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The BI Trends for 2018 – common sense for successful BI projects

Posted on: 18-12-2017 10:13:501328

BI trends for 2018

2018 kicks off in a couple of weeks. Time to check some predictions, for example on Business Intelligence. So, I Googled “BI Trends 2018” and started reading the content, both from BI suppliers, as well as from independent research & consulting companies. And guess what… the BI suppliers are (of course) predicting world-changing exciting developments, like augmented analytics, natural language processing, artificial intelligence and machine learning. The researchers tend (also of course) to focus more on the things that must be solidly in place before adopting these world-changing stuff. Luckily, they have several topics in common, Data Quality, Data visualization, Data discovery, Self-service BI, Mobile BI (also on my smartphone please), Data governance, Real-time analytics, Predictive analytics and Agile BI development, to name a few.

BARC (check provides a neat Data Visualization example on a BI trend Top-20, based on a broad survey of more than 2,700 BI professionals.

BI trends for 2018


#1 Master data / data quality management

Let’s have a look on the top-6 in this graph, starting with a quote from BARC’s November 14, 2017 press release: “For the first time, BI users and practitioners identify master data / data quality management as the #1 trend in the business intelligence (BI) industry at the moment. In third position last year, this trend now occupies the top spot ahead of data discovery / visualization and self-service BI.”

As an information engineer and member of the ‘researcher school’ I have to say ‘Yes! Finally!’. What use is it to introduce eye-catching graphs, interactive geographical maps or whatever new flashing user interface technique, when your data is crap. It is basic logic to clean it up first.

#2 Data discovery / visualization

Second on the list is “Data discovery/Visualization”. Not too many business users can analyze stuff on sight in lists of figures. But most business users can spot trends and peak values on sight in a graphical representation, so it is also logic that this one comes second.

 #3 Self-Service BI

And the third on the list “Self-Service BI”. Again, plain logic… the business environment is changing at a high pace; thus, the business user’s information need is changing at the same speed; thus, the user cannot allow to wait for three months to get a report from the IT department (if and only if she or he had a solid business case and was able to correctly specify what she or he needed). That’s why Self-Service BI is so high on the list. And it must be more than the ‘here are some cubes that you can drag fields from’-BI, because many operational questions have an ‘ad hoc’-character. In laymen speak: ‘This morning I was not even aware the question existed, now I need the answer yesterday, and when I have the answer, I will probably know what to do and how to prevent from having to ask the question again, so tomorrow the software you built is no longer needed’. Many IT/BI specialists will let this cup pass by to avoid nervous breakdowns, won’t they. And so, consequently, many business users will build or buy some more shadow-IT themselves. One needs governed ‘True Business User Self-Service’ to cope with ad hoc questions, meaning ‘a business user can answer more than 90 % of his operational questions, within three minutes and without the help of IT.”

#4 Data Governance & #5 Data preparation for business users

If something will bring agility to the BI department, ‘True Business User Self-Service’ will. But that can only be provided with properly governed basic data and analysis logic (ergo Data governance as topic 4) and when the data is prepared to be used by business users, hence topic 5. The user needs information (data combined with business logic), not just data in hundreds of tables.

#6 Real-time analytics

And (topic 6) there is of course a need to have as near real-time as possible data, because all this technology with outdated data would not be too effective, would it. It doesn’t mean that all the information must be ‘last-second’, which might be necessary for specific services, yet in general it isn’t. Analysts don’t like ‘dancing figures’ on their screen when analyzing, and that’s why these analyses are based on frequently refreshed snap shots.

As an information engineer I admit… AI, Big Data, Machine learning, Data Science are fascinating fields of knowledge and it’s fun and interesting reading about it.

Yet topics 1 to 6 are common sense and mandatory to get more successful BI projects, so, let’s focus on that first.


Jacques Adriaansen
Business Improvement Thought Leader | LinkedIn

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