Michael Daconta | Five steps to better data management

Reality Check--commentary

Michael Daconta

WE OFTEN BEGIN a new year by reflecting on the past and planning for the future, resolving to dedicate or rededicate ourselves to the disciplines of a healthier lifestyle. Similarly, organizations benefit from taking stock of their disciplines ' especially when it comes to the way they deal with data, information and knowledge management.

If money is an organization's lifeblood and people its muscles, data is the nervous system. What resolutions would discipline and strengthen an organization's nervous system? Let me suggest five practical resolutions.

1. Conduct a data privacy audit.

Given that identity theft and government data loss are of public concern, you should conduct an audit of the privacy vulnerability of your data assets. If you have a completed Federal Enterprise Architecture Data Reference Model, this is easy. It can be done by a simple query of the data attributes exposed by each information technology system against your privacy policy.

2. Develop and harmonize your business glossary.

If your agency doesn't have a business glossary, create one. When I was at the Homeland Security Department, Secretary Tom Ridge spearheaded an initiative to develop a DHS glossary so the department could effectively communicate across its organizational elements.

If you already have a business glossary, ensure it is harmonized across the enterprise so that terms mean the same thing across departments.

3. Enable data mashups and social applications for users.

A data mashup is a Web-based application that combines data from multiple sources into a single view to enable new insights. For example, combining real-estate data from Craigslist and maps from Google Maps was the inspiration for housingmaps.com. There are numerous other examples of mashups, such as the Environmental Protection Agency's Superfund locator and other agencies' use of crime data, weather data and social data. The Transportation Security Administration recently created a successful Web 2.0 application called the idea factory, which was modeled after Dell's IdeaStorm site (www.dellideastorm.com). Empowering users with these Web 2.0 technologies forces you to ask the right data questions: What data should we expose? Is our data ready to be exposed? Is our data trustworthy?

4. Install a data services layer in your service-oriented architecture plumbing.

As you begin to enable your organization for Web services ' or make it net-centric, for Defense Department readers' build your services from the data up. To do this is, create an access layer to your data that exposes each major data entity in your business glossary. For example, basic entities such as incident, case, vehicle or facility should be exposed with a standard set of create, read, update and delete services. You then build higher-level services on top of these foundational services.

5. Learn why rules rule.

This year, we will see the rise of rule-based applications that let users modify business rules and policies that control your applications. Rules standards ' from the Object Management Group and World Wide Consortium, for instance ' and tools such as JBoss (GCN.com/906) are coming into fruition to make these applications easy to build. Why do we care about rules in data management? For rules to work reliably, they require standard, formally defined data.

These resolutions, if followed, will put you on track to a data-healthy organization. A belated Happy New Year! Daconta (mdac[email protected] com) is former metadata program manager at the Homeland Security Department and the author of 'Information As Product: How to Deliver the Right Information to the Right Person at the Right Time.'

About the Author

Michael C. Daconta ([email protected]) is the Vice President of Advanced Technology at InCadence Strategic Solutions and the former Metadata Program Manager for the Homeland Security Department. His new book is entitled, The Great Cloud Migration: Your Roadmap to Cloud Computing, Big Data and Linked Data.


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