| The overall objective of data warehouses is to provide a repository of the organization’s information for use in developing analytic measurements and guiding planning and decision making. However, the data funneled into the data warehouse from various operational and analytical applications usually has widely divergent formats and standards, and is given only basic transformational mapping. In most cases, little attention is paid to the data's internal quality and integrity. As a result, the quality and reliability of the data in the data warehouse is questionable, at best. |
|
| What is the impact of using such data? The Data Warehousing Institute reports that data quality problems cost US businesses more than $600 billion a year in unnecessary operational and administrative expenses.* But potentially even more costly are the effects of using inaccurate and unreliable data as the foundation for strategic or mission-critical decision making. |
|
Innovative's automated data profiling and data integration solutions can enhance the quality, accuracy and usability of your Data Warehouse, to increase the value of data warehouse-based analytics and provide more reliable information for corporate decision making. Using our data profiling and data integration tools, you can:
|
|
• |
|
Drill down into the selected data segments to identify inconsistent formats, damaged data structures, missing information and other anomalies |
|
|
|
• |
|
Use the results of the data profiling to write transformation specifications that help ensure that all data segments will be successfully integrated the first time |
|
|
|
• |
|
Cleanse, standardize and link the data during the transformation process to maximize accuracy and eliminate duplication |
|
|
| To enhance the quality of the Data Warehouse as a whole, the same process of data profiling, writing mapping specs based on the profiling results, integrating the data, and then cleansing, standardizing and de-duping it can be applied to the data already in the warehouse and/or to new data as it is added. |
| |
* From the TDWI 2002 Report Series titled Data Quality and the Bottom Line:
Achieving Business Success through a Commitment to High Quality Data |
