Data Quality Services-Making Data Suitable for Business

There are lots of DQ issues we are going to talk about some of the common issues and later on see how we handle them. The biggest issue that customer come to us with is data which is incorrect. What does it mean incorrect –
1.Misspelled names
2.Misspelled addresses – addresses which do not exist, e-mail addresses
 3.Another big problem we address in DQ issues is duplicates. Any company that deals with lots of companies has this problem. For example you can’t imagine how many entries for Boeing can be in a data source. If you have the same entity entered many time with different representations it can be a problem as now you won’t believe what your BI is telling you.
For example what is your total sales ?
Did you count them multiple times?
Did you under count them?
This is a huge problem. You can spend lots of time and money on your BI tools but if your underline data is wrong than it’s a waste of time and money.

This session will show you how to gain back that confidence by employing Data Quality Services from Microsoft.  A Knowledge base driven approach to cleaning your enterprise data.
Presented by Allan Mitchell at SQLBits IX
Tags BI
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  • SpeakerBIO
    Allan is the joint owner of Data Relish Ltd.  I work with companies helping them to decide how best to store their data  Key/Value (Redis) Document (DocumentDB, Mongo) Relational (SQL Server) NoSQL (Hadoop/HBase) I also help customers to decide on whether a move to cloud based offerings makes sense. The Azure platform from Microsoft has a lot to offer and it isn't necessarily a Cloud/On Premise binary choice. Hybrid scenarios make a lot of sense too. I also work with customers who have large scale or interesting data movement requirements. This could be batch processes which are complex or real-time sensor and telemetry data. We offer training as well as consultancy
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