1. Data Governance at a glance…
Presented by: Warren Sifre

2. Warren Sifre Presenter… Principal Consultant / Technical Lead
Moser Consultant
LinkedIn:

3. Who is Warren??? Data Professional for over 20 years…
OCR/Spartan/Savage Racer and American Ninja Warrior in Training!!!
Interests in SQL Server, MongoDB, Hadoop, PowerShell, and Information Security
Indy BI PASS User Group Founder and Chapter Leader / Indy Power BI User Group Chapter Leader
Frequent national and international presenter for PASS SQL Saturday, PASS Local/Virtual User Groups, and other non-PASS related Conferences / User Groups
MSCE: Data Platforms/Business Intelligence, Hortonworks HCA, Teradata 14 CTP and many more…

4. Agenda Do you need Data Governance? What is Data Governance?
Data Governance Objectives
Data Governance Roles
Data Classification
Additional Elements to Data Governance
Keys to Successful Implementation

5. Do you need Data Governance?
Are there compliance requirements?
Are there security responsibilities?
Are users leveraging data in ways unbeknownst to the business?
Are users’ taxonomy confusing to other business units?
Are there challenges in data management, growth, and manageability?

6. What is Data Governance?
Defined by The Data Governance Institute as
“A system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.” 
In Short…
A way to ensure the quality, availability, integrity, security, auditability, and usability of data within an organization.

7. Data Governance Objectives
The Framework
Quality
Integrity
Availability
Security
Usability
Auditability

8. Data Governance Roles Data Trustee Data Steward Data Custodians
Planning and Policy Level responsibilities
Data Steward
Manage datasets and work with Data Custodians in implementation
Data Custodians
System and Database Admins
Data Users
Everyday Users who consume the data in the enterprise

9. Data Classification Levels
Public
Controlled
Restricted

10. Data Classification Execution
Source System
Risk
Competitor
Controlled
Compliance
Restricted
Employee Sensitive
Client Perception
No Risk
Everyone
Public

11. Additional Elements to Data Governance
Database Design Conventions
Modeling Style Guidelines
Data Name Conventions
Report Design Guidelines
Metadata Definitions
Reusable Assets such as Frameworks and Components

12. Reason why Dev Teams go rogue
Don’t know that it exists
Don’t know they should work with them
Too difficult to work with
Too slow to work with
Offers little value

13. Keys to Successful Implementation
Easy to adopt and provide value to devs
Adapt the process to changing needs
Build Compliance into your processes
Flexible Architectures and Frameworks
Ensure Data Gov is aligned with IT Gov
Evangelize the process and value it provides