Importance of Data and Analytics Skills in 2022

The importance of data analytics for business growth has been growing exponentially in the last decade. According to the statistics, the big global data and business analytics (BDA) market grew from 168.8 billion U.S. dollars in 2018 to 215.7 billion U.S. in 2021.

Data analytics penetrates different parts of the business process growing from the realm of specialized departments into the routine skills any worker should have.

In this article, we’ll share some thoughts on what data analytic skills are essential in 2022 and what will be trending in the following periods.

Data management

Companies approach data management in different ways. Some have roles and departments dedicated to this task, while others train all the staff on this skill.

Today, numerous data management systems work in physical or cloud environments and are widely used for data management automation.  

As an option, numerous companies outsource data analytics and management as a part of DevOps outsourcing. Practically, any role in data management, such as a data architect or engineer, database administrator, or information security analyst, can be outsourced today.

This way is perfect in case of a need to quickly solve data-related tasks when the in-house team is incapable of the workload.

The heightened attention to employee training in data management, the appearance of new roles, and specialization all prove that data management is an essential data analytics trend and will remain a valuable skill in the future workforce market.

Statistical visualization

The future data will be characterized by high velocity, volume, and variety. Therefore, handling the data with the usual means will be more complex. Services and skills in data visualization will grow in importance in 2022.

According to the forecast, only IoT devices will generate 79.4 ZBs of data in 2025. The increasing volume and complexity of data sets will require new and better means of visual presentation, as well as a higher level of proficiency in using visualization tools like Tableau and others.

Since businesses are becoming more reliant on data, any employee should be able to skillfully transform data analysis results into dashboards, visualizations, reports, and data models.

Data science and machine learning

Although employees are not generally demanded to be proficient in machine learning, literacy in this domain may become an important or even a must-have skill in the nearest future.

Machine learning is a sub-division of AI development dedicated to creating algorithms that can spot patterns in big data sets.

With the growing mobile and cloud computing traffic, and the growth of new technologies like AI (including machine learning), how we treat and process data will change.

In the future, we’ll have new statistical and analytic tools. Since data broadens businesses’ ability to spot trends early, everyone will try to master data science and use machine learning algorithms.

In conclusion

Based on the prevailing trends, it gets evident that companies ignoring data analytics will be outside the competition in future markets. Although not all the developments are clear now, we can see that data analytics moves towards further elaboration and complication. We are to expect new tools, methods, and technologies as well.

The following two tabs change content below.

Recent Posts

Posts by Topic

Here is the sidebar widget