Data Apart Together

Managing and governing data in an unpredictable, highly distributed context requires an, agile, federative mindset right from the start, in every decision

The single source of truth in corporate data is like the Holy Grail: great to pursue yet destined not to be found. Therefore, organizations must adapt to a federated business reality. As a result, many different sources, uses, and perspectives of data exist both inside and outside the corporate perimeter. Enter meta-data management, master data management, and federated analytics. They deliver integrated yet powerful access to data spread across multiple data stores. Governance is thus more agile and closer to the business than ever before. It complements the crucial quest for trustworthiness and unobstructed collaboration on data. The best of both worlds, really.


  • The increasing need to execute not just on internal data, but also with external partners, means that more data needs to be connected and collaborated on in a highly federative way.
  • Master data management and the cross-reference it supplies between systems is crucial to ensure that connections between data can be both navigated and managed.
  • A realistic, light-weight approach to this does not require an undisputed “golden record” though, just the minimum to enable people and systems to connect the dots: quality can sometimes wait, but collaboration cannot.
  • Next to MDM, meta-data management, business process management, increasingly powerful self-service exploration, data virtualization and AI all significantly help to thrive on federation.


  • A leader in healthcare and life science wanted to open up distributed data for self-service analytics. It created a data catalog that automatically inventoried every field of data from several data lakes so that business analysts could maximize their time to value.
  • With product information residing in multiple systems with different standards definitions across various regions, a global beauty products company spent way too much time finding and aligning data. Through the implementation of federated MDM, it reestablished its grip on mastering complexity while freeing up time to actually work on insights-driven product management and marketing.


  • Business advantage is built on insights from data: wherever it is kept, by whomever, in whatever way.
  • Getting the right information means knowing what can be obtained: for example what customer information lives in which lakes and other data stores and what product information is related to it.
  • Enabling owners and users of internal and external data lakes to collaborate, so to provide better business outcomes for all parties involved.
  • Creating quick results without lengthy, often unrealistic unification and standardization efforts


  • Master Data Management

– IBM InfoSphere Big Match for Hadoop, Informatica Intelligent Master Data Management, Talend Master Data Management, SAP Master Data Governance

  • Data Exploration

– Informatica Enterprise Data Lake, Cloudera Navigator, Apache Atlas, Waterline Data Catalog, Microsoft Data Catalog

  • Data Virtualization

– Datometry Hyper-Q, Tibco data virtualization, Informatica data virtualization, Denodo data virtualization