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Field Tips Series- Streamlining & reducing cost of Business Intelligence- Evaluate Open Source
You can reduce your costs, by gradually testing and adopting Open-Source BI in a select set of areas. Open-source BI is gradually gaining attention. Open Source BI is essentially business intelligence software which is open-source. There is a difference within open source and commercial open source. In this page we are talking about commercial open source (don't even think of pure open source, if you are a medium level enterprise and above), which is not free of cost but of minimal cost, with adequate support and services infrastructure. Pentaho and Jasper are examples of commercial open source.
 
This page of 'Principles and Rules' is linked to:  Data Analysis/OLAP, BI platform Tools Evaluation, Data Quality, BI business intelligence end-to-end view, Data Warehousing,

Open source BI brings in the advantages of

  • Low cost
  • Quicker fixing of bugs.
  • Easier to integrate with the other application, as the API used are not proprietary.

However, Open source (at this point of time), should not be seen as the replacement of your core BI platform. The reasons are:

  • Its end to end BI platform capabilities and robustness has not been proven over a time-span and across various organizational scenarios.
  • The ease of use of the proprietary BI platforms, and user friendly documentation (though open source has more comprehensive and transparent documentation.
  • The BI platform providers bring in a whole framework of BI implementations, which is critical element of success.

We recommend Open Source to be used for the peripheral or non-core platforms like:

  • Interactive visualization tools
  • Performance management tools
  • Business modeling tools
  • Reporting & Querying tools. These are not enterprise reporting tools, but used for small-scale ad hoc querying and analysis.
  • Core elements like OLAP servers, ETL, Enterprise Reporting Tools, Enterprise Analytics tools for non-critical stand-alone BI requirements. This can be taken as a pilot for a functional level data-mart.

This open-source BI usage approach has the following advantages:

  • It allows you to gain experience on how to handle the open-source environments, without risking your core installations.
  • It has a good cost-advantage. One of the biggest barrier of making BI to reach every end-user is the user-based/client based licensing of proprietary BI. In this kind of licensing regime, one needs to pay for every user who wants to view a report. Though the cost per license is minor but it adds to huge costs for a large user-base. Even if there is an enterprise level license, it has an inherent usage driven license fee calculation.
  • Open-source data presentation tools, are best of both the worlds, as they free of cost (or even if there is a license for commercial open source, it is typically at an enterprise level and quite cheap), and non-risky for this kind of application. This is one area, which is a Quick-hit

As you evaluate open-source, one has to be more diligent as this is a new trend. Even if the commercial open source is a very low-cost, every acquisition takes a lot of energy, and you may not like to go wrong. While we have separate section (under tool domain) for vendor and tool evaluation, the broad items, which one has to focus more for open-source BI are:

  • Licensing terms of commercial open source.
  • Watch a comprehensive demo.
  • Check on the framework they have on resolving bugs and issues.
  • The Support SLAs.
  • Proposed upgrade path.
  • Retro-fitting support.
  • Check on Consulting and IT service providers, which are the implementation partners of these packages.
  • Diligent reference checks
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