Data Quality Services in SQL Server – A Primer

With the advent of social media, 2575_img5Smartphone and a hyper connected world, we are in throes of an information revolution. A company today tends to receive huge volume of data from which valuable actionable intelligence can be garnered. However even the best Business Intelligence tool will fail to deliver relevant results if the underlying data is vague or error prone. A lot of the data that enters into the SQL database may go unmapped if they do not conform to parameters necessary for BI application. For example something as simple as New York may get left out of queries if someone has entered the city field as NYC. However with the help of Data Quality Services (DQS) which have been introduced in MS SQL Server 2012, you get the chance to modify the data records for accurate identifications. Essentially with DQS you can ensure that your BI applications are able to correctly consider each underlying data element and present accurate scenarios.


Understand How DQS is implemented in SQL Server 2012

The basic premise of DQS involves creating a rule based knowledgebase that can be used to clean up data records. The SQL Server 2012 offers you three main sections under the DQS head. These include the Knowledgebase Management Screen to put in place the necessary rules and Administration Screen. For encompassing the cleaned data and collate them, the Data Quality Projects section is available. Using DQS you can specify specific rules for every field or implement correction procedures. For example you place a standing instruction that if NYC is notices, it would automatically be changed to New York. You can also quickly map the data to relevant columns using Projects feature. In fact you can even get specific end users to implement their custom validations on their respective projects. Once records are cleaned they can be exported into a spreadsheet or directly incorporated into the SQL Server. Now if you are looking to enrich the data to make the data more amenable for BI applications, you can take help third party providers that offer predefined data validation and cleansing procedures. By choosing to reference DQS with DataMarket you can drastically reduce the time and effort needed for setting elaborate clean up rules.


What if your SQL data files get corrupted

By using DQS you can structure data to facilitate better insights. However all such data records may be at risk in case of a SQL corruption. Now in case you wish to avoid such risks then it is advisable to keep a potent sql recovery tool like the DataNumen SQL repair at hand. This remarkable application is capable of dealing with data stored in myriad formats and can dig out contents from removable media too. Further its speed of recovery and effectiveness is unmatched in its class and it maintains the consistency of the data to the last detail. Its neat interface and intuitive options come rather handy when you are looking to recover multiple MDF files in one go.


Author Introduction:

Alan Chen is President & Chairman of DataNumen, Inc., which is the world leader in data recovery technologies, including access recovery and sql recovery software products. For more information visit

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