Data Governance was a hot topic at this year’s Enterprise Data World held in Atlanta. With Big Data driving a massive growth in the amount of stored information, it behooves organizations to develop and implement policies for the control of this data.
EDW 2012 featured a host of sessions covering the principles of Data Governance; the conference had some sessions suitable for an introduction to the concepts of DG, while more advanced topics were covered at the tutorials and seminars. No matter one’s prior level of exposure to Data Governance, Enterprise Data World provided enough information to enhance that knowledge.
A number of companies offering Data Governance products or services maintained a booth presence at this year’s EDW Exhibit hall. These were highlighted by conference Platinum Sponsor, Adaptive.
Adaptive Focusing on Data Governance
Jojy Mathew is a Global Practice Leader for IT services company, Capgemini. The main speaker for an EDW session hosted by Adaptive, Mathew provided an excellent, project-based overview covering the best practices for implementing Data Governance suitable for many organizations.
Pete Rivett, CTO for Adaptive, introduced Mathew’s talk which focused less on vendor-specific solutions and more on the operationalizing of business metadata and data quality, in addition to Data Governance. “Operationalizing” in essence means an enterprise making that practice a core component of how they do business.
In most cases, an organization’s move towards a Data Governance program is driven by regulatory requirements. Mathew stressed that DG is “a program, not a project; it’s a must have competency.” The ultimate deliverable of this program is a common information model for both business and technology that includes business models, technology models, and control models.
The integration of metadata for both the business and IT sides of the shop remains vital, as is the development of frameworks and methodologies to support Data Quality in addition to Data Governance and Stewardship. All told, this Adaptive-sponsored session succeeded by its focus on the practical steps an organization needs to take when implementing a Data Governance practice.
As Enterprise Data World 2012’s Platinum Sponsor, Adaptive’s exhibit hall presence stood out, featuring their suite of products tuned for managing an enterprise’s Data Governance initiatives. Enterprise Architecture Manager, IT Portfolio Manager, and Metadata Manager combine with an effective governance strategy, helping any organization to stay ahead of the rapidly changing compliance requirements and also improving IT efficiencies.
EDW 2012 Data Governance Track Session Highlights
The Data Governance session track at this year’s Enterprise Data World featured talks useful for professionals at all levels of DG familiarity. The track was co-sponsored by Adaptive as well as the Data Governance Professionals Organization.
Data is the Foundation
Microsoft’s Kira Chuchom presented a notable session covering steps to overcome barriers and resistance to change when implementing a Data Governance program. The most important key consideration for a DG project is the fact that “Data is the Foundation.”
Through successive layers of analysis, this foundational data eventually transforms into information, knowledge, and insight, ultimately providing an enterprise with the strategic and predictive intelligence to transform and grow their business.
Competing for shared resources during a DG project is a potential barrier; therefore cultivating relationships between a variety of project sponsors and implementers is another key consideration eventually tying to an organization’s overall cultural maturity.
Chuchom drove home the importance of building a community of trust within an organization centered on education, communication, and collaboration. These remain principles important to a Data Governance program as well as any other project involving multiple departments within a large enterprise.
Identifying Business Value Metrics Using Data Governance
A key in getting executive buy-in for continued DG-related expenditures is being able to show tangible improvement in business value because of Data Governance. Sallie Mae’s Michele Koch covered the importance of metrics as part of this process.
Koch’s presentation detailed some of Sallie Mae’s successes in Enterprise Data Definition metrics, reducing the number of in-process data entities and attributes due to their DG program. In addition to increased value more pleasing to a DB administrator, Sallie Mae also showed a tangible financial savings, primarily due to reduced expenses.
Sallie Mae leveraged the Governance Maturity Model, mostly derived from the Data Governance Institute, as the prime indicator for their overall governance level. They also developed a set of metric categories for their DG program, including Data Standardization and Data Quality. As part of this process, metrics for tracking business value were also created.
Ultimately, the metric development process involves a detailed approach combining multiple series’ of interviews with internal line-of-business “owners” to determine criteria and calculations for business value. A Data Quality dashboard provides an easy-to-use system for reporting on the success of a Data Governance program, allowing the interested user to drill down into a more granular level of detail.
Leveraging Agile Methodologies and Data Governance
As the Agile project methodology continues to be more widely used in IT, it makes sense that some of its principles apply in Data Governance. Phasic Systems’ Geoff Malafsky, in addition to Phasic’s EDW exhibit hall presence, hosted a session showing how Agile can be useful in dealing with terminology mismatches on a DG implementation.
Agile provides the flexibility to quickly handle constantly changing business requirements compared to traditional waterfall methodologies. For DG projects, Phasic’s Agile Data system, working with existing data and applications, facilitates the successful alignment of governance and standards to the actual data and integration, providing a final solution in the fraction of the time and cost.
Phasic Systems offers their DataStar suite of applications as a solution to handle an organization’s Data Governance needs. DataStar Discovery brings an Agile approach to a management system for supporting DG standards and methodology. DataStar Unifier connects data warehousing with the models, etc. used by an enterprise’s DG staff. DataStar Adapter provides mapping functionality from source data to XML schema, and also features transactional conversion of the data. Finally, Phasic’s Corporate NoSQL combines traditional data modeling with features and terminology from the modern NoSQL movement.
DAMA’s DMBOK and Data Governance
The Data Management Association’s (DAMA) Data Management Book of Knowledge (DMBOK) is laden with guidelines for organizing and implementing a Data Governance practice suitable for any enterprise. Anne Marie Smith of Alabama Yankee Systems, LLC presented an EDW 2012 session covering how to leverage the DMBOK for Data Governance.
In the DMBOK, Data Governance is central to an entire collection of data management functions. These functions run the gamut from data operations and development to a whole host of different management disciplines, including Metadata, Reference and Master Data, as well as Data Architecture, among others.
Smith’s presentation touched on a common theme across many of the other Data Governance sessions at EDW 2012 — the importance of cross-enterprise planning and communication when implementing a governance program at an organization. It is important to accurately define the organizational scope for the program, as well as making sure that the business side of the shop becomes familiar with the nomenclature around data management.
There is little doubt that any data professional looking at a career in Data Governance needs to peruse the DMBOK for a clear and useful explanation of governance’s role in the overall data management picture, as well as ideas to use when setting up a new DG practice.
Data Governance and Data Stewardship
David Plotkin’s Monday morning EDW 2012 tutorial provided an excellent introduction to the principles of Data Governance. Combining practical real-world experience with material from the Data Governance Institute, the tutorial also hinted at the importance of Data Stewardship as a key part of any DG program.
That same afternoon, Plotkin gave a focused tutorial on Data Stewardship, subtitled “Doing it for Real.” Plotkin feels an operational Data Governance practice essentially gives a mandate for Data Stewardship, since the latter is the operational aspect of DG. In other words, if Governance is the execution of authority over the management of data, then Stewardship is the formalized accountability for said data management.
The tutorial covered the three basic types of Data Stewards. Business Data Stewards and Technical Data Stewards hold general responsibility for their “sides of the data shop” so to speak, while Project Data Stewards hold more of a day-to-day role of gathering data definitions, data quality rules, as well as project issues, and then passing the needed information to the Business and Technical Data Stewards.
Plotkin feels that Data Stewardship itself is not a job. Rather, it is the “formalizing of data responsibilities that are likely in place in an informal way.” Conversely, the role sometimes requires tasks that warrant training of the steward. Accountability for things like data definitions, data quality, downstream uses of the data, etc. tend to be requirements for most stewards.
Most importantly, stewards must support a strong communications role since a quality Data Governance practice depends greatly on internal business communication and the embedding of governance policies within the processes and workflows of any organization. In short, without Data Stewards, implementing any Data Governance program becomes needlessly difficult. A fully-formed Data Stewardship organization is a key part of any Governance practice.
Enterprise Data World 2012 provided a window into the growing importance of Data Governance for data professionals and the industry as a whole. The sessions and tutorials featured real-world examples of DG in action, while the exhibit hall allowed companies a platform for marketing their solutions supporting Data Governance implementation.
