Open Source Data Management or Do-it-Yourself

With the tough economy people are still cutting back on corporate spending.  There is a sense of urgency to just get things done, and sometimes that can lead to hand-coding your own data integration, data quality or MDM functions. When you begin to develop your plan and strategies for data management, you have to think about all the hidden costs of getting solutions out-of-the-box versus building on your own.

Reusability is one key consideration. Using data management technologies that only plug into one system just doesn’t make sense.  It’s difficult to get that re-usability with custom code, unless your programmers have high visibility into other projects. On the other hand, all tool vendors, even open source ones have pressure from their clients to support multiple databases and business solutions.  Open source solutions are built to work in a wider variety of architectures. You can move your data management processes between JD Edwards and SAP and SalesForce, for example, with relative ease.

Indemnity is another consideration. What if something goes wrong with your home-grown solution after the chief architect leaves his job? Who are you going to call? If something goes wrong with your open source solution, you can turn to the community or call the vendor for support.

Long-term costs are yet another issue.  Home-grown solutions have the tendency to start cheap and get more expensive as time goes on.  It’s difficult to manage custom code, especially if it is poorly documented. You hire consultants to manage code.  Eventually, you have to rip and replace and that can be costly.

You should consider your human resources, too. Does it make sense to have a team work on hand-coding database extractions and transformation, or would the total cost/benefit be better if you used an open source data integration tool? It might just free up some of your programmers to pursue more important, ROI-centric ventures.

If you’re thinking of cooking up your own technical solutions for data management, hoping to just get it done, think again. Your most economical solution might just be to leverage the community of experts and go with open source.