As master data management (MDM) and data integration (DI) initiatives become more common within organizations, many companies move from individual data-related projects to a broader approach to data management (DM) in general. The realization that information drives business decisions leads businesses to look more closely at how they are managing their information assets, including data quality, data cleansing, and data profiling initiatives. The combination of initiatives is leading organizations towards a more holistic approach to the way they view and implement data management practices.
Consequently, solution providers such as SAS (through DataFlux), Informatica, and Kalido are working towards the development of a cohesive platform approach to data management initiatives. This step towards a one-stop approach to DM provides the basis for companies to start in one place (for instance, their ETL and data quality processes) and expand their DM related projects without having to look for new solutions or additional products as their DM environment matures.
With the addition of the platform approach to DM, solution providers are integrating MDM functionality and data governance (DG) into the mix. From recent acquisitions of best of breed MDM players, to solution providers adding seamless integration capabilities, and an increasing focus on DG, organizations will now be able to manage data entities within the organization as part of their data management as opposed separately. The key value is that in order to gain visibility and identify contributing factors to customer satisfaction, buying patterns, supply chain, marketing initiative success, etc. organizations need to have access to data. But this data has to be relevant, valid, and connect to other valid pieces of information. This means that combining data quality and data governance with MDM gives customers the advantage of managing their information assets continuously and combining that with ongoing and new data integration initiatives.
Although the platform concept is new, the idea behind creating a single way to manage data from operations through insight is a good one. Realistically, however, companies are still at the beginning of their holistic data management journeys. Early adopters and organizations with mature DM environments are well poised to take advantage of a holistic approach to data management. For other organizations, the trick will be how to decide where to start and what aspects of data management are most able to provide initial value to the business, while still providing the appropriate stepping stones for future growth.
About the Author
Lyndsay Wise is an industry analyst for business intelligence. For over seven years, she has assisted clients in business systems analysis, software selection and implementation of enterprise applications. Lyndsay is the channel expert for BI for the Mid-Market at B-eye-Network and conducts research of leading technologies, products and vendors in business intelligence, marketing performance management, master data management, and unstructured data. She can be reached at email@example.com. And please visit Lyndsay's blog at myblog.wiseanalytics.com.
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