Last year, the global tech acquisitions deals totaled $634 billion, a 91.8% year-over-year increase, according to GlobalData. This year, the mergers & acquisitions market spun to full bloom from the very early days of 2021.

Here are some of the transactions which will most likely reshape the future.

IBM bought Turbonomic to focus on observability for customers

IBM announced the acquisition of Turbonomic at the end of April.

Turbonomic specializes in Application Resource Management (ARM) and Network Performance Management (NPM) software.

This applies to containers, VMs, servers, storage, networks, and databases.

This acquisitions will help IBM offer a greater range of AIOps and observability options for customers.

Microsoft acquired Kinvolk for its managed Azure Kubernetes Service

Microsoft made a move to boost its capabilities in the Kubernetes space with the acquisition of German firm Kinvolk. This also took place in late April.

Founded in 2015, Kinvolk has been building enterprise-grade tools to help developers adopt cloud-native technologies.

Microsoft expects to integrate the Kinvolk team and technology into the team responsible for its managed Azure Kubernetes Service (AKS).

UiPath purchased Cloud Elements to build more effective automations

On March 23rd, RPA vendor UiPath made an addition of its own, picking up the Denver, CO-based firm Cloud Elements.

Cloud Elements specializes in API integration, similar to Mulesoft and Apigee, which are now part of Salesforce and Google, respectively.

For UiPath, a Romanian-born start-up, this capability could allow customers to better link processes that span various enterprise systems.

SAP acquired Signavio for cloud-native solutions

German software firm SAP announced it’s acquiring fellow German firm Signavio, which specializes in cloud-native enterprise business intelligence for processes and management, in late January.

This acquisition adds Signavio-designed solutions to the bundle of existing SAP software and services aimed at offering customers “business transformation-as-a-service”.

SAP will aim to use Signavio’s expertise around business process intelligence to help more customers optimize these processes as they become more digital.

Qualcomm integrated Nuvia for the 5G era

Qualcomm announced it was acquiring Nuvia in early January. This 2021 tech acquisition led the way to the upcoming M&A operations of the year.

Nuvia was founded by a team of Apple engineers and makes high-performance CPU chips.

Together, the two companies will be positioned to deliver a new class of products and experiences for the 5G era.

You might also find interesting: SMEs rely on RPA for business efficiency

Neuroscientists from MIT have discovered that brain activity while coding differs from processing language or doing mathematics.

Coding is matched by many with learning a new foreign language. And, granted, there are certainly many similarities. To the brain itself, however, it seems to be quite different.

Researchers took fMRI brain scans of young adults in a small coding challenge, using both Python and visual programming language ScratchJr. The purpose was to see what parts of their noggins lit up.

Almost no response was seen in the language processing parts of the brain.

Instead, it appears that coding activates the ‘multiple demand network’ of our brains. This area “is also recruited for complex cognitive tasks such as solving math problems or crossword puzzles.”

Yet when solving maths problems directly, slightly different brain activity patterns emerge.

The multiple demand network is spread throughout the frontal and parietal lobes of the brain. Previous studies have found that math and logic problems dominate the multiple demand regions in the left hemisphere. Tasks involving spatial navigation lean on the right hemisphere more than the left.

Coding activates both the left and right sides of the multiple demand network. This counters the belief that coding causes the same brain activity as maths. One interesting fact: ScratchJr activated the right side slightly more than the left.

You can find a full copy of the study here:

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Guido von Rossum launched Python on February 20th, 1991. Python is known as an incredibly versatile language. It is used in developing some of the most popular web applications, from Instagram to Dropbox.

At the same time, it is a gateway language for many in the world of software development.

Moreover, it is frequently taught to schoolchildren and people worldwide who lack any prior programming experience.

Read more details here:

One reason for the popularity of this programming language lies in its simplicity. Its users do not need to understand compilers or assemblers. They also don’t need to understand other tiny details programming languages require.

Feedback is instant, and Python is improving all the time. In addition to its popularity among entry-level users, Python is rapidly becoming a priority within the business environment. It has also found favor for serving as the ‘gluing language’.

Large development projects always have a trade-off between scale and speed. The typical software stack that a large organization uses every day may include code written in several different languages. Moreover underlying data may be stored in numerous formats, languages, and locations.

In such environments, Python has taken root as a subtle, but powerful way to bridge between different applications and code libraries.

When Python is used as gluing code in compiled languages, development cycles are shortened. Results are made more interactive and are quicker to observe. At the same time, the delays caused by things such as long compile times are eliminated.

Researchers from MIT and Intel have created MISIM, an algorithm that can create algorithms. What does that mean for software developers?

For most of us, writing code is like learning a foreign language. But no more! A team of researchers from MIT and Intel are looking to change all that by building a code that will write code.

The new technology is named MISIM (Machine Inferred code Similarity). MISIM studies snippets of code to understand what a piece of software intends to do. It uses a pre-existing catalogue of codes and it can understand the intent behind a new code.

Will this actually help software developers? The Intel-MIT team says yes. MISIM will help developers working on software by suggesting other ways to “attack” a program. MISIM will also aid them in offering corrections and options that will make the code more efficient.

The principle behind MISIM is not new. Technologies that try to determine whether a piece of code is similar to another one already exist. They are used by developers, but they focus on how code is written and not on what it intends to do. MISIM can act like a recommendation system. It suggests different ways to perform the same computation – that are faster and more efficient.

Software development becomes more and more complex. Technologies such as MISIM could have a significant impact on productivity. This was the opinion of Justin Gottschlich, the lead for Intel’s machine programming research team.

More details about the MISIM algorithm here:

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Graph databases store information as nodes and data specifying their relationships with other nodes. They are architectures for storing data with complex relationships.

They have been substantially used, especially during the past decade, despite the fact that companies have considered other NoSQL and big data technologies.

The global graph database market was estimated at $651 million in 2018 and is expected to grow to $3.73 billion by 2026.

Competitors remain in the range of other big data management technologies, including Hadoop and Spark.

Graph databases and query languages

Developers think in objects and use hierarchical data representations in XML and JSON regularly.

For graph databases, although it may be relatively easy to comprehend the modeling of nodes and relationships used, querying them requires learning new practices and skills.

Developers can query Neo4j graph databases using Resource Description Framework (RDF) and Gremlin, but 90% prefer to use Cypher.

The query is elegant and efficient but has a learning curve for those used to writing SQL queries. Here’s one of the first challenges for organizations moving toward graph databases: SQL is a pervasive skill set, and Cypher and other graph query languages are a new skill to learn.

These databases can be used in flexible hierarchy design

Product catalogs, content management systems, project management applications, ERPs and CRMs all use hierarchies to categorize and tag information. Graph databases enable arbitrary hierarchies. Developers need to create different views of the hierarchy for different needs.

To take advantage of flexible hierarchies, it helps to design applications from the ground up with a graph database. The entire application is then designed based on querying the graph and leveraging the nodes, relationships, labels, and properties of the graph.

Databases and cloud deployment – reduced operational complexity

Deploying data management solutions into a data center has to consider infrastructure and operations, security requirements and review performance considerations. These are used to size up servers, storage, and networks. They are also used as replicated systems for redundancy and disaster recovery.

Organizations experimenting with graph databases now have several cloud options. Engineers can deploy Neo4j to GCP, AWS, Azure, or leverage Neo4j’s Aura, a database as a service.

The public cloud vendors have graph database capabilities. These include AWS Neptune, the Gremlin API in Azure’s CosmoDB, the open source JanusGraph on GCP, or the graph features in Oracle’s Cloud Database Services.

When it comes to recruiting, half of professionals in the U.S. are now changing their in-person meetings to either phone or video, for health and safety reasons. And Europe makes no exception; so new times call for new ways to handle such experiences.

There is no doubt about it: in Covid-19 challenged times the way we conduct our professional lives is changing.

As a candidate, you need to know that the questions and conversations are likely to be the same as they would have been in a live one-to-one interview. But an offline interview conducted face-to-face has some differences as against one through a digital screen.

If you’re in the process of getting ready for a job recruiting interview on video, these examples of what NOT to do ahead of and during a video interview for a new job should be best practices to get you set up for success.

Internet connection – don’t leave it to chance

Check your internet connection speed to help ensure your video will come across smoothly – particularly in the room in which you want to be at the time of the recruiting interview. Don’t leave your familiarization with virtual meeting tools up to the time of the interview. You can also download the software used, like Microsoft Teams and Google Hangouts, which are currently being made available for free test runs. Have the virtual meeting tool available both on your laptop, as well as on your smartphone.
Don’t leave it up to the interviewer to remind you to share cellphone numbers – just in case you need to conduct the interview (or parts of it) over the phone.

The space around you 

We recommend you have the interview at home – a quiet, well-lit space with a neutral background is ideal. Despite it being your personal space, choose not to clutter it with home interior accessories, photos of your loved ones or any other type of memorabilia.
Also try to keep pets and family members in another room during the interview.
Make sure you aren’t distracted by your phone and computer notifications (yet there’s the upside that you can have some notes on hand to highlight that you’re the right candidate for the job).

Your attire – don’t get too comfy

Even if it’s a virtual meeting, it’s important to dress as you would if you were going to the interview in person.
Do not use bright colors in your attire and also avoid large pieces of jewelry or statement accessories, other than the necessary headphones.
Also, don’t rely on the fact that your bottom half will not show: make sure your bottom half matches your upper half, in case you need to get out of your seat for any reason.

Don’t dive in the virtual recruiting interview pool without a small practice

Virtual interviews have their challenges. One of the biggest is the conversation flow, which may at times become robotic.
Try to be calm and patient. Pitch in to the conversation with something you have read or documented about the company you are considering joining.
Adjust your body language and don’t sulk (adjust your posture and sit upright, without seeming stiff). Don’t be irritated if the recruiter is taking longer to respond.
Remember that there is a two-way street to the video interview game and that the recruiter is also human 🙂 Loosen the connection with the interviewer and show that you are a team player, capable to adapt to diverse situations.
Have a practice run ahead of the actual interview, as this might prove to be your winning ticket to a new job.

Also take into consideration, ahead of the interview to:

Good luck!

Artificial Intelligence – it goes by many names and it’s definitely here to stay. Whether we call it machine learning, machine intelligence, thinking machine, electronic brain, Artificial Intelligence impacts technology trends and how companies relate to it.

Machine learning is changing companies’ DNA

Over the past 2 years, in particular, there has been a flurry of activity in this respect. Companies have been born carrying the Artificial Intelligence DNA exclusively.

It all makes sense: machine learning is a powerful tool with tremendous potential. It encompasses a staggering range of applications. Off the top of our head, here’s a few: recommendation search engines, fraud identification, detecting and predicting machine failure, optimizing options-trading strategies, diagnosing health conditions, speech recognition and translation, enabling conversations with chatbots, image recognition and classification, spam detection. Basically it can predict everything. From how likely someone is to click on an advertisement, through to how many new patients a hospital will admit.

Therefore at VON Consulting we have a deep interest in how technology impacts software and hardware applications and how it will continue to do so in the future, in particular through our Tech Division. Our team of professionals is able to advise our clients, prior to incorporating new technologies in their business plan, with a healthy validity assessment.

The validity-assessing scheme we propose in AI integration

Step 1: Identifying the problem/opportunity
We recommend you always start with the problem statement. What does your company say it’s trying to do, and is it worthy of machine learning? And how can AI become an opportunity in this framework?

Step 2: Approaching the problem/opportunity
This is where we want to figure out how your company has reframed its problem statement into a machine-learning problem, and determine what data it would need to input into its algorithms.

Step 3: Sourcing training data
Once we know the kind of data your company needs, we want to know how you should go about acquiring it. Most AI applications use supervised machine learning, which requires clean, high-quality labeled data. Who is labeling the data? And if the labels capture something subjective like emotions, do they follow a scientific standard? Knowing the details of this part of the pipeline also helps you identify any potential sources of data collection or labeling bias.

Step 4: Auditing products
Now we should examine whether your company tests its products. How accurate are your algorithms? Are they audited for bias? How often does it reevaluate its algorithms to make sure they’re still performing up to par? If your company doesn’t yet have algorithms that reach its desired accuracy or fairness, what plans does it have to make sure it will, before deployment?

Step 5: Decision call
In this particular step, you should consider the benefits of having this technology available. Also, if they outweigh the potential human rights violations of emotional surveillance. One more question needs to be asked: does your company have mechanisms in place to mitigate any possible negative impacts?

What to do, as a company?

As such, we advise any company with a quality machine-learning product to check off all the boxes above. Basically, it should be tackling a problem fit for machine learning and have robust data acquisition and auditing processes. Also, to have highly accurate algorithms or a plan to improve them and be grappling head-on with ethical questions.
Our team is here to assist you with this evaluation process as well as hands on technology integration, product development and launches.

For all of its potential to increase efficiency, working-from-home also presents unique challenges.
One of the main advantages of working-from-home is that it eliminates certain distractions, however it also opens the door to new ones, temptations to do non-work related things.
One other important aspect to consider is that the home environment itself can be a challenge if it’s not suitable for working. Whereas office buildings are generally designed to enhance productivity, such as with adequate lighting and space, your home probably wasn’t.

With that in mind, we’ve put together a short list of tips that might help you overcome potential hurdles (they helped our team).

Choose the right working space

Setup, setup, setup! It’s a good idea to have a space at home that’s dedicated to work, whether it’s a dedicated room or a defined space, where you can run both a laptop and desktop, if need be, within reach of some ‘perks’, such as your coffee machine (this is how you prevent a coffee making trip from turning into an hour’s time waster). Choose a space that’s airy, spacious enough and comfortable.

Focus on having a working routine

It sounds great; the idea that you can have the liberty to adjust your working schedule. It also may prove to be tricky, as you can end up either burning the candle at both ends, or reduce your productivity. Try to divide your most productive time frames, if your company allows it – for instance, early morning (7-11 a.m.) and then again in the early evening (3-7 p.m). Having a routine lets you focus on work and schedule other stuff in the time you have spare.

Try to allot daily time to offline activities

It can be very easy when you work from home to end up glued to your chair, for work-related, as well as personal tasks. That’s not good for your health or your productivity. Make sure that you build in time to exercise (at least take a walk) and get out of your workspace. Working from home should not mean working round the clock any more than it should mean never working at all.

Don’t disregard healthy eating habits

Sitting on your backside all day at home is fraught with risk anyway. So don’t push yourself any further over the edge by living on a diet of fast food and soft drinks. Granted, we know, this is easier said than done. It’s hard to resist the occasional splurge. It’s still a hard cold fact: the more junk you eat, the harder it is to find any motivation to get stuff finished.

Avoid blurry traps that get you out of the workflow mindset

Whilst you may occasionally prefer to dress down when working-from-home, try to get dressed for it, once in a while. Why? The act of getting dressed is something that you take on in work-from-office life. It reminds you that you are going to work and not just sitting in front of the computer all day. It also prevents you from accidentally surprising colleagues and clients when you answer a video call.


• Design, technical delivery and project management of Central Voice Platforms and Services, in particular, focusing on Central Number Portability Database platform, including:
• Infrastructure design, delivery and testing, including configuration and development of new features and capabilities.
• Review and assess platform status based on best practices, engineering principles and operational key performance indicators.
• Creation and maintenance of the platform capacity plan and executing the capacity planning process.
• Service customers and suppliers on-boarding, including design, delivery and testing.
• 3rd level operational support (e.g. troubleshooting and problem management) during platform operation.


With these activities you will have a great impact on our business:

• Complete platform lifecycle management: definition and maintenance of the platform architecture and design principles, virtualized infrastructure and software releases.
• Management of new service functionalities, from assessment, to implementation, including roadmap release control, feature design, development, testing and acceptance, implementation and performance optimization.
• Customer and supplier onboarding, ensuring service levels and data quality.
• Drive platform’s quality and continuous improvement.
• Operational support (Level 3) and problem management during major incidents.


With these skills you are a great candidate:

• Solid understanding of number portability platforms architecture and functionalities.
• Strong experience in national and international interconnect and roaming infrastructure, including signaling platforms (experience with NetNumber technology would be preferable) and relevant protocols (e.g. ENUM, DNS, SIP, Diameter, SS7).
• Good knowledge of platform infrastructure, including OSs (Linux), database management, IP connectivity and virtualized environments (VMWare).
• Track record of capacity and SW release management incl. planning, delivery and reporting.
• Telecommunications industry and project delivery experience.


We’ve got even more to offer:

•Work from Home – You can have home office 2 days per week
•Medical and dental services
•Life insurance
•Dedicated employee phone subscription
•Special discounts for gyms and retailers
•Annual Company Bonus
•Ongoing Education – we continuously invest in you to ensure you have everything needed to excel on the job and enhance your skills
•You get to work with tried and trusted web-technology
•Getting in on the ground floor of a technology changing company
•Flexible Vacation – Take time off when you need it, we trust you

It’s morning. Coffee mugs of all shapes and sizes start flooding the office. You take a seat at your desk, excited to start your work for the day. As always, the younger coworkers’ voices reach your ears, making you furious. They won’t stop chatting about the latest Facebook posts, or complaining about the inflexible work schedule, stiff coworkers, the number of official policies they have to remember, and god knows how many other things. Sounds familiar?

They are the millennials- those born between 1984-2000, often described as narcissistic, lazy and disinterested. „Born with a smartphone”, this generation has a never-before seen ability to adapt to the new and to happily welcome changes within society, traits which earned them the nickname „digital natives”. Among this generation’s characteristics, we can highlight the deep desire to quickly climb the  professional ladder, the ease with which they switch jobs as soon as something better comes along, a constant need for approval, as well as an innate openness to change of any kind.

At a glance, the millennial demographic may seem a nightmare at the workplace, like too much to handle. Some organizations have a flexible culture, the emphasis being on young employees, while, in others, senior workers are more appreciated. How can we harmoniously collaborate with these kinds of people at the workplace, regardless of the company’s environment?

Firstly, it is important to understand that millenials owe a big part of their personality to their age. They are young, freshly emerging on the labour market and excited to be acknowledged by the world- normal traits for anyone just beginning the journey of their career. Then, every demographic’s personality is fundamentally influenced by certain events or happenings from society. If the Baby Boomers saw the rise of the technological era and the spread of media channels, the millenials are those who are completely immersed in this phenomenon, digitization being a part of all aspects of their lives. Technology brought about new ways of interacting, learning and, frankly, of looking at society and the environment, while emphasizing the idea of unity, broadening of horizons and shaping the concept of „global citizen”.

However, in every country influences of the place’s cultural values exist and manifest, especially through other citizens. These can not be that easily swayed by external events. Thus, traits which are millenial-specific in Romania may differ, more or less, from millenials in other countries.

According to Dragoş Iliescu (during a speech within Romanian Youth Focus, 2015), the Romanian millennial generation is one which is more individualistic, with a higher dose of hedonism, who tends towards decentralization of power, preferring instead that companies have hierarchies based more on convenience, way more flexible than the traditional ones. In regards to their personality, romanian millenials are more narcissistic, and with a lower emotional stability-  having received, growing up, mostly positive feedback, this demographic developed a lower tolerance to negative feedback and critique. According to data, romanian millenials are, also, a more extravert generation, witnessing a rise in perseverance and conscientiousness.

Thus, it becomes obvious that a big part of job conflicts between millenials and more senior employees are, mostly, a normal part of intergenerational conflicts. However, this generation poses both a challenge, as well as an opportunity for managers to review  and to update their relationship with their employees. A study recently conducted by PwC comes to our aid in this regard, offering a couple of practical advice, which can be implemented right away: