Is Open Source Analytics Software The Right Option?

Should your company look to exploit open source?


LinkedIn’s decision to move its real-time analytics engine, Pinot, to an Open Source (OS) license is already attracting attention from a number of fast-growing start-ups looking for analytics software. Pinot monitors, manages, and utilizes the vast and complex datasets produced across LinkedIn’s professional social networks and digital publishing products. It is the latest piece of software that LinkedIn has chosen to make available on an OS license.

But is using OS software the correct decision for a company looking to take advantage of the data they are now generating?

When looking for an analytics solution, it is important that a company first determine whether OS is the right option. Much of this will come down to costs, or rather lack thereof. For start-ups and SMEs, it is usually the case that OS software will be the most attractive option because it’s free. There is also no vendor lock in, so should the software not work to your liking there are no contracts to break.

This freedom extends to every area of usage. OS software gives you the option of operating, sharing, and modifying the software as you choose.

It is also a boon to innovation, with collaborators able to access the software from around the world to share ideas and add features that could improve it. An InformationWeek survey of 420 business-technology professionals found that over 60% of firms believed OS software offered more opportunities for rapid innovation, compared to less than 10% who said that it offered fewer.

There are, however, a number of drawbacks to using OS software. While implementation involves low costs, these may end up being paid for elsewhere as it is often more complicated to use than its proprietary equivalent, due to either lower productivity or the additional training necessary to use it effectively. This is further complicated by a lack of support with OS software, which are usually at hand to offer help around the the clock.

It is also the case that OS software is often provided by people out of generosity, and it could happen that they simply get bored and move on. However, this is not likely to be the case with something like Pinot or other OS technologies that are supported by major commercial organizations.

In Lyndsay Wise’s book, Using Open Source Platforms for Business Intelligence: Avoid Pitfalls and Maximize ROI, she notes four questions that should be asked by a firm before they make the decision to adopt OS software:

  • Why you are adopting BI?
  • What you hope to achieve -- both on a departmental level as well as organization-wide?
  • What exists in-house in relation to software, hardware, skillsets, and comfort factors?
  • Whether OS is right for the organization by looking at the potential benefits outside of initial software costs?
  • The long-term benefits of BI adoption and how the type of solution selected now will affect use in the future?

It is important to know the answers to these in order to get the best idea of what sort of software you should look for, and whether OS or proprietary software will offer you the best ROI.


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