Data quality implementation is important in the context of Data Warehouse and Business Intelligence. This blog focuses on why this is important and how it can be implemented.
Importance of integrating quality data to Enterprise Data Warehouse
A Data Warehouse is an integral part of those enterprises which want to have clear business insights from customer and operational data. It has been observed that fundamental problems arise in populating a warehouse with quality data from various multiple sources systems. Let us see in greater detail.
1. Impact of Erroneous data being integrated to DW
Many organizations grapple with poor data quality which ultimately results in poor decision-making. After all, decisions are no better than the data on which they are based. Reliable, relevant, and complete data supports organizational efficiency and is a cornerstone of sound decision-making Poor quality data could be an obvious reason for the malfunctioning and operational inefficiency of an organization. The negative implications of poor data can be felt in terms of decreased customer satisfaction and trust, high running costs, poor business decision and performance