Although data silos are denounced as inherently bad since they complicate the coordination of enterprise-wide business activities, since they are often used to support some of those business activities, whether or not data silos are good or bad is a matter of perspective.
For example, data silos are bad when different business units are redundantly storing and maintaining their own private copies of the same data, but data silos are good when they are used to protect sensitive data that should not be shared.
Providing the organization with a single system of record, a single version of the truth, a single view, a golden copy, or a consolidated repository of trusted data has long been the anti-data-silo siren song of enterprise data warehousing (EDW), and more recently, of master data management (MDM). Although these initiatives can provide significant business value, somewhat ironically, many data silos start with EDW or MDM data that was replicated and customized in order to satisfy the particular needs of an operational project or tactical initiative. This customized data either becomes obsolesced after the conclusion of its project or initiative – or it continues to be used because it is satisfying a business need that EDW and MDM are not.
One of the early goals of a new data governance program should be to provide the organization with a substantially improved view of how it is using its data – including data silos – to support its operational, tactical and strategic business activities.
Data governance can help the organization catalog existing data sources, build a matrix of data usage and related business processes and technology, identify potential external reference sources to use for data enrichment, as well as help define the metrics that meaningfully measure data quality using business-relevant terminology.
The transparency provided by this combined analysis of the existing data, business, and technology landscape will provide a more comprehensive overview of enterprise data management problems, which will help the organization better evaluate any existing data and technology re-use and redundancies, as well as whether investing in new technology will be necessary.
Data governance can help topple data silos by first turning them into glass houses through transparency, empowering the organization to start throwing stones at those glass houses that must be eliminated. And when data silos are allowed to persist, they should remain glass houses, clearly illustrating whether or not they have the business-justified reasons for continued use.
This blog originally appeared at OCDQblog.com.