Mark Gschwind
Enterprise Information
Management in SQL Server 2012
Originally Titled “Master Data and Data Quality Managem...
Mark Gschwind
 Independent Consultant
 Business Intelligence practitioner, manager since 1995
 Over 50 Business BI proj...
Agenda
 Enterprise Information Management (EIM)
 What is it and why do we need it?
 Microsoft EIM, 3 technologies worki...
Why Do We Need EIM?
Impediments to EIM Success
DATA QUALITY
SERVICES
MASTER DATA
SERVICES
INTEGRATION
SERVICES
What is Data Quality?
DQS: What is Data Quality?
 Data Quality represents the degree to which the
data is suitable for business usages
 Data Q...
Common Data Quality Issues
Data
Quality
Issue Sample Data Problem
Standard Are data elements consistently
defined and unde...
Common Issues DQS Addresses
Name Gender Street House # Zip code City State D.O.B
John Doe Male 60th street 45 New York New...
DQS Use Cases
• One-Time cleanups
o Merge/Migrate multiple divisional CRMs into one
• Continuous Process with Steward Inte...
DQS Process
Build
Use
Knowledge
Management
Knowledge
Base
Demo
Integrate DQS using SSIS
(continuous low-intervention use case)
MDS: What is Master Data?

 Continuous quality management
 Ease of use for business users (not just IT)
 Effective sha...
MDS Use Cases
Regulatory
Enable security
management and auditing
of data used for
regulatory reporting
Data Warehouse /
Da...
Where is Master Data (in a DW)?
Versioning
Validation
Authoring business rules
to ensure data
correctness
Modeling
Entities, Attributes,
Hierarchies
Enabl...
MDS Architecture
MDS Database
Entity Based
Staging Tables
Subscription
Views
IIS Service
MDS Service
Excel Add-InWEB-UI
Ex...
Demo
Business Rules
 Business Rules are expressions and actions that
can govern the conduct of business processes*
 Enable da...
Security
 Functional area permissions
 Model/Entity level permissions provide column-
level security
 Hierarchy permiss...
DATA QUALITY
SERVICES
MASTER DATA
SERVICES
INTEGRATION
SERVICES
Key Takeaways
 SQL Server has tools to address EIM, the biggest
impediment to BI success
 EIM is People + Processes enab...
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Enterprise Information Management (EIM) in SQL Server 2012

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These are the slides from my 2013 SQL Saturday presentations in Mountain View and Sacramento. I suggest you view the (newer) videos, as they cover all that material and more. However, here is the session description these slides cover:
A recent survey by Information Week found that data quality is the greatest barrier to BI adoption in enterprises. MDS addresses this challenge with modeling, validation, alerting and security capabilities. In this presentation, you will learn how to use MDS to model your data to ensure correctness, update it with changes from your ERP, and create workflows with notifications. Next you will learn the capabilities of DQS and see how it addresses data standardization, completeness and other challenges. You will then see how to use them together to enable Enterprise Information Management. BI professionals will come away with knowledge on how to use tools that address the greatest risk to success for BI projects - data quality

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  • Working w these EIM technologies for 5 years, 7 implementations
  • How many people are using MDS or DQS ? How many people are using something else for MDM ?Need to start w a little background…
  • http://reports.informationweek.com/cart/index/downloadasset/id/8574“2013 Analytics & Information Management Trends” (in 2012 was “2012 BI and Information Management Trends”)Was top barrier in 2011 as well
  • Today I will show you 3 tools that address these top 3 impediments to success
  • Microsoft has 3 tools that work together to address these challengesThese technologies + People+ Processes is the MSFT strategy to Product accurate, trustworthy dataMDS appeared in 2008R2 (acquired Stratature), DQS in 2012 (acquired Zoomix). Integration of these products is a work-in-progress.
  • Data Quality is kind of like doing the dishes; a lot of work you don’t get much credit for
  • Larry English claims that “Poor data quality can cost companies 15% to 25% (or more) of their operating budget”Good discussion on the cost of bad data is here:http://dataqualitybook.com/?p=300
  • <skip>
  • Now, how to address DQ use cases
  • DQS is a Knowledge-Driven data quality solution,ie you must know some things about your data in order to cleanse it.Ie, you must know rules to identify valid values, lists of valid values, etc.Create a process to continually improve the KBReference data from the azure marketplace
  • Transition: from a “Continuous Process with Steward Intervention” use case to “Continuous Process with Minimal Intervention”Map values to a kb + domains in DQS, can do a conditional split on bad values etc
  • Transition: we’ve gone through 2 legs of EIM (DQS and SSIS), not the 3rd leg, MDS…most of us know what master data is, but stating some things about it will help frame our discussion about it.Because of its importance, it can be in the center of many business processes and hence must be effectively shared for both producing and consumingWhat MDS does is enable these different groups bring their objects together and they can be cared for centrallyOnce an organization has this, it can be used in a number of scenarios
  • Explaining by saying where it ends up
  • Let’s talk about MDS’s capabilities for addressing these use casesIn the center we have our data steward who uses the MDS web UI and Excel addin to continuously maintain data qualityModeling an enterprise’s master data objects is a capability brought to the data stewardship process, as well as…DQS – some integration, won’t be showing tonightData Quality Services is acquired from Zoomix in 2008MDS is acquired from Stratature in 2007
  • Now let’s talk about the underlying technologies supporting these capabilitiesA requirement for any MDM system these days is it has to be SOAP-enabled, to interact with ERPs like SAP and Oracle.The Windows Communication Foundation (or WCF), is an application programming interface (API) in the .NET Framework for building connected, service-oriented applications.The Excel addin communicates through WCF, the Web UI uses Silverlight 5 (new in 2012 and enhances the performance)BizTalk allows organizations to more easily connect disparate systems with over 25 multi-platform adapters and a robust messaging infrastructure.External systems can interact w MDS either through the WCF to the MDS service, or more directly with SQL tablesMention the database can be sql 2008 or sql 2012
  • DEMOS TO DO:TileSample
  • Slide Goal: Review what was saidThese technologies + People+ Processes is the MSFT strategy to Product accurate, trustworthy data
  • Enterprise Information Management (EIM) in SQL Server 2012

    1. 1. Mark Gschwind Enterprise Information Management in SQL Server 2012 Originally Titled “Master Data and Data Quality Management in SQL Server 2012”
    2. 2. Mark Gschwind  Independent Consultant  Business Intelligence practitioner, manager since 1995  Over 50 Business BI projects  Data Warehousing/Cubing/Reporting/Data Mining/EIM  MCP, certified in Oracle Essbase, Melissa Data MVP  Working with clients on EIM since 2008 mark@gschwindconsulting.com find me on www.linkedin.com/in/markgschwind Blog Site: www.marksbiblog.com
    3. 3. Agenda  Enterprise Information Management (EIM)  What is it and why do we need it?  Microsoft EIM, 3 technologies working together  DQS • Capabilities • Demo  SSIS  MDS • Capabilities • Demo  EIM=DQS+MDS+SSIS  Wrap up  Questions
    4. 4. Why Do We Need EIM?
    5. 5. Impediments to EIM Success
    6. 6. DATA QUALITY SERVICES MASTER DATA SERVICES INTEGRATION SERVICES
    7. 7. What is Data Quality?
    8. 8. DQS: What is Data Quality?  Data Quality represents the degree to which the data is suitable for business usages  Data Quality is built through People + Processes + Technology  Bad Data  Bad Business “Poor data quality can cost companies 15% to 25% (or more) of their operating budget” - Larry English (International Data Quality Expert)
    9. 9. Common Data Quality Issues Data Quality Issue Sample Data Problem Standard Are data elements consistently defined and understood? Gender code = M, F, U in one system and Gender code = 0, 1, 2 in another system Complete Is all necessary data present? 20% of customers‟ last name is blank, 50% of zip-codes are 99999 Accurate Does the data accurately represent reality or a verifiable source? A Supplier is listed as „Active‟ but went out of business six years ago Valid Do data values fall within acceptable ranges? Salary values should be between 60,000-120,000 Unique Data appears several times Both John Ryan and Jack Ryan appear in the system – are they the same person?
    10. 10. Common Issues DQS Addresses Name Gender Street House # Zip code City State D.O.B John Doe Male 60th street 45 New York New York 08/12/64 Jane Doe Male Jonathan ln 36 10023 Poughkeepsy NY 21-dec-1954 Name Gender Street House # Zip code City State D.O.B John Doe Male E 60th St 45W 10022 New York NY 08/12/64 Jane Doe Female Jonathan Lane 36 10023 Poughkeepsie NY 12/21/54 Name Address Postal Code City State John Smith 545 S Valley View Drive # 136 34563 Anytown New York Margaret & John smith 545 Valley View ave unit 136 34563-2341 Anytown New York Maggie Smith 545 S Valley View Dr Anytown New York John Smith 545 Valley Drive St. 34253 NY NY Name Address Zip Code City State Cluster John Smith 545 S Valley View Drive # 136 34563 Anytown New York 1 Margaret & John smith 545 Valley View ave unit 136 34563-2341 Anytown New York 1 Maggie Smith 545 S Valley View Dr Anytown New York 1 John Smith 545 Valley Drive St. 34253 NY NY 2 Before Before After After Completeness Accuracy Conformity Consistency Uniqueness
    11. 11. DQS Use Cases • One-Time cleanups o Merge/Migrate multiple divisional CRMs into one • Continuous Process with Steward Intervention o Vendor master with continuous trickle of data o Customer master with incomplete data • Continuous Process with Minimal Intervention o Database marketing mailing list
    12. 12. DQS Process Build Use Knowledge Management Knowledge Base
    13. 13. Demo
    14. 14. Integrate DQS using SSIS (continuous low-intervention use case)
    15. 15. MDS: What is Master Data?   Continuous quality management  Ease of use for business users (not just IT)  Effective sharing (producing and consuming)  Centralized maintenance, by different departments  Changes that keep pace with the business  Master Data contains different attributes for different departments (marketing, finance, operations, business groups…)  The challenge: To make a trusted single source of business data used across multiple systems, applications, and processes
    16. 16. MDS Use Cases Regulatory Enable security management and auditing of data used for regulatory reporting Data Warehouse / Data Marts Mgmt Operational Data Management Enable business users to manage the dimensions and hierarchies of DW / Data Marts Central data records mgmt and consumption sourced by other operational systems A company has adopted 6 “best of breed” systems from different vendors. They need to be able to propagate the correct customer information to each system in a consistent way. MDS provides a platform for central schema, integration points and validation for SI/ISV/Internal IT to develop a custom solution The IT department has built a data warehouse and reporting platform, but business users complain about the correctness of the dimensions and lack of agility in making updates. MDS empowers the business users to manage dimensions themselves while IT can govern the changes There are 3 G/L systems whose G/L accounts need to be consolidated and rolled up to create financial statements for regulatory reporting to several countries MDS enables an approval process for changes with role-based security and transactional auditing of all changes
    17. 17. Where is Master Data (in a DW)?
    18. 18. Versioning Validation Authoring business rules to ensure data correctness Modeling Entities, Attributes, Hierarchies Enabling Integration & Sharing MDS Capabilities Role-based Security and Transaction Annotation Master Data Stewardship External (CRM, ..) Excel DWH Loading batched data through Staging Tables Consuming data through Views Registering to changes through APIs Excel Add-In Web UI Workflow / Notifications Data Matching (DQS Integrated)
    19. 19. MDS Architecture MDS Database Entity Based Staging Tables Subscription Views IIS Service MDS Service Excel Add-InWEB-UI External System CRM/ERP Workflow / Notifications DWH Excel Cleansing and Matching (DQS) Silverlight SSIS SSIS SSIS BI OLAP External System WCF PW Pivot BizTalk / Others
    20. 20. Demo
    21. 21. Business Rules  Business Rules are expressions and actions that can govern the conduct of business processes*  Enable data governance by: -- Enforcing data standards -- Alerting users to data quality issues -- Creating simple workflows  Have limitations, but can be extended *EIM = DQS+MDS+SSIS+People+Process
    22. 22. Security  Functional area permissions  Model/Entity level permissions provide column- level security  Hierarchy permissions allow row-level security  Use AD groups, not individual users  Only use Hierarchy permissions if row-level security is required
    23. 23. DATA QUALITY SERVICES MASTER DATA SERVICES INTEGRATION SERVICES
    24. 24. Key Takeaways  SQL Server has tools to address EIM, the biggest impediment to BI success  EIM is People + Processes enabled by Technology

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