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Every organization has standards and best practices for data quality. Now, you can build and enforce corporate standards - in batch or real-time - through an innovative customization interface.
Standardized information, such as uniform abbreviations, correct spelling and formatted patterns must meet data quality requirements if they are to provide a true picture of your organization and its business initiatives. DataFlux automates tedious data standardization processes to help you build more consistent data.
DataFlux technology provides an array of out-of-the-box standardization rules — or you can customize rules to meet the specific requirements of your data. With this technology in place, you can standardize data that typically has a number of permutations, including company names (DataFlux, DataFlux Corp, DataFlux Corporation) and product or item data (10W30, 10w30 Motor Oil, 10/30).
Creating rules to enforce standards
DataFlux solutions help you transform inconsistent data into one common product representation. In the example shown, inventory levels for a product named specifically "KS63C" appear to be 19 units. A user reviewing the raw data could identify that the inventory levels for this product might be 149 units by including other data points that have similar codes. Without a data quality solution, however, any computer-generated report that asks for products with the code “KS63C" might yield only 19 results.
DataFlux solutions help you transform inconsistent data into one common product representation. In this example, a standardization scheme, utilizing data conversion, converts each instance of similar data into a consistent naming pattern: “KS36C Walk-Behind Mower." This allows your reporting and data mining software to show the true picture — and will generate a report showing the appropriate inventory levels of 149 units.