The term Business Analytics – a replacement of the older “Business Intelligence” – represents at best an umbrella term, covering a large variety of business needs:

      1 - 
Data Query and Visualization
      2 - 
Enterprise Reporting
      3 - 
Performance Management
      4 - 
Information Discovery
      5 - 
Machine Learning
      6 - 
Data Mining
      7 - 
Econometric Modeling
      8 - 
Big Data

 

Business Analytics Functional Areas

At this moment, there are available a wide range of instruments and technologies answering to the listed needs (most cases, one tool answers to more of the functional areas described above), both commercial off the shelf (COTS)/ proprietary as well as open-source.

Most of the solutions are covering several functional areas (while in this document only the most significant areas of well-known solutions are presented), but always only some (not all!) of the range mentioned before.

The solutions are still unstandardized functionality-wise (unlike the ERP applications, for instance. Choosing the wrong solutions (which does not have well developed a critical area for the company making the choice) can lead to situations similar to “beating nails with a microscope” or “using boxing gloves instead of tweezers”.

 

Data Query and Visualization

What? The need to ask questions and to manipulate intuitively data structures otherwise abstract, in order to understand the relations between the model’s various parameters evolution.

How? Traditionally, the dominant technology was the on-line analytical processing (OLAP), but more recently other models have appeared (the associative model, visual query interrogation languages, etc.)

With What? Both tools specialized in visualization – such as QlikView (from QlikTech),  as well as generic engines with newer visualization developments - Microsoft (MS Analysis Services with Power View). Also, there are available proprietary (Oracle Essbase) or open-source (Mondrian) OLAP engines .