software security

Big data analytics has become the “new black” in business, and the “date pipeline” is more often heard in companies than “we broke the product.” So what is so special and why is everyone talking about it?

Who Is a Big Data Engineer?

Obviously, if you want to analyze big data, the last one should be appropriately collected and stored. This is exactly what the Data Engineer does: he sets up the infrastructure for Big Data, corporate data warehouses, and third-party sources (mail, CRM-, ERP- and other applied systems).

Thus, the data engineer’s duties encompass the following:

● organization of an automated collection of data into single centralized storage;

● moving and storing information arrays;

● customization, integration, and creation of data for analysts and researchers;

● control and improvement of data quality.

According to Dataversity, any data scientist must be able to prove the correctness of their conclusions. This requires knowledge of statistics and basic mathematics related to statistics.

Machine learning and data analysis tools are indispensable in today’s world. If familiar tools are not available, you need to have the skills to quickly learn new tools, create simple scripts to automate tasks.

It is important to note that the data scientist must effectively communicate the results of the analysis. In this, he will be helped by visualizing data or the results of research and testing hypotheses. Specialists should be able to create charts and graphs, use visualization tools, understand and explain data from dashboards.

Three areas come to the fore for the data engineer:

● Algorithms and data structures. It is important to get your hands on when writing code and using basic structures and algorithms: analysis of the complexity of algorithms, the ability to write understandable supported code, batch processing, real-time processing.

● Databases and data warehouses, Business Intelligence: storage and processing of data, design of complete systems, data Ingestion, distributed file systems.

● Hadoop and Big Data. Data is becoming more and more, and on the horizon of 3-5 years, these technologies will become necessary for every engineer.

Machine learning will be ubiquitous, and it is important to understand what business problems it will help solve. It is not necessary to be able to make models (data Scientists can handle this), but you need to understand their application and the corresponding requirements.

What to Do to Find a Specialist

Don’t look for a unicorn. People with all these skills are already involved in interesting projects, lead teams, or are very expensive. The growing presence of women in engineering in 2021 is proof of that.

Try to highlight the key characteristics for the candidate. Decide what you would like to implement or establish in the first place, and build on this. Remember, finding someone who has worked with all of the tools can be difficult. Focus on skills. If a person has experience in MySQL, but not in Google BigQuery, that’s okay. Adaptation is minimal and there is more choice of candidates.

Don’t be afraid to spend time talking to a large number of candidates. Remember, you need an active business representative. The analyst will personally show whether he is ready to be part of the product, to fight for it and develop, or if he prefers the role of the performer.

More often than not the employer hired an employee for hard skills and test skills, and then it turned out that the specialist could only perform the assigned tasks. It is better to forgive the candidate for the lack of technical skills but focus on his inquisitiveness, initiative, and openness. The skills of working with Tag Manager and Google Analytics can be improved in a month, but motivation is more difficult to find.

How to Build the Perfect Big Data Team

Take a look at statistics from a dedicated report published by Raconteur, an internationally renowned content marketing firm. The infographic breaks down the current production of data into sections based on the source. It also predicts that by 2025 we will be creating over 400 exabytes (4 x 1020 bytes) every day! Also worth noting is the 28 petabytes of data expected to be generated from wearable devices only by 2020. This is perhaps just a small fraction of the data expected from millions of other IoT devices.

Given these statistics, there is no doubt that the future of corporations will be even more dependent on data than it is now. If you feel that your business is becoming increasingly data-driven, then it’s time to tackle big data solutions. This does not mean, “Just buy some fancy data analysis tools and your job is done!” You need to involve people who specialize in this particular field and know how to use these special tools correctly to turn your random data into useful information.

So, how to hire world-class engineers? The best answer to this question will be looking at international engineering marketplaces such as Engre. This is a platform that provides customers with a wide range of engineering services. It is a place where contractors meet with businesses: specialists are looking for interesting projects as well as businesses find a professional team of workers.