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Data Cleansing & Normalisation |
Data cleansing, also called data scrubbing, is the process of amending or removing data in a database that is incorrect, incomplete, improperly formatted, or duplicated. For organizations in a data-intensive field like banking, insurance, retailing, telecommunications or transportation, data quality is of paramount importance and without it organizations run the risk of making decisions based on incomplete information, or failing to comply with corporate governance regulations.
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Data quality is a critical factor for the success of enterprise intelligence initiatives. Bad data on one system can easily and rapidly propagate to other systems. If information shared across the organisation is contradictory, inconsistent or inaccurate, then interactions with customers, suppliers and others will be based on inaccurate information, resulting in higher costs, reduced credibility and lost business. |
SOFTUNIQUE provides a solution that seamlessly integrates data quality with the data cleansing process. With this process SOFTUNIQUE transforms and combines disparate data, remove inaccuracies, standardize on common values, parse values and cleanse dirty data to create consistent, reliable information. |
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SOFTUNIQUE takes care of the entire process for you and offer a data cleansing service, which will revive your database. Our data cleansing service covers several steps in our quality process, depending on the type of data and carries out data cleansing on catalog data irrespective of the format and can turn out the output either in XLS, Access, CSV, CUP, CIF, cXML, OEX, XML, BMECat etc., or in any other format that you, the customer, specify. |
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The Data/Content Quality Process |
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1. Classifying products and services supports procurement activities |
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Parse: Identify and isolate data elements in data structures. |
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Standardise: Normalise data values and formats according to your business rules. |
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Re-arranging the description: Input descriptions are re-arranged in the order of Noun, Modifiers basis. |
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Correct: Verify, scrub, and append data, based on a set of sophisticated algorithms that work with secondary data sources. |
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Enhance: Append additional data, thereby increasing the value of the information. |
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De-duplication: eliminate duplicate records which might be similar looking records |
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Clean and accurate product information and presentation: Since customers cannot actually see, touch and feel products in person, the presentation must be clear and visually accurate. |
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