data governance

Being able to understand how and which hub domains are defined within an organization can support the overall data governance process.

Operational data stewards are usually members of a data governance team in an enterprise responsible for information assets.

In my next blog, I'll write about a framework for data governance based on data policies and a set of processes around the policies.

First things first, get the following out: Your data governance maturity model template (filled in) and the in-scope data for your program.

I'll admit that I'm starting to see some value in this data governance stuff.

Data governance has many facets: availability, security, privacy, quality, audit, and retention to name a few.

Establish a core set of data governance directives that account for the special requirements of big data sets.

To provide a useful vehicle for Data Governance regarding responsibilities for information creation, update, deletion, distribution and use.

Data governance significantly reduces the cost of data management activities.

The staged data governance gives organizations greater control over the flow and life cycle of information.

Data governance, says Adler, is largely about systematically identifying and addressing error entry points.

The concepts behind data governance are changing business operations for organizations in healthcare and beyond.

Decisions regarding how rules are enforced and by which services are a key aspect of data governance.

Healthcare and insurance have been leaders in data governance, though not exactly by choice.

And as it turns out, the rise of data governance is also changing the roles and responsibilities of DBAs in important ways.

In five blog entries spanning five days, the Data Governance Blog provides a quick start guide for developing a Data Maturity Model.

The latest in a long line of squishy-sounding concepts to come my way is "data governance. "

The benefit of data governance in comparison to traditional approaches is better data at a lower cost.

To manage standardization , provide data governance and control for Material and vendor master data.

"Data governance is integral to better healthcare delivery and reducing costs, " says Brooks.

Finally, the canonical data model is a critical foundation for effective data governance.

DBAs work on data structures as usual and "apply good data governance principles as they do their jobs, " according to Brooks.

BCBST built a data governance application to balance and control updates to the data warehouse.

Communicate the data governance policy effectively.

Does the data governance policy you're developing support the decision-making model?

Steve Adler makes a good case in arguing the business value of data governance.

In the first of the five part series on Data Governance, the focus is on defining scope and establishing a baseline.

Issues related to data governance can be some of the most complex and important issues that a project has to address.

What has your data governance policy actually achieved?

BCBST dove into data governance before the term existed.

How do you get some traction with a data governance effort?

We might even have a non-snarky talk about data governance.

What in the world do you mean by 'data governance'?

Establishes the ability to generate operations to implement master data governance policies to manage and control the quality of master data

IBM has a portfolio of robust data governance offerings that span the facets mentioned above. Key portfolio goals here are