A complete understanding of all the issues, risks and opportunities that you are facing. This will allow you to work more effectively with the parts of your organization that drive the data governance policies.
In many companies, the responsibility for data governance splits across multiple departments. As an example: Defining PII – legal; securing PII – IT and regulatory compliance of PII – compliance. However, the accountability for data governance rests with the product manager or business unit owner who must understand the subject matter data to be able to effectively orchestrate the efforts of the different stakeholders to ensure the company’s data monetization products respect personal privacy, are secure against forced or accidental breach and are in compliance with all applicable regulations.
Data Lifecycle Management (DLM) – a policy-based approach to managing the flow of an information system’s data throughout its life cycle: from creation and initial storage to the time when it becomes obsolete and is deleted.
Information Lifecycle Management (ILM) – a comprehensive approach to managing the flow of an information system’s data and associated metadata from creation and initial storage to the time when it becomes obsolete and is deleted. Unlike earlier approaches to data storage management, ILM involves all aspects of dealing with data, starting with user practices, rather than just automating storage procedures, as for example, hierarchical storage management (HSM) does.
Data Governance – a holistic approach to managing corporate information by implementing processes, roles, controls and metrics that treat information as a valuable business asset. The goal of a holistic approach to information governance is to make information assets available to those who need it, while streamlining management, reducing storage costs and ensuring compliance.
Data Mapping – a process used in data warehousing by which different data models are linked to each other using a defined set of methods to characterize the data in a specific definition
Master Data Management (MDM) – a comprehensive method of enabling an enterprise to link all of its critical data to one file, called a master file, that provides a common point of reference. When properly done, MDM streamlines data sharing among personnel and departments.
Data Mining – a process in which large amounts of data are sifted through to show trends, relationships, and patterns. Data mining is a crucial component to data management because it exposes interesting information about the data being collected.