Enterprise Data Warehouse Governance Best Practices

Abstract

Maintaining a stable data warehouse becomes quite a challenge if discipline is not applied to code development, code changes, code performance, system resource usage and configuration of integration specification. As the size of the data warehouse increases the value it brings to an organization tends to increase. However these benefits come at a cost of maintaining the applications and running the data warehouse efficiently on a twenty four hours a day and seven days a week basis. Governance is all about bringing discipline and control in the form of guidelines for application developers and IT integration engineers to follow, with a goal that the behavior of a data warehouse application becomes predictable and manageable. In this article the authors have defined and explained a set of data warehouse governance best practices based on their real-world experience and insights drawn from industry and academic papers. Data warehouse governance can also support the development life cycle, maintenance, data architecture, data quality assurance, the Sarbanes-Oxley (SOX) Act requirements and enforce business requirements.

From Classical to Fuzzy Databases in a Production Enterprise

“…Data warehouses have a potential to deliver Business Intelligence solutions for companies seeking to gain competitive advantage. The development of data warehouses, their implementation, measurements, data quality monitoring and performance monitoring are critical for the implementation and maintenance of a data warehouse In another approach, authors suggest the structure of an information system that ensures operation and usability of a single data warehouse [Porshnev et al 2018]. The aim was to see data warehouse processes as a single unified system integrating all the processes, so they would seem to be one.…”

An Agent Approach to Manage Heterogeneous and Distributed Knowledge

“…)to workcollaborativelytodesign,developandindustrializethisproduct.Intheseprojectsenvironment, Knowledge is heterogeneous, since it comes from different sources. Rahman in (Rahman 2016) highlightstheimportancetodevelopthebestpracticetomanagedata,informationandknowledge. Knowledgeisalsodistributedthroughouttheenterprisenetworksinceeachprofessionalactoruses hisownsoftwaretoolconnectedtotheentirecorporatenetwork.…”