Data governance is the foundational component of the enterprise data management function. It is responsible for the development and implementation of policies and standards for managing data and information across and within the organization. Introduction Data governance is the planning, oversight, and control over management of data and the use of data and data-related resources, and the development and implementation
Every organization must perform project management according to the accepted principles and using the approved processes and procedures to enable successful results. Introduction Every day, organizations are asked to accomplish activities that do not align into the “business as usual” format. The Project Management Institute (PMI) defines a project as “a temporary endeavor undertaken to create a unique product or
An enterprise data strategy should be part of every organization’s strategic development. A data strategy ensures the organization uses its data and information to support business goals. Introduction Most organizations have a business strategy: a plan of how the company will achieve its goals, meet the expectations of its customers, and sustain a competitive advantage in the marketplace. Once defined,
Data quality is a function of data’s fitness for use to a particular purpose in a given context; measured against stated requirements or guidelines. High data quality engenders trust in operational and strategic decisions. Introduction Data quality is a perception or an assessment of data’s fitness to serve its purpose in a given context (Thomas C. Redman, 2008). It is
The DAMA-DMBOK© is the premier reference guide for all aspects of the data management profession, covering all components of data management with best practices and expert advice. Introduction Every profession has its “body of knowledge,” a collection of best practices and proven techniques for performing the functions of the discipline. Project Management has the PMBOK (Project Management Body of Knowledge);
Measuring the maturity of an organization’s data management capabilities against a standard model provides structure and the ability to gauge progress over time Introduction Organizations do not know how to treat data as an asset. As evidenced by the fact that many organizations do not or cannot control the data they capture and store for it to produce business value,
Data stewardship is the role practiced by business staff that implements the policies and standards developed by data governance professionals. Data stewards ensure the quailty of data for use. Introduction Data stewardship is the management and oversight of an organization’s data assets according to established data governance practices. Selected business users ensure that the organization has high-quality data that is
Enteprise data modeling is an essential component of strong enterprise data architecture, with subject, conceptual and enterprise logical models based on business concepts and requirements Introduction In many organizations, there is no way to understand the scope and variety of the data captured, stored and used by the applications and business activities that need information. An enterprise data model is
The Semantic data web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries Introduction Interest in the Semantic Web has skyrocketed, along with interest in the implications of semantic technologies on traditional data management. The promises of the Semantic Web – for example, being able to find information regardless of the
ISO 8000 defines the parameters of data quality, so one can ask for quality data and verify that one has received quality data Introduction It is common to see the relationship between data and information represented as a pyramid with data as the base rising through information and knowledge to wisdom as the apex. In researching the origin of this
