Importance of integrating quality data to Enterprise Data Warehouse
A Data Warehouse is an integral part of those enterprises which want to have a 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
2. Cost of Integrating poor quality Data to DW
Any kind of anomalies and impurities in data such as data incompleteness, incorrectness, Integrity violation etc. could avert its effective utilization, disabling high performance, hamper accurate processing of the results etc. Conclusions gained by data analysis could lead to faulty decisions once the data warehouse is polluted with bad data.
Let us see few facts given below
75% of all the data integration projects has been reported to have either over-run their budgets or have met a complete failure
70% organizations have identified costs stemming from dirty data
33% of organizations have delayed or canceled new IT systems because of poor data
Business intelligence (BI) projects often fail due to dirty data, so it is imperative that BI-based business decisions are based on clean data