Posts Tagged ‘data governance’

Of all the governance trends, none is more foundational and critical to the success of the governance program – indeed the organization itself – than the need for accurate, consistent, and relevant models that communicate the meaning, use, and residency of the assets of the enterprise. Modeling not only addresses the integration and ingestion of […]

To achieve success, businesses must sell their products swiftly, seamlessly, and at the lowest possible cost. This begins with efficient product data management. Simplifying data management and minimizing IT involvement can shorten the time needed to bring a product to market, enabling faster sales. Empowering business teams to manage product information, rather than relying on […]

Democratization of Ownership and Stewardship The rise of big data, self-service, and more powerful and flexible end-user information visualization and preparation tools, consumer/ member/patient experience is impacting governance in a significant manner with regard to structure, decision rights, and accountabilities. End-users are gaining more control of these assets, including the ability to integrate and manipulate […]

Related to the trend of recognizing the difference between information and data, content, and knowledge is that governance of information requires it be viewed as a business capability. This recognition is starting to take hold because healthcare organizations are realizing that it is the business needs and drivers that supply the context for data, content, […]

Once upon a time, it was simple. The IT department took care of technology implementations and kept the trains (emails) running. Marketing had a distinct set of tools, operating within relatively clear parameters. Clinical applications operated in their own silos, and that was just fine. Operational and workflow systems had their own idiosyncrasies. Imperfect, but […]

The trend of treating information, content, and knowledge as assets means that ultimately these things need to be addressed and accounted for just like all other assets in a business. This means making it a part of the organization’s balance sheet – if not formally, as accounting principles do not yet support this capitalization concept […]

A Data Lake can be a highly valuable asset to any enterprise, and there is a myriad of technology solutions available for leveraging the processes to feed, maintain and retrieve information from the Lake. But all this technology is, if not worthless, significantly less valuable, if the environment is not well governed and managed. This […]

Data lineage is the capture of the flow of data from the source through intermediary systems and data transformations to a final destination or consumer. Having good data lineage provides a means to confirm that data used by consumers is from trusted, authoritative sources with adequate controls in place to govern the hand-offs between systems. […]

Establishing an authoritative sources capability confirms the enterprise approved source for data ownership, including both origination and distribution. Before a financial institution can agree on authorized sources of data, there must first be a common understanding of the type of data being sourced. Data will need to be classified in an agreed-upon enterprise data model. […]

The data architecture capability will supply the components and standards necessary to implement other capabilities coherently and enable them to work together. A primary responsibility of data architecture is to define and have an accepted enterprise-wide set of models, standards, glossaries and hierarchies which allow a standard description of data across business lines, products and […]

The data governance road map should define a data governance operating model and organization structure. As part of the structure, an executive steering committee should be established with representation from all key areas of the financial institution. The steering committee is responsible for providing overall direction and vision for the company’s data strategy and governance […]

In my last blog, you may recall that we were discussing the value and the need for Standards and Templates for ensuring a consistent and efficient use of the Data Lake, both in its population (supplying) and in its retrieval (consuming) of information. To achieve this level of consistency and efficiency, as well as reliability, […]