Data Quality Services and Master Data Services: good partners within the enterprise
Ask any business person if their data is clean enough to make efficient and effective decisions and the answer is generally “No”. This is particularly important when it comes to governmental and financial regulations (such as GDPR) and this is where Master Data Services can really help us!
We are going to see that, if Master Data Services is properly implemented the answer can become a “Yes” and this will be the conclusion that we shall arrive at by the end of this full day session.
In this full day precon, we shall be covering the following
1) A high overview of how ALL of the pieces fit together.
2) Using extremely dirty data we shall see how Data Quality Services can be utilized to modified/cleanse dirty data AND THEN modify future incoming data based upon Artificial Intelligence (AI).
3) We shall discuss the concepts of Models, Entities and Attributes.
4) We shall create a “model” from scratch, defining rules and validations that must be implemented.
5) We shall discuss the inclusion of 3rd Party data into our models.
6) We shall also create additional models based upon model inheritance and see how easily all this may be achieved.
7) We shall be incorporating SQL Server Integration Services into the blend and see how daily processing and updates may be automated (i.e. Data Quality Services and Business Analyst changes).
8) We shall be looking at how the AI within Data Quality Services is able to classify data as either New, Correct, Corrected or Invalid and see how we may route the invalid data back to the business side to be corrected, and then (once corrected) incorporated into the next daily/hourly loads to production.
9) We shall also create model backups in case issues go awry.
10) We shall then see how easily these models may be “recovered”.
11) We now move onto Master Data Services.
12) We shall be creating a working Master Data Services model.
13) We shall see the “method in the madness” of the integration our Master Data Services Model into the Data Quality services model.
14) We shall be looking at and implementing Master Data Services security and see how this is as effective and efficient as utilizing the database engine. Why?
15) We shall be creating Master Data Services entities and attributes.
16) We shall be creating a Master Data Services GUI for the business side to correct and maintain corporate data. This includes ongoing new data.
17) We shall be see how Data Quality Services and Master Data Services may be integrated to produce the COMPLETE SOLUTION.
18) We shall be working with SQL Server Integration Services to automate the daily / hourly processing of data from both Master Data Services and Data Quality Services.
19) We shall be discussing and looking at how we can ease post auditing and required maintenance issues.
20) Lastly we shall be looking at the GOTCHA’s.