The Doppler Quarterly Winter 2016 | Page 26

Your Guide to Data Governance David Linthicum As companies increasingly turn to data to influence their decisions, it is critical that data owners under- stand the rapidly evolving needs of risk management for data that crosses applications, on-premise facili- ties and clouds. Successful data governance can be achieved with applications that span private on-premise environ- ments and public cloud resources, but governance must be a fundamental part of the design and imple- mentation, not an after thought. Key Components of a Complete Data Governance Strategy Value Know what value the data holds in terms of cost if lost, cost of generation and value derived through analysis. These metrics will be used to determine safeguards for protecting the data and relative costs for storing the data on different platforms. Location Know both where the data is created and where it is stored. This information leads to what safeguards are needed to protect the data at rest as well as in transit. This metric also helps determine the best methods for moving data between sites for analysis, transfor- mation, and integration. Risk Knowing what risk the data poses to your organization is key to ensuring it is appropriately protected. High- risk data includes social security numbers, addresses, and credit card information, all of which require alert- ing customers if they are lost or compromised. Decision Makers Every organization has varying levels of individuals that are accessing data in different ways. A solid data gover- nance strategy will include an inventory of these deci- sions makers; including what data they require access to, on what time frames and with what tools. This enables the organization to properly plan how to enable these users, while managing the associated risk. Accuracy Data, and the decisions derived from it present them- selves in many ways, including completeness, non-ob- solescence, precision and repeatability. It is critical that all data sets have an associated set of policies about the quality of the data that drives the organiza- tion to properly clean incoming data, and properly gauge the accuracy of results derived from that data. Best Practices in a Cloud-First World Keep security context with the data as it moves between systems By keeping security context with a data set, it ensures 24 | THE DOPPLER | WINTER 2016