In this article, we will talk briefly about data quality in SQL Server. Then, we will give a brief overview of the Melissa Data Quality for SQL Server Integration Services (SSIS), and we will demonstrate the components available in the community edition.
Read more »
An interesting opportunity arose at a client site during early October which provided a phenomenal opportunity to do a Data Quality Services implementation. My client (a grocer) had been requested to produce summary reports detailing the amount of funds spent during 2016 (YTD) with the myriad of manufacturers from whom the chain purchases their inventory. All “accounts payable” entries are done manually and as such are prone to errors.
Read more »
A few weeks back, I was approached by a client who lives in Cape Town, South Africa. The data that he wanted to insert into Master data services was far from clean and he was wondering if there was any way have a positive influence on the data quality.
Read more »
A year or so ago, I worked for an online web grocery software house located in the northern United States. At that time I had my ‘baptismal’ exposure to ‘genuinely dirty data’. Granted most of the data entry was done manually and many times from offshore. The point being that I could not fathom just how many ways there were to spell the brand name of a major cereal manufacturer. Why is this such an issue? The answer is fairly straight forward. Imagine the scenario that you are trying to ascertain the dollar value of breakfast cereals sold in the country from the local supermarket standpoint all the way up to national sales. Imagine this utilizing a SQL Server Multi-dimensional cube. The ‘eagle – eyed’ reader will recognize that the results will not aggregate correctly should our aggregation attributes have a plethora of different ways of being spelt. Read more »
© Quest Software Inc. ALL RIGHTS RESERVED. | GDPR | Terms of Use | Privacy