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Advanced analytics software - ease of use most important factor

According to a new study by BARC, ease of use is the most important purchase criterion for companies selecting an advanced analytics solution.
E-3 Magazine
June 21, 2019
Advanced analytics software - ease of use most important factor
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This text has been automatically translated from German to English.

52 percent of companies say that usability is a reason for Data Scientists to choose their software. At the same time, usability is very important for business analysts, with 51 percent of companies citing it as a reason for purchase.

Other important factors for software buyers include coverage of specific requirements (46 percent), a code-free environment (39 percent) and compelling performance (36 percent).

The fact that the software has governance functions and concepts, on the other hand, only plays a role for a small proportion of companies (12 percent).

"Analytics software users belong to a heterogeneous group:

From technically oriented Data Scientists and Machine Learning Engineers who work on data analytics to Business Analysts who focus more on visual analytics and data exploration.

The latter group, which prefers visual user interfaces to programming, is becoming increasingly important"

says Sebastian Dervish, BARC analyst and co-author of the study.

"For this reason, software vendors are now increasingly trying to provide code-free user interfaces and user guidance to make analytics as accessible as possible for users."

The benefits achieved by open source users and commercial software users are largely congruent, but with some interesting exceptions.

48 percent of users of commercial analytics software achieve increased transparency of data use, while the corresponding figure in the open source community is only 36 percent. In addition, users of commercial software more often report improved employee satisfaction.

Only one-third of open source users achieve greater cost reduction.

"Considering that open source software is free, it's surprising that cost savings aren't achieved more often"

Dervish comments.

"One possible reason is that running open source software can require additional effort. Another explanation could be that Data Scientists with knowledge of open source languages are often absent and thus cost more."

Open source scores with functionality, commercial software has other advantages.

Graphic Barc
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