Solving Source Data Problems with Automated Data Profiling

Solving Source Data Problems with Automated Data Profiling
Data profiling process is the best way to accurately plan projects and eliminate the risks associated with data quality problems. It also reduces costs and increases productivity as much as 90% over manual methodsMany project managers and systems integrators have learned know the importance of understanding the data before starting an integration or migration project. The data profiling process is the best way to accurately plan projects and eliminate the risks associated with data quality problems. It also reduces costs and increases productivity as much as 90% over manual methods. Data profiling can automatically identify potential exceptions and anomalies, rather than leaving project managers with having to write scripts based on what they suspect the anomalies to be. Data profiling uncovers such things as missing and duplicate data, misspelled data, broken data rules, invalid data structures, incorrect content, and irreconcilable data. Find out how Ford Financial Europe used a data analysis solution to enable them to able to identify within a few days, data issues across multiple data sources, that would have taken 180 man days of effort to overcome. They were able to improve their monthly reporting, thus increasing support for the many decision making processes across the enterprise. Data profiling process is the best way to accurately plan projects and eliminate the risks associated with data quality problems. It also reduces costs and increases productivity as much as 90% over manual methodsMany project managers and systems integrators have learned know the importance of understanding the data before starting an integration or migration project. The data profiling process is the best way to accurately plan projects and eliminate the risks associated with data quality problems. It also reduces costs and increases productivity as much as 90% over manual methods. Data profiling can automatically identify potential exceptions and anomalies, rather than leaving project managers with having to write scripts based on what they suspect the anomalies to be. Data profiling uncovers such things as missing and duplicate data, misspelled data, broken data rules, invalid data structures, incorrect content, and irreconcilable data. Find out how Ford Financial Europe used a data analysis solution to enable them to able to identify within a few days, data issues across multiple data sources, that would have taken 180 man days of effort to overcome. They were able to improve their monthly reporting, thus increasing support for the many decision making processes across the enterprise. -->

Published on 03 November 2010

By Trillium Software
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