erwin
APRIL 16, 2021
Data governance is best defined as the strategic, ongoing and collaborative processes involved in managing data’s access, availability, usability, quality and security in line with established internal policies and relevant data regulations. Data Governance Is Business Transformation. Predictability.
Alation
JANUARY 19, 2023
The words “ data governance ” and “fun” are seldom spoken together. The term data governance conjures images of restrictions and control that result in an uphill challenge for most programs and organizations from the beginning. Or they are spending too much time preparing the data for proper use.
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erwin
MARCH 25, 2021
erwin recently hosted the second in its six-part webinar series on the practice of data governance and how to proactively deal with its complexities. As Mr. Pörschmann highlighted at the beginning of the series, data governance works best when it is strongly aligned with the drivers, motivations and goals of the business.
Alation
APRIL 25, 2023
That means if you haven’t already incorporated a plan for data governance into your long-term vision for your business, the time is now. Let’s take a closer look at what data governance is — and the top five mistakes to avoid when implementing it. 5 common data governance mistakes 1.
erwin
FEBRUARY 4, 2021
Better decision-making has now topped compliance as the primary driver of data governance. However, organizations still encounter a number of bottlenecks that may hold them back from fully realizing the value of their data in producing timely and relevant business insights. Data Governance Bottlenecks. Regulations.
Alation
DECEMBER 8, 2022
Data governance is growing in urgency and prominence. As regulations grow more complex (and compliance fines more onerous) organizations aren’t just adapting data governance frameworks to drive compliance – they’re leveraging governance to fuel a growing range of use cases, from collaboration to stewardship, discovery, and more.
Anmut
MARCH 22, 2023
This ultimately allows for more effective goal-setting, with targets determined according to both your data maturity right now and the desired stage you want to attain in the future. Why do we need data maturity models? A data maturity model helps your company measure its data and business health.
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