Data Governance at a glance… Presented by: Warren Sifre

Warren Sifre Presenter… Principal Consultant / Technical Lead Moser Consultant Email: warren.sifre@moserit.com Twitter: @WAS_SQL LinkedIn: www.linkedin.com/in/wsifre

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…

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

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?

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.

Data Governance Objectives The Framework Quality Integrity Availability Security Usability Auditability

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

Data Classification Levels Public Controlled Restricted

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

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

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

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