Big Data Should Mean Big Quality
September 2, 2014
Why does logic seem to fail in the face of fancy jargon? DataFusion’s Blog posted on the jargon fallacy in the post, “It All Begins With Data Quality.” The post explains how with new terms like big data, real-time analytics, and self-service business intelligence that the basic fundamentals that make this technology work are forgotten. Cleansing, data capture, and governance form the foundation for data quality. Without data quality, big data software is useless. According to a recent Aberdeen Group study, data quality was ranked as the most important data management function.
Data quality also leads to other benefits:
“When examining organizations that have invested in improving their data, Aberdeen’s research shows that data quality tools do in fact deliver quantifiable improvements. There is also an additional benefit: employees spend far less time searching for data and fixing errors. Data quality solutions provided an average improvement of 15% more records that were complete and 20% more records that were accurate and reliable. Furthermore, organizations without data quality tools reported twice the number of significant errors within their records; 22% of their records had these errors.”
Data quality saves man hours, discovers missing errors, and deleted duplicate records. The Aberdeen Group’s study also revealed that poor data quality is a top concern. Organizations should deploy a data quality tool, so they too can take advantage of its many benefits. It is a logical choice.
Whitney Grace, September 02, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
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