Consolidating data using datamarts

Posted by / 29-Oct-2019 06:35

Consolidating data using datamarts

Traditional data warehouse solutions were not designed to handle the rapid growth in data and varying data types.They also were not designed to keep pace with the changing needs of end users and the applications that rely on them.Kimball’s approach is known as a bottom-up approach.

For example, an insurance company clearly needs a high-level overview from the outset, incorporating all factors that affect its business model and strategic choices, including demographics, stock market trends, claim histories, statistical probabilities, etc., so taking the Inmon approach and starting with a Data Warehouse makes most sense here.Data Warehouses/Marts often use a denormalized data structure, wherein the administrators take steps to improve query performance by adding back redundant data to normalized data to decrease analytic query running times.An important concept is extract, transform, and load (ETL).Data Mart Defined A Data Mart is a subject-oriented data repository that serves a specific line of business, such as finance or sales.The following are some important distinguishing features of a Data Mart: Data Warehouse Defined A Data Warehouse is an enterprise-wide repository of integrated data from disparate business sources, systems, and departments.

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Ralph Kimball argues that the best approach is to begin with the most important business aspects or departments, from which Data Marts oriented to specific lines of business emerge.