3 Trends in Data Analytics that We'll See More of in 2020

Data Basics, Scaling AI Nancy Koleva

New types of data, tools, and technologies are shaping the jobs of analysts, taking them in exciting new directions. In fact, things are moving so fast in the data analytics space, that some analysts are beginning to worry about what this could mean for the future of their jobs.

Smart machine learning algorithms can now analyze and interpret data with an ever- growing speed and accuracy, and even produce content for dashboards and printable reports. So as another year comes to an end, you may be wondering, will my job as an analyst still be in demand in 2020 and beyond?

Our answer is YES: as with any other job out there, the role of data and business analysts might evolve in order to keep up with the most recent innovations, but rest assured, it is here to stay. In fact, the continuous developments in AI, machine learning, and automation, when implemented the right way, are less of a threat than an opportunity for data analysts.

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These are some of the upcoming data and business analytics trends to look out for in order to future-proof your career in 2020 and beyond:

Data Analysis Skills Will Continue To Be In High Demand

Data-related skills are, and will continue to be, in high demand. Forecasts seem to suggest that the most important role data technologists will play in the near future is that of a data analyst. The reason behind this growing trend is the increasing automation of many data-related tasks, and the growing importance of data analysis by humans.

In the new decade, business analytics will be less about hoarding data and more about acting intelligently on data-driven insights, a task for which no one is better suited than analysts.

AutoML Will Have Even Broader Applications

At a very high level, AutoML is about using machine learning techniques to, well, automatically do machine learning. Its development, however, has spurred the application of automation to the whole data-to-insights pipeline, from cleaning the data to operationalization. At this larger scale, it’s no longer AutoML, but augmented analytics. Today, automated analytics can add efficiency to large swaths of the data pipeline, with the potential to impact the entire process and influence the structure of data teams long term.

Data Science And Business Intelligence Converge

Organizations have traditionally employed separate teams for standard business intelligence and data science, but this is all about to change soon. The two areas are increasingly converging as the applications of the different technologies are growing together.

In 2019, we’re likely to see more cutting-edge organizations bring their data science and business intelligence practices together, providing them with real-time centralized access to various sources of data.

With data science and business analytics increasingly converging, you might want to stay up to date with the latest trends in data science as well - check out our predictions for 2020 in this video:

 

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