Research shows that dirty data is a problem for most UK business organisations and enterprises causing a major loss of worker productivity and business productivity.
October 18, 2006 (Press Release) --
Oxford, UK - Grid-Tools Limited, a leading vendor of test data management and information lifecycle management software announces its solution to the impact of dirty data on UK business productivity. It is estimated that 61 per cent of British workers spend an average of 7 hours a week verifying the accuracy and quality of data they use to make decisions. Grid-Tools software offers a solution to a problem that causes major losses of productivity for UK businesses.
For more information, please visit: www.grid-tools.com or call 0871 309 8293.
Business intelligence relies on good quality data
Achieving the full benefits of business intelligence is dependent upon having good quality data. Research has consistently shown that ‘dirty data’ is a problem in many organisations. Recent research by Business Objects found that 62 per cent of British respondents admitted that business decisions had been based on flawed data. In addition, 61 per cent of British workers spend an average of 7 hours a week verifying data quality and data accuracy, causing a major loss of productivity.
The growth of ‘dirty data’
Poor quality data arises for many reasons, including errors and deficiencies in the following: existence, consistency, integrity, validity, timeliness, accuracy, completeness and relevance. The processes that lead to the creation of dirty data are largely the result of errors made by staff that input data or are dealing with it. Those people that generate the dirty data rarely see the impact of the problems. Often errors arise during the receipt, input, duplication, categorisation, interpretation and translation of data. Inaccurate data can waste time reconciling discrepancies, and can result in poor decisions that upset businesses processes and even customers.
Organisations must admit that they have a data problem
Large organisations may incur more costs due to poor-quality data than any benefits they derive from implementing customer relationship management, enterprise resource planning or Business Intelligence applications. Data must also be kept up to date, to ensure data quality if an investment in Business Intelligence is to be realised, but getting them to admit there is a ‘dirty data’ problem is the hardest challenge. “It is difficult to get organisations to admit to having data problems,” says Huw Price, managing director of Grid-Tools, a database management company. “Most people react to problems, rather than systematically implementing a data quality regime.” The Grid-Tools suite of products is designed to address these issues and helps enterprises generate and maintain ‘clean data’ to enhance productivity.
About Grid-Tools Limited
Grid-Tools’ software enables organisations with databases to achieve legal compliance, to increase the productivity of its IT staff and to improve the price/performance of its infrastructure. Grid-Tools’ solutions apply to test data management and information lifecycle management. The core product automates
For more information, please visit: www.grid-tools.com or call 0871 309 8293.
Business intelligence relies on good quality data
Achieving the full benefits of business intelligence is dependent upon having good quality data. Research has consistently shown that ‘dirty data’ is a problem in many organisations. Recent research by Business Objects found that 62 per cent of British respondents admitted that business decisions had been based on flawed data. In addition, 61 per cent of British workers spend an average of 7 hours a week verifying data quality and data accuracy, causing a major loss of productivity.
The growth of ‘dirty data’
Poor quality data arises for many reasons, including errors and deficiencies in the following: existence, consistency, integrity, validity, timeliness, accuracy, completeness and relevance. The processes that lead to the creation of dirty data are largely the result of errors made by staff that input data or are dealing with it. Those people that generate the dirty data rarely see the impact of the problems. Often errors arise during the receipt, input, duplication, categorisation, interpretation and translation of data. Inaccurate data can waste time reconciling discrepancies, and can result in poor decisions that upset businesses processes and even customers.
Organisations must admit that they have a data problem
Large organisations may incur more costs due to poor-quality data than any benefits they derive from implementing customer relationship management, enterprise resource planning or Business Intelligence applications. Data must also be kept up to date, to ensure data quality if an investment in Business Intelligence is to be realised, but getting them to admit there is a ‘dirty data’ problem is the hardest challenge. “It is difficult to get organisations to admit to having data problems,” says Huw Price, managing director of Grid-Tools, a database management company. “Most people react to problems, rather than systematically implementing a data quality regime.” The Grid-Tools suite of products is designed to address these issues and helps enterprises generate and maintain ‘clean data’ to enhance productivity.
About Grid-Tools Limited
Grid-Tools’ software enables organisations with databases to achieve legal compliance, to increase the productivity of its IT staff and to improve the price/performance of its infrastructure. Grid-Tools’ solutions apply to test data management and information lifecycle management. The core product automates
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