Session talks about SQL 2012 Enterprise Informatoin Managment

1. Enterprise Information Management with DQS, MDS and SSIS
http://blogs.msdn.com/karang
http://karanspeaks.com

2. 
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Data Warehousing Concepts
 Master Data
 Fact Data
Enterprise Information Management (EIM)
 What is it and why do we need it?
Microsoft EIM, 3 technologies working together
 DQS
• Capabilities and Demo
 MDS
• Capabilities and Demo
• SSIS
 EIM=DQS+MDS+SSIS
Questions

3. 
A data warehouse is a general structure for storing the data needed for good BI
(Business Intelligence).
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Data in a warehouse is of little use until it is converted into the information that decision
makers need.
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The large relational databases, typical of data warehouses, need additional help to
convert the data into information.
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In data warehouse we have two kinds of data
and

4. 
Measures are the key performance indicators that you want to evaluate.

To determine which of the numbers in the data might be measures, here
is a rule of thumb:


If a number makes sense when it is aggregated, then it is a measure.
Examples
 Salary
 Utilization
 Sales

5. 
Dimensions are the categories of data analysis.

Here is the rule of thumb:
 When a report is requested "by" something, that something is usually a
dimension.
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Examples
 Employee
 Geography
 Department
 Products

6. What is EIM – Enterprise Information Management
The set of capabilities enabling the
enterprise to get the right data to the right
consumers, reliably, repeatedly, efficiently &
with high confidence.

8. SQL 2012 Enterprise Information Management
Data Quality Services
Knowledge based Data
Cleansing and Matching
Master Data Services
Master and reference
data Management
Integration Services
ETL and Data Integration
Tool

9. SQL Server Data Quality Services
A knowledge driven Data Quality Solution

10. What is Data Quality ?

12. What is SQL 2012 DQS ?
Data Quality Services (DQS) is a
Knowledge-Driven data quality solution,
enabling IT Pros and data stewards to
easily improve the quality of their data

13. Knowledge Bases
• To prepare knowledge for a data quality project, you build and
maintain a knowledge base (KB) that DQS can use to identify
incorrect or invalid data.
Domains
• Knowledge in a knowledge base is maintained in domains,
each of which is specific to a data field.
Knowledge Discovery
• A computer-assisted process that builds knowledge into a
knowledge base by processing a data sample

15. DQS

16. SQL Server Master Data Services
SQL Server Master Data Services provides a central
data hub that ensures the integrity of information and
consistency of data is constant across different
applications.

17. Master Data
People
Things
Places
Abstract
• Customers
• Products
• Stores
• Contracts
• Vendors
• Organizational units
• Wells
• Warranties
• Sales people
• Recipes
• Power lines
• Time
• Employees
• Parts
• Geo areas
• Metrics
• Partners
• Storage bins
• Warehouses
• Securities
• Patients
• Documents

18. Where is the real Boeing?
Boeing
Boeing Inc
HR Doc
Boeing (Renton)
Aut_Boeing
Boein’
Asset Mgmt
Purchasing DB

19. No single, trusted source of the truth
No dimension maintenance capability
Conflicting views of product, customer location, etc
No system to maintain attributes
Multiple stakeholders for the same record
Inability to enforce data stewardship processes
Inconsistencies cost – mistakes, incorrect reports, etc.

21. MDS

22. Conclusion
Enterprise Integration Management (EIM) provides an a
portfolio of solutions that enable organizations to trust the
credibility and consistency of their data so they can make
critical business decisions.

23. Thanks
EIM EBooks
Master Data Services (MDS) Operations Guide
Master Data Services
Data Quality Services

24. Stay Connected
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