Data governance is a principled approach to managing data during its life cycle, from acquisition to use to disposal.
Every organization needs data governance. As businesses throughout all industries proceed on their digital-transformation journeys, data has quickly become the most valuable asset they possess.
Senior managers need accurate and timely data to make strategic business decisions. Marketing and sales professionals need trustworthy data to understand what customers want. Procurement and supply-chain-management personnel need accurate data to keep inventories stocked and to minimize manufacturing costs. Compliance officers need to prove that data is being handled according to both internal and external mandates. And so on.
Data governance is everything you do to ensure data is secure, private, accurate, available, and usable. It includes the actions people must take, the processes they must follow, and the technology that supports them throughout the data life cycle.
Data governance means setting internal standards—data policies—that apply to how data is gathered, stored, processed, and disposed of. It governs who can access what kinds of data and what kinds of data are under governance. Data governance also involves complying with external standards set by industry associations, government agencies, and other stakeholders.
Users throughout your organization get the data they need to reach and service customers, design and improve products and services, and seize opportunities for new revenues.
Data helps you manage resources more effectively. Because you can eliminate data duplication caused by information silos, you don’t overbuy—and have to maintain—expensive hardware.
An increasingly complex regulatory climate has made it even more important for organizations to establish robust data governance practices. You avoid risks associated with noncompliance while proactively anticipating new regulations.
By being in auditable compliance with both internal and external data policies, you gain the trust of customers and partners that you will protect their sensitive information, so they feel positive about doing business with you.
With strong governance, you can allay concerns about exposure of sensitive data to individuals or systems who lack proper authorization, security breaches from malicious outsiders, or even insiders accessing data they don’t have the right to see.
Strong data governance allows more personnel access to more data, with the confidence that these personnel get access to the right data and that this democratization of data does not negatively impact the organization.
As cloud adoption accelerates, questions inevitably arise about how it impacts data governance. Enterprises have concerns that:
Data governance often means giving accountability and responsibility for both the data itself and the processes that ensure its proper use to “data stewards.”
Data governance is also used to ensure data quality, which refers to any activities or techniques designed to make sure data is suitable to be used. Data quality is generally judged on six dimensions: accuracy, completeness, consistency, timeliness, validity, and uniqueness.
This is a broad concept encompassing all aspects of managing data as an enterprise asset, from collection and storage to usage and oversight, making sure it’s being leveraged securely, efficiently, and cost-effectively before it’s disposed of.
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