SQL SERVER – Why Do We Need Data Quality Services – Importance and Significance of Data Quality Services (DQS)

SQL SERVER - Why Do We Need Data Quality Services - Importance and Significance of Data Quality Services (DQS) dqs-brush Databases are awesome.  I’m sure my readers know my opinion about this – I have made SQL Server my life’s work after all!  I love technology and all things computer-related.  Of course, even with my love for technology, I have to admit that it has its limits.  For example, it takes a human brain to notice that data has been input incorrectly.  Computer “brains” might be faster than humans, but human brains are still better at pattern recognition.  For example, a human brain will notice that “300” is a ridiculous age for a human to be, but to a computer it is just a number.  A human will also notice similarities between “P. Dave” and “Pinal Dave,” but this would stump most computers.

In a database, these sorts of anomalies are incredibly important.  Databases are often used by multiple people who rely on this data to be true and accurate, so data quality is key.  That is why the improved SQL Server features Master Data Management talks about Data Quality Services.  This service has the ability to recognize and flag anomalies like out of range numbers and similarities between data.  This allows a human brain with its pattern recognition abilities to double-check and ensure that P. Dave is the same as Pinal Dave.

A nice feature of Data Quality Services is that once you set the rules for the program to follow, it will not only keep your data organized in the future, but go to the past and “fix up” any data that has already been entered.  It also allows you do combine data from multiple places and it will apply these rules across the board, so that you don’t have any weird issues that crop up when trying to fit a round peg into a square hole.

There are two parts of Data Quality Services that help you accomplish all these neat things.  The first part is DQL Server, which you can think of as the hardware component of the system.  It is installed on the side of (it needs to install separately after SQL Server is installed) SQL Server and runs quietly in the background, performing all its cleanup services.

DQS Client is the user interface that you can interact with to set the rules and check over your data.  There are three main aspects of Client: knowledge base management, data quality projects and administration.  Knowledge base management is the part of the system that allows you to set the rules, or program the “knowledge base,” so that your database is clean and consistent.

Data Quality projects are what run in the background and clean up the data that is already present.  The administration allows you to check out what DQS Client is doing, change rules, and generally oversee the entire process.  The whole process is user-friendly and a pleasure to use.  I highly recommend implementing Data Quality Services in your database.

Here are few of my blog posts which are related to Data Quality Services and I encourage you to try this out.

Reference: Pinal Dave (https://blog.sqlauthority.com)

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3 Comments. Leave new

  • Nice information, thanks for Sharing.

  • This might at first appear as a statement of the bl**ding obvious but as the cliche correctly indicates: “rubbish in, rubbish out”! Data quality has to be paramount for any serious database initiative. It’s what Sidestep 4 concentrates on with UK resident, address and related insight. I support Pinal Dave’s view to make quality the forefront of all insight. Thanks for the reminder.

  • Which is the difference between data quality and a good modelling database. Like DQS could see and repair age in range of 100 years and we could do the same with a (job to repair that ages already in + Check constraint to not let any ages enter with age incorrect + not null column to dont let age null ), just an exemple. Could you give an example that the RDBM could not do data DQS can do?


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