{"id":153,"date":"2006-12-05T09:31:57","date_gmt":"2006-12-05T17:31:57","guid":{"rendered":"http:\/\/www.formtek.com\/blog\/?p=153"},"modified":"2006-12-05T09:31:57","modified_gmt":"2006-12-05T17:31:57","slug":"poor-data-quality-can-undermine-business-intelligence","status":"publish","type":"post","link":"https:\/\/formtek.com\/blog\/poor-data-quality-can-undermine-business-intelligence\/","title":{"rendered":"Poor Data Quality can Undermine Business Intelligence"},"content":{"rendered":"

Keeping data up to date and fresh is a global problem.\u00a0 How many times have you searched the internet to find the\u00a0information in the top results to be out-dated?\u00a0 The same problem plagues\u00a0data managed in enterprises.<\/p>\n

A\u00a0Data Warehousing Institute’s study<\/a> estimated\u00a0that $600\u00a0billion are lost each year in US businesses due to poor data quality.\u00a0 The impact of poor data quality are many and include data reprocessing and loss of customers due to dissatisfaction.\u00a0 Data quality can adversely affect the performance and efficiency of operational systems by undermining business intelligence.\u00a0 Data is a strategic asset and if not properly treated can easily become outdated, inconsistent, orphaned or duplicated.<\/p>\n

Bad data can be the result\u00a0of problems related to data entry or from just becoming stale.\u00a0 Often data quality problems are\u00a0introduced when\u00a0systems are converted or integrated (such as during mergers and acquisition).<\/p>\n

Especially in\u00a0the area of regulatory compliance, poor data quality can be a very costly proposition.\u00a0 A new study<\/a> from AIM Software finds that data quality is the biggest problem for companies trying to comply with regulatory compliance initiatitives like Sarbanes-Oxley and Basel II.\u00a0 69% of companies are implementing risk management solutions for regulatory reasons.<\/p>\n

The AIM study of 1027 IT managers at financial services firms also found that 44% of companies are investing in “reference data management” systems over the next two years to improve data quality.<\/p>\n

Reference Data Management refers to management of data that resides in “master” tables.\u00a0 It boils down to their not being a consistent business language in communicating data.\u00a0 Multiple applications and sources of data, many coming from different domains, are frequently not coordinated well\u00a0among business, process and technology groups.\u00a0 There often is no single source of truth for reference data.<\/p>\n

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Keeping data up to date and fresh is a global problem.\u00a0 How many times have you searched the internet to find the\u00a0information in the top results to be out-dated?\u00a0 The same problem plagues\u00a0data managed in enterprises. A\u00a0Data Warehousing Institute’s study…<\/span><\/p>\n

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