sadowski, CEO of Brand24, remarks on what it’s like to run a startup in Poland:

Michał Sadowski announced that Brand24 will be coming back to the Warsaw Stock Exchange.

• Founded in – 2010
• Founders – Michał Sadowski
• Funding – 3,800,000 PLN
• Largest round – Venture Round — 1,500,000 PLN
• Investors – Venture INC S.A., Inovo Venture Partners
• Number of employees – 65
• Business model – B2B SaaS

edrone

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Cracow-based edrone is one of the world’s leading CRMs for eCommerce. edrone has two integral elements: Learn, which covers extensive analytics, RFM segmentation and a detailed look at each client, and Engage, which consists of 20 customer behaviour scenarios, sending recommendations, and cross-selling based on their Customer Intelligence algorithms.

edrone uses sophisticated technology like AI and machine learning to provide the best possible data-driven CRM. Still, even though edrone is so complex beneath the surface, its implementation is like a walk in the park. Their mission is to help eCommerce companies understand their customers and engage them with easy-to-use Plug‘n’Play software.

• Founded in – 2014
• Founders – Michał Blak, Rahim Blak
• Funding – $5,900,000
• Largest round – 2020 Grant — 12,600,000 PLN
• Investors – PortfoLion Capital Partners
• Number of employees – 112
• Business model – B2B CRM SaaS

Booksy

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Polish startup with headquarters in San Francisco, Booksy is the leader in the field of platforms for beauty-related businesses. With great numbers raised through funding — first €49 million and then $70 million in VC, Booksy has experienced considerable growth with almost 30 000 active businesses.

Booksy facilitates the process of appointing a visit through Facebook, Instagram, Yelp, and Google integrations. Booksy’s mobile app is also a way of scheduling. Not only does it help customers, but it also lets beauty salons get discovered more easily, reduce no-shows, and keep their schedules full. Booksy also offers management features in terms of bookings, team management, and client records.

• Founded in – 2014
• Founders – Stefan Batory, Konrad Howard
• Funding – $118,700,000
• Largest round – Series C 27 Jan 2021 — $70,000,000
• Investors – Cat Rock Capital, ENERN Investments Piton Capital, Open Ocean, Inovo Venture Partners
• Number of employees – 90
• Business model – B2B SaaS

Brainly

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Cracow-based Brainly is a peer-to-peer platform for teachers, students, and parents who are in need of assistance in terms of homework. Brainly offers the unique experience of contacting thousands of people all around the world to answer your questions concerning schoolwork. Currently, Brainly’s users amount to 350 million in 35 countries.

• Founded in – 2009
• Founders – Michał Borkowski, Łukasz Haluch, Tomasz Kraus
• Funding – $148,500,000
• Largest round – Dec 2020 Series D — $80,000,000
• Investors – General Catalyst, Point Nine Capital, Learn Capital, Runa Capital, Kulczyk Investments
• Number of employees – 378
• Business model – P2P platform

Surfer

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Surfer, being a unique position in this particular list, is a company that was bootstrapped right from the beginning. Sławomir Czajkowski, Surfer’s Co-Founder and CEO, comments on the troubles of bootstrapping:

Surfer has now grown to $2.8 million in Annual Recurring Revenue.

Surfer is a content intelligence tool that enables companies to actively improve their content in terms of on-page optimisation. Based on hundreds of ranking factors and the top 10 positions in the SERP, Surfer provides machine learning-powered recommendations for your articles. It’s hugely based on NLP, or Natural Language Processing, which enables the tool to give you the best possible solutions for optimisation.

• Founded in – 2017
• Founders – Michał Suski, Lucjan Suski, Sławomir Czajkowski
• Funding – None
• Largest round – N/A 
• Investors – N/A
• Number of employees – 30
• Business model – B2B SaaS

If you’d like to read about skyrocketing Polish IT companies, Future Processing has also composed a list of the top 15 fastest-growing enterprises.

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What is Clutch?

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Founded in 2013, Clutch has become the ratings and reviews platform for IT and marketing service providers. The main benefits of using Clutch are a better market presence and brand reputation for companies as well as enabling potential clients to find their dream team. Listing over 150,000 agencies, Clutch provides unbiased reviews written by appropriate, independent analysts and customers. It’s become their tradition to release multiple rankings every year, which are determined by combining hundreds of reviews and ratings.

Clutch covers virtually all areas of these sectors, ranging from custom software solutions, data science, Virtual Reality, business services, to Artificial Intelligence, and much more.

Clutch IT/software development rankings in 2020 and 2021

A lot of great companies compete for the privilege of appearing in Clutch’s rankings. Numerous firms get distinguished, and we created a list of the ones that in our opinion, are definitely worth a closer look.

Future Processing – an IT company appearing in a number of prestigious Clutch rankings at the top spots in 2020 and 2021.

Future Processing has been named one of the best software development providers in Poland and selected among the Top 100 IT Services Providers in Poland. The company was also enlisted among Highly-Rated B2B Companies in the Custom Software Development Sector.

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Top IT Services Providers Among Selected Categories for 2021

Due to providing high quality specialised IT services Clutch enlisted Future Processing in the worldwide ranking of best companies in terms of Microsoft Azure technical expertise.

Top-Performing Development Companies in Poland

Finally, Clutch has released a report about top-performing IT companies, wherein Future Processing was among the top 10. What is more, in both 2020 and 2021, Future Processing made its way as one of the top IT providers.

Other tech companies presented in reports by Clutch in 2021

Business service providers in Poland

If you’re looking for a solid, well-established, and experienced provider, look no further.

The first place in the ranking by Clutch for best business service providers was awarded to ICEO – Venture Builder, whereas the runner-ups were Talent Place and Bee Talents. All of the companies that made their way into the report help businesses grow by providing top-notch services in various sectors of development.

ICEO – Venture Builder are an expert venture builder and complete team of practitioners. With a focus on profitability, monetisation and digital product implementation in industries such as FinTech, Legaltech, Smartcity (etc.), ICEO provides comprehensive support to entrepreneurs with their idea from the concept stage through architecture plans all the way up until successful execution.

Talent Place was established in response to the demand for staff in the BPO and SSC industries. The first project they implemented concerned recruiting candidates who spoke German at that time. They hired ambassadors who promoted job offers on universities’ campuses as well as remote recruiters to make it possible to complete recruitment 100% remotely using crowd staffing methods based on their employees’ skill sets.

Bee Talents was founded with a goal to provide startups in Western Europe all the necessary support for building their team, developing HR marketing strategy and hiring IT specialists. They have conducted hundreds of job interviews resulting from which they learned how to identify outstanding candidates that will contribute greatly to an organisation by utilising efficient communication skills and acting according to GTD methodologies. The experience gathered working in event management, the education industry, as well as software development, has taught them how combining available resources can efficiently help accomplish goals.

B2B Leaders in the Artificial Intelligence Space

If you’re in need of an AI-powered bot, then Clutch’s selection of B2B AI solution providers could be a great place to start looking. As an international ranking, there’s a vast array of companies that are specialised in fields such as chatbots, cognitive computing, machine learning, Natural Language Processing, and robotics.

Again, to satisfy the tradition, Clutch has determined the top companies for each sector of AI. These are Master of Code Global for chatbots and NLP, Oxagile for cognitive computing, MobiDev for machine learning, and Waverley Software for robotics.

Master of Code is a full-scale design and development company that offers integrated web, mobile, chatbot solutions as well as its own out of the box products like Presentain. Located in seven offices around the world with more than two hundred employees globally, Master of Code has been providing high-quality products for companies all over since 2004.

MobiDev is a software development company that creates complex business-driven solutions, with a focus on innovation and transparency of actions. Experts in Industrial IoT & Augmented Reality, Data Science & Machine Learning, Microservices& cloud infrastructure as well native mobile & desktop development – MobiDev has delivered more than 350 products globally over its 10 years of existence.

Oxagile is one of the most well-known and successful IT companies in today’s scene. Over its decade long history, they have successfully developed a variety of solutions for their clients in different industries including Media & Entertainment, Education Technology, Advertising/Marketing Services, as well as Healthcare. They’ve worked with such high profile names as Google and Disney to name but two examples among many others.

Top-Performing B2B Companies in the Web Development Space

The Web Development sector is one of the fastest-growing fields of software development, surpassing most other areas. If you’re looking to develop a web application using innovative solutions, you might have found just the thing for you.

Clutch created a report consisting of specialisations like BigCommerce, Drupal, Magento, NodeJS, PHP, Python & Django, ReactJS, Ruby on Rails, Shopify, Sitecore, and WordPress. While all of the companies listed there are worthy of mentioning, these two especially caught our eye.

Rave Digital, the winner of the Magento category, founded in 2008, is a top-rated Magento Certified, Adobe Magento Silver Partner focused on delivering cutting-edge eCommerce solutions for both B2B & B2C Industries. Headquartered in the US with 3 additional locations spanning the globe, they are experts on Open Source and M2 Commerce applications that have managed to grow exponentially over time because of their expertise and know-how when it comes to developing custom online stores.

Silk Software a leading competitor that is able to provide customised solutions for B2B and B2C clients with a decade of experience in the eCommerce industry. They strive to help their clients stand out from their competition with their efficient and cost-effective digital commerce products, so they can propel your business forward into an ever-evolving competitive marketplace.

Leading Companies in App Development

Lastly, we’d like to mention the leaders in the category of app development. That’s another sector that has been growing wildly during the past few years, and with the pandemic still at large, this development has only been accelerated by an influx of new mobile device users.

The report was comprised of Android App Development App Modernization, CRM & Sales Enablement App Developers, Cross-Platform App Developers, E-Commerce App Developers, React Native Developers, iPad App Developers, and iPhone & iOS App Developers. We believe that two of the firms listed there earned an additional mention.

WillowTree®, the winners of CRM & Sales Enablement App Developers, helps companies develop a mobile strategy to launch the most creative and successful products. They tailor their services by providing strategic advice at every stage of production, as well as being experts in all aspects of design, development, testing and growth for any project they are involved with. What sets WillowTree apart is that not only do they offer expert opinions on how to make your product succeed but also provide all necessary tasks required throughout each step along the way until it reaches success. WillowTree has also appeared in Android App, iPhone and iOS, and React Native App Developers, which makes them one of the most versatile companies out there.

hedgehog lab is a global digital product consultancy with over 10 years of experience in technology, design and development. Whether it’s iOS/Android apps, immersive web solutions or voice-activated products – they’ve done it all for some of the world’s most innovative enterprises. With their expertise in solving problems through new technologies that deliver real business impact to clients worldwide, you can expect hedgehog lab to provide even more cutting edge ideas into how companies are approaching every rapidly evolving industry.

Wrap-up

We’d like to congratulate all the companies that were enlisted in various Clutch’s rankings. We know how honourable it is. We’re happy to be enlisted in so many categories. It fills us with determination to develop and do our best for and with our clients.

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Achieve your business goals with technology and get the product that is well adapted to your environment.

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What is Natural Language Processing?

Natural Language Processing is all about mimicking and interpreting the complexity of our natural, spoken, conversational language. It’s a field of computational linguistics, which is a relatively new science.

What is NLP? It is a subfield of computer science and artificial intelligence (AI) that uses machine learning to enable computers to understand and communicate with human language. While this seems like a simple task, it’s something that researchers have been scratching their heads about for almost 70 years.

Still, with tremendous amounts of data available at our fingertips, NLP has become far easier. The more data you analyse, the better the algorithms will be. The growth of NLP is accelerated even more due to the constant advances in processing power.

Similarly to AI specialists, NLP researchers and scientists are trying to incorporate this technology into as many aspects as possible. Modern NLP technologies, particularly deep learning models, have revolutionised the field by using neural network models to train NLP systems from diverse and large datasets, enabling transfer learning to achieve new tasks with less data and compute effort.

Even though NLP has grown significantly since its humble beginnings, industry experts say that its implementation still remains one of the biggest big data challenges.

Before putting NLP into use, you’ll need data. By using information retrieval software, you can scrape large portions of the internet.

Want to know more about NLP? Take a look here:

• How is Natural Language Processing (NLP) used in business?
• How do NLP and IDP address business challenges?
• NLP techniques: key methods that will improve your analysis

NLP consists of two fundamental tasks: syntax analysis and semantic analysis.

Syntax analysis

Syntax analysis is used to establish the meaning by looking at the grammar behind a sentence. Also called parsing, this is the process of structuring the text using grammatical conventions of language.

Essentially, it consists of the analysis of sentences by splitting them into groups of words and phrases that create a correct sentence. Syntax analysis is one of the fundamental NLP tasks in processing human text and voice data.

This doesn’t account for the fact that the sentences can be meaningless, which is the point where semantic analysis comes with a helping hand.

Semantic analysis

Our understanding of language is based on the years of listening to it and knowing the context and meaning. Computers operate using various programming languages, in which the rules for semantics are pretty much set in stone. Now, human language is different, as it is dynamic.

With the invention of machine learning algorithms and advancements in natural language understanding, computers became able to comprehend and generate human language. At least to a certain degree.

While syntax analysis is far easier with the available lexicons and established rules, semantic analysis is a much tougher task for the machines. Meaning within human languages is fluid, and it depends on the context in many situations.

For example, Google is getting better and better at understanding the search intent behind a query entered into the engine. Still, it’s not perfect. I bet that you’ve encountered a situation where you entered a specific query and still didn’t get what you were looking for.

NLP helps with that to a great degree, though neural networks can only get so accurate.

The benefits of NLP

Natural Language Processing (NLP) offers numerous benefits across various fields and industries:

1. Improved communication: NLP enables more natural human-computer interaction through voice assistants, chatbots, and language translation services, breaking down language barriers.
2. Efficient information extraction: It allows for quick analysis of large volumes of unstructured text data, extracting key insights and trends that would be time-consuming for humans to process manually.
3. Streamlined business operations: By automating text-heavy tasks like document classification, email filtering, and report generation, NLP increases operational efficiency and reduces human error.
4. Advanced search capabilities: NLP improves search engine performance, enabling more accurate and context-aware results, benefiting both users and content creators.
5. Market Intelligence: NLP tools help businesses gain valuable insights from social media, reviews, and news articles, informing strategic decisions and product development.
6. Accessibility: Text-to-speech and speech-to-text technologies, powered by NLP, make digital content more accessible to people with visual or auditory impairments.
7. Research and Development: NLP accelerates scientific research by helping researchers quickly sift through and analyse large volumes of academic papers and data.

These benefits demonstrate NLP’s wide-ranging impact, improving efficiency, accuracy, and accessibility across numerous domains.

How does NLP work?

There are numerous techniques associated with Natural Language Processing, including machine learning methods. Each of them is different, though they can provide you with invaluable insights concerning your data when used together.

These techniques also reduce the time it takes to process data by removing and simplifying particular elements of sentences.

Find out how NLP is used in practice in different areas:

• NLP in the insurance industry: top 5 use cases and benefits
• How is NLP transforming finance, FinTech, and banking?

Sentiment Analysis or Opinion Mining

Sentiment analysis is the investigation of statements in terms of their — as the name suggests —sentiment. In essence, it consists of determining whether a portion of text has a positive, negative, or neutral attitude towards a certain topic.

Now, the more sophisticated algorithms are able to discern the emotions behind the statement. Sadness, anger, happiness, anxiety, negativity — strong feelings can be recognised. It’s widely used in marketing to discover the attitude towards products, events, people, brands, etc.

Data science services are keen on the development of sentiment analysis, as it’s one of the most popular NLP use cases.

Parsing

Parsing is all about splitting a sentence into its components to find out its meaning. By looking into relationships between certain words, algorithms are able to establish exactly what their structure is.

Stemming and Lemmatisation

Stemming is a method of reducing the usage of processing power, thus shortening the analysis time. Stemming converts words into their roots, e.g. “buying” will be converted to “buy.” Consider the sentences “I’ll be buying some shoes,” and “I will buy some shoes.”

They have the same meaning, so the algorithm reduces the first infinitive one to its stem, decreasing the amount of data needed to analyse.

Lemmatisation differs a bit from stemming in that it reduces words into their most basic forms.

Imagine that you’re looking into terabytes of information to gather insights. Such situations will occur fairly frequently, and the amount of time you save is significant.

Named Entity Recognition (NER)

Named Entity Recognition (NER) is the process of matching named entities with pre-defined categories. It consists of first detecting the named entity and then simply assigning a category to it.

Some of the most widely-used classifications include people, companies, time, and locations. NER is one of the many NLP tasks that involve processing human text and voice data.

NER is helpful when you need an overview of immense amounts of writing.

Relationship Extraction

The Relationship Extraction process takes named entities from a text and then recognises the relationship between them.

For example, you could ask Google, “who is the chairman of Intel,” and the algorithm, using RE, would associate the relationship between “chairman” and “Intel,” providing you with the correct answer.

RE could also be used when you analyse large portions of customer service queries. It allows for the detection of particular relationships and categorises them in terms of priority. This, in turn, facilitates your support tasks and improves customer experience.

Topic Modeling and Classification

Topic Modeling is most commonly used to cluster keywords into groups based on their patterns and similar expressions. It’s a technique that is entirely automatic and unsupervised, meaning that it doesn’t require pre-defined conditions and human ability.

On the other hand, Topic Classification needs you to provide the algorithm with a set of topics within the text prior to the analysis. While modelling is more convenient, it doesn’t give you as accurate results as classification does.

Stop Word Removal

One of the essential elements of NLP, Stop Words Removal gets rid of words that provide you with little semantic value. Usually, it removes prepositions and conjunctions, but also words like “is,” “my,” “I,” etc.

Tokenisation

Tokenisation is the process of breaking down text into smaller units called tokens. These tokens are typically words, numbers, or punctuation marks, but can also be subwords or characters depending on the specific application.

Tokenisation can use various methods:

• White space tokenisation – splits text at spaces (simplest method, but can be inaccurate for languages without clear word boundaries).
• Rule-based tokenisation – uses predefined rules to identify word boundaries.
• Regular expression tokenisation – employs regex patterns to split text.
• Machine learning-based tokenisation – uses trained models to identify tokens, especially useful for complex languages.

Tokenisation is crucial in NLP technology as it’s often the first step in text processing, forming the foundation for further analysis like part-of-speech tagging, NER, or sentiment analysis.

What are some common applications of NLP?

NLP has a lot of uses within the branch of data science, which then translates to other fields, especially in terms of business value.

Speech recognition

NLP is what lies behind speech recognition software. By analysing speech patterns, meaning, relationships, and classification of words, the algorithm is able to assemble the statement into a complete sentence.

Using deep learning, you also get to “teach” the machine to recognise your accent or speech impairments to be more accurate.

Additionally, the technology called Interactive Voice Response allows disabled people to communicate with machines much more easily.

Market analysis

NLP allows companies to determine current trends by analysing large amounts of available data. Using Topic Classification, the machine can find out what categories are the most common.

Social media analysis, for example, can provide you with insights concerning your industry, product, or brand straight from the consumers’ point of view, which improves your business intelligence.

You get to see what the sentiment is, which topics are the most usually talked about, what the opinion about your competitors is, the latest trends, and so on. And what better source of information than your audience?

Predictive text

NLP finds its use in day-to-day messaging by providing us with predictions about what we want to write. It allows applications to learn the way we write and improves functionality by giving us accurate recommendations for the next words.

Language translation

Online translators wouldn’t be possible without NLP. Remember a few years ago when software could only translate short sentences and individual words accurately? Well, that’s history.

For example, Google Translate, which uses machine translation, can convert entire pages fairly correctly to and from virtually any language.

Disease prediction

NLP is widely used in healthcare as a tool for making predictions of possible diseases. NLP algorithms can provide doctors with information concerning progressing illnesses such as depression or schizophrenia by interpreting speech patterns.

Still, psychiatry is not the only field of medicine that NLP finds use in. Natural language generation can also be used to summarise medical information into text.

Medical records are a tremendous source of information, and practitioners use NLP to detect diseases, improve the understanding of patients, facilitate care delivery, and cut costs.

Search Engine Optimisation (SEO)

With NLP and BERT interconnected, the entire field of SEO has undergone considerable changes following the 2019 update. Context, search intent, and sentiment are currently far more important than they’ve been in the past. BERT has impacted about 10% of all queries, which is a tremendous number.

Google has incorporated BERT mainly because as many as 15% of queries entered daily have never been used before. As such, the algorithm doesn’t have much data regarding these queries, and NLP helps tremendously with establishing the intent.

Challenges of Natural Language Processing (NLP)

One of the primary difficulties is dealing with the inherent ambiguity in language, where words and phrases can have multiple meanings depending on context. This ambiguity extends to sentence structure, idioms, and cultural references, making it challenging for machines to accurately interpret human communication.

Another significant hurdle is the vast diversity of languages and dialects worldwide. Each language has its unique grammatical rules, syntax, and semantic nuances, requiring specialised models and approaches. Moreover, many languages lack extensive digital resources, making it difficult to train robust NLP models for them.

Context understanding presents another major challenge. NLP systems often struggle to grasp the broader context of a conversation or document, which is crucial for accurate interpretation. This includes understanding sarcasm, humor, and implicit information that humans easily infer but machines find difficult to detect.

Handling informal language, including slang, abbreviations, and evolving internet language, poses ongoing difficulties. These linguistic elements change rapidly, making it hard for NLP models to stay current.

Bias in language models is a growing concern. NLP systems can inadvertently perpetuate or amplify biases present in their training data, leading to unfair or discriminatory outcomes. Addressing this requires careful consideration of data sources and model design.

Multimodal NLP, which involves integrating language processing with other forms of data like images or audio, presents its own set of challenges in aligning and interpreting diverse data types.

Finally, the computational resources required for advanced NLP tasks, especially for large language models, can be substantial. Balancing model performance with efficiency and accessibility remains an ongoing challenge in the field.

Do you want to use the potential of NLP in your business?

Natural Language Processing Market is set to surge from a valuation of $29.1 billion in 2023 to $92.7 billion by 2028, demonstrating a Compound Annual Growth Rate (CAGR) of 26.1% during this period (2023 to 2028).

With the available information constantly growing in size and increasingly sophisticated, accurate algorithms, NLP is surely going to grow in popularity. It’s altering the way of interaction between humans and machines. The previously mentioned uses of NLP are proof of the fact that it’s a technology that improves our quality of life by a significant margin.

As much as 80% of the information that surrounds us is unstructured. For this reason, NLP is one of the largest fields of data science.

Organising this data is a considerable challenge that’s being tackled daily by countless researchers. Continuous advancements are being made in the area of NLP, and we can expect it to affect more and more aspects of our lives.

And if you are looking for a consultation or partner to implement solutions in the areas of AI/ML, Data services or related areas – give us a call!

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