Open Source Software

Using Open Source Software for Data Management, by Julie Hunt

another insightful article by Hub Designs Magazine’s editor, Julie Hunt

While there has been growth in Sofware-as-a-Service (SaaS) and Cloud software offerings for MDM, there hasn’t been as much activity for open source software options (OSS) for enterprise MDM.

For several years, MDM OSS offerings have emerged that, for the most part, provide basic though limited capabilities. However, for MDM-related solutions such as data integration and data quality, stronger OSS options have been increasing over the years. So eventually, OSS may become more viable for fulfilling the requirements of an end-to-end enterprise MDM solution.

Talend, a vendor for OSS data management tools, makes the argument that OSS options become more attractive when a software solution space achieves maturity:

The industry having evolved and matured, there are solid definitions of the requirements placed on an MDM system. A standard definition of requirements marks the beginning of the commoditization of the market and the entry of open source.

The idea of commoditization of a software solution space marking the debut of OSS options works fine, but it doesn’t mean that OSS will be a successful option for all solution domains. MDM for many enterprises requires sophisticated and well-defined software capabilities that support many areas including the data management practices, processes, and roles of people that must be handled well to achieve success with MDM initiatives.

The Right Fit – And The Right Solution

picture of Lock and KeyFor a while, open source software was touted as a ‘free’ option for software solutions. Time and experience have revealed many of the “hidden” costs for OSS implementations. The community approach to the OSS code base has been successful for many vendors and does indeed offer free access to the code. However, things change when OSS vendors seek to make money from the software. Most vendors have added separate for-fee “enterprise” versions of the software that in some ways provide little difference from typical on-premises licensed or SaaS versions of enterprise software.

It is essential then to understand what it takes to use OSS for data management and how to assess whether OSS is the right fit for a particular organization. Lyndsay Wise tackles this serious task for the Business Intelligence (BI) software domain in her new book Using Open Source Platforms for Business Intelligence – Avoid Pitfalls and Maximize ROI. Lyndsay is an industry analyst and advisor for organizations with regard to the selection of BI software solutions that will meet their needs.

Lyndsay does a thorough job of dissecting the kind of technology resource commitment that it takes to travel the OSS path for Business Intelligence (OSBI) solutions. Lyndsay rigorously considers why an organization might consider OSBI, with thorough substantiation of her thinking. She draws on her many years of advising organizations of all sizes, to provide a fair and honest survey of the challenges, drawbacks and benefits of OSBI (Chapter 7 is particularly strong in this area).

Lyndsay makes clear what the overall costs are for OSBI and that many times, it is not a ‘free’ option for organizations. In fact, OSS may not be a good choice for most small businesses, and frequently may not be suitable for many mid-sized companies – due to the on-going IT resources that implementations and maintenance can consume. Often larger enterprises are better suited to the adoption of OSS, as long as software development is a strength and key strategy for the direction of IT, in support of business objectives. It may well be that OSBI will emerge as preferable to traditional BI solutions for certain organizations. Lyndsay provides the guidance to find out if that is the case.

To help an organization understand if OSS is a good fit, Lyndsay has created very useful tools through items like “readiness checklists” (Chapter 18), as well as frequent assessment lists at the end of many chapters. She continuously asks all the right questions.

An important point is that much of what Lyndsay details in her book for evaluating OSS for BI, including the checklists and assessment lists, can be applied to other software domains and solution requirements.

Most of Lyndsay’s OSBI assessments are focused on technology and the in-house IT team, simply because OSS is technology-intensive. There is less value from the pure business perspective for OSS in and of itself. For the business side of the story, the value comes from solving business problems, ease-of-use, excellent performance, reasonable cost, just as it would for any kind of BI – or other – software solution.

Convergence and Business Value

It’s not a stretch to take the guidance for assessing the viability of OSS for BI and apply it to other data management solutions when evaluating OSS options. For some time, there has been parallel development and convergence of the many solutions in the data management domain anyway. These solutions include MDM, data integration, data quality, BI, and business process management (BPM).

Separately these solutions can bring value and successful outcomes to the enterprise, but frequently at the cost of duplicated effort and resources.

A good starting place is finding the points of commonality across data-related technologies, where lessons learned in one solution area can be applied to other solutions, in support of unified goals. MDM itself is a reflection of how an enterprise uses data for business purposes. A corporate data strategy is critical to facilitate the integration of data infrastructure, technologies and processes to ensure that enterprises make the best use of data and the business and IT teams that make it all happen.

The question of using OSS for a single domain such as BI or MDM takes on larger importance for enterprises that want to better integrate the components of the data infrastructure and reduce duplicate effort and silos. For each organization, the question becomes: does OSS have a fit for the desired symbiosis of data-related technology solutions?

About The Author

Julie Hunt is the editor of Hub Designs Magazine and an independent software industry analyst and consultant for solution and customer strategies. She has worked in the B2B software industry on the vendor side for more than 25 years in roles from the very technical (developer, SE, solutions consultant) to customer-focused work in strategies for products and solutions, future trends, and go-to-market initiatives. Julie also writes extensively for several online publications, covering software industry topics.

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