Data Management

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Marc J. Firenze
Marc J. Firenze
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Building a Successful Data Governance Framework

Business leaders and technologists must work together to build a data governance framework that is flexible, well managed, and built for long-term success.

Data governance seems to be an issue with which many firms in all sectors are locked in a perpetual struggle. Even when C-level executives pay close attention to how their data is managed, the struggle continues. Despite a swath of regulation addressing the handling and privacy of data over the last couple of decades, the task of building a data governance framework is still frequently underestimated and misunderstood.

There are three common misconceptions we often see when it comes to data governance frameworks that can significantly hamper a successful implementation. First, many think it’s a fairly straightforward and simple thing to implement (wrong). Second, many leaders feel that it’s a largely technical initiative that relies on building validations into data flows in order to trap errors (wrong). And finally, some feel that it’s a project that runs for a finite amount of time with a definite end date (wrong again).

A successful data governance framework implementation should be founded on the following guiding principles:

1. Information is an asset and should be viewed and managed as a valued resource. It is tempting to approach data governance by simply focusing on connecting the pipes, especially when budgets are tight and resources are spread thin. However, good data is an asset and needs to be recognized as such by the business. In order for data to be leveraged appropriately, businesses need to own the data, manage the process by which it is sourced, and institute an organization-wide data governance vision.

2. Quality is achieved by applying management processes, methods, tools, and best-practices. Data governance frameworks require organizational change, which is something that organizations can be resistant to -- both at a personnel level and in terms of infrastructure. Getting buy-in and recognition from senior executives that the current business practices need to change is critical to the success of an implementation. IT infrastructure may also be resistant to change. An organization might want good data governance but also needs to recognize it may require a change in IT.

3. Data governance (business) and stewardship (IT) are a shared responsibility. Business needs to be an equal partner with the technology to be successful. Data governance is not a purely technical initiative. Good data governance is a strategy shared among the managers of the business and the stewards of the IT. Once again, senior business sponsorship and a clear articulation of the challenges and the ultimate benefits of the process are crucial.

4. Data governance is a business discipline, not a project. Success is achieved when the people, process, and technology are all malleable. Business requirements change over time, meaning that the use of data also changes, often for purposes beyond the scope of existing expectations. A successful implementation therefore needs an inbuilt process to ensure it is sustainable and flexible in order to incorporate the inevitable change factor that will come.

A solid data governance framework formalizes accountability for data management across the organization and ensures that the appropriate people are involved in the process. By providing a clearer picture of the data environment it becomes easier to assess the impact of changes and fosters the philosophy that with owning data comes greater accountability and control over this important asset. 

As Chief Technology Officer of Eagle Investment Systems , Marc Firenze drives the software, technology, and architecture decisions across Eagle's investment management suite and ensures that development directly supports the firm's corporate vision. With more than 20 ... View Full Bio
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