Leveraging Business Metadata for Trusted Information in Data Warehousing and Business Analytics
The need for making quality decisions rapidly is powering the broader integration of business intelligence and algorithmic analytics into operational business processes across the enterprise, up and down the management chain. Yet the entire decision-making process can grind to a screeching halt when information consumers question the meaning of the data presented to them. This lack of information visibility and utility can impact a number of dimensions of value, from revenue-generation, to risk management, or productivity and cost management.
In this interactive discussion, we will examine some of the root issues affecting enterprise information utility and level of trust that can reduce an organization’s ability to rapidly make good decisions. We will consider how varying semantics can lead to confusion, especially in assessing the impacts of changes in policies or data definitions. Yet clarity in data lineage can improve enterprise-wide data quality, reduce application development and maintenance efforts, and ensure the delivery of trusted information to the consumers of data warehouses and business analytics to the point where someone can look at a report, understand its true semantics, and really know the sources of that information. Our discussion will also include some real-world examples.
In this Webinar, you will learn:
- Ensuring that consistency between the presentation of actionable knowledge and its real meaning
- Understanding the connections between business terms, business definitions, and data element concepts
- The value of systemic data lineage and visibility
- Using semantic metadata to operationalize data lineage to benefit impact assessment, data trustworthiness, and dependable decision-making