Services > Enable > Data Management

Take your data governance and give it wheels.

With a data management program, you can graduate from setting data expectations to making your data conform to those expectations.

The life of your data is eventful. From the point of capture to all the points of use, your data is parsed, routed, merged, stored, and read by a variety of systems, processes, and people. Much of this movement and manipulation is automatic, driven by data integration, MDM, and data quality applications you've worked hard to build. But these applications frequently differ across departments. And data movement and manipulation is just as frequently manual—users and groups copy and create data for individual purposes all the time.

So who’s minding the store?

If the answer is your data governance program, that’s good. But does it have the cross-functional support it needs to turn standards into consistent daily action on an enterprise level? Data management can provide this support, taking your data governance from policy to practice.

Data management coordinates all the diverse data processes in your organization. It promotes the uniform treatment of data in your development and operational environments; in your solution and information architectures; in your transactional and analytical processes and technologies; and in your organizational structures and communications. It defines how data will be accessed, used, shared, and stored. Ultimately, its goal is to help your organization sustain and grow data as an asset, and use this data to achieve business objectives.

We know how overwhelming that can sound--it's why a lot of organizations have put off tackling data management. But they're missing out.

One of the tenets Clarity holds most dear is that business intelligence should be more straightforward to build and use. It should make users' lives easier, not harder. We apply that approach to data management, too:

• It doesn't have to be another set of rules, regulations, or resources--it can be deployed via your data governance organization or Center of Excellence, both of which help garner support and manage change for enterprise activities.
• It doesn't have to be another layer of architecture--it works best when it simplifies and rationalizes already in-place architectures.
• It doesn't have to be another technology selection effort--it actually offers a clear benefit of technical efficiencies through shared services.
• It doesn't have to be implemented enterprise wide--it can start delivering benefits when you link just two data-centric processes, like data integration and data quality, in one business unit.

For all these reasons, any politically-minded objectives to data management are easier to overcome. And with all its direct benefits to BI, why not get started today? Contact us for more information.