Data governance in a Cloud BI world

© 2018 Visual BI Solutions, Inc. All rights reserved. www.visualbi.com
DATA GOVERNANCE IN
A CLOUD BI WORLD
Clint Vallandingham
Sr. Manager BI & Analytics www.visualbi.com
Chandler Stevens
VP, Microsoft BI & Analytics

© 2018 Visual BI Solutions, Inc. All rights reserved. www.visualbi.com 3
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Data Governance in a Cloud BI World
WEBINAR AGENDA
Introduction1
Data quality and the modern data warehouse2
Establishing data integrity and accountability4
Conclusion
Ensuring compliance with Azure governance3
Development lifecycle with Azure DevOps6
Accountability of the data steward5
7
BI Vantage8

Introduction
What is Data Governance?
Wikipedia defines data governance as, “the people, processes, and
information technology required to create a consistent and proper
handling of an organization's data across the business enterprise.
This definition holds just as true when utilizing cloud based resources
and technologies.
1. People
The data steward plays a critical role in the success of a data governance program. Ownership and accountability must be assigned and agreed upon prior to
releasing data and analytics to an enterprise.
2. Process
Data governance requires a well-defined process or workflow where data is stored or ingested and transformations are applied. Additions or modifications to
this process must go through change control. Security should be a consideration at every step of this process.
3. Technology
The technology must meet the standards defined in the data governance program. The technology chosen should help with the implementation considerations
such as security and availability.

Why Data Governance?
A good data governance program can have many benefits. We are going
to focus on a few key elements and the role of Cloud BI in each of these
areas:
Quality
Data quality must be established and maintained throughout the
lifecycle of the data.
Compliance
Good data governance practices help ensure not only internal
compliance but also from external entities such as GDPR.
Integrity
A combination of security and change control can help ensure the
integrity of the data from source to destination.
Accountability
If and when the data comes into questions it is important that data
stewards have validated and approved the data and analytics.
Introduction

Cloud Considerations
When choosing cloud based resources for a data services solution it is important to ensure those solution are complaint and can even help
when implementing a data governance program. In this presentation we will focus on Microsoft’s Azure platform and demonstrate how to
implement data governance procedures using Azure.
Policies should be drafted and followed for each of these key areas:
Data Lifecycle – Organizational policy should classify data and define when that data should be removed from the cloud based data
services. This helps control cost and reduces risk.
Security – Policy should define access and accessibility at the data set level and this policy must be followed across cloud based resources.
Logging & Metadata – Cloud based services should provide adequate logging to ensure integrity of the data services solution. The service
should also provide relevant metadata of the data set as to the source, type and owner.
Transformation – Policy should require all transformations are documented and approved by the data steward. Transformations may occur
at different stages in the data lifecycle. It is critical that all are documented and approved.
Introduction

QUALITY COMPLIANCE INTEGRITY ACCOUNTABILITY
Data Quality and The Modern Data Warehouse
System Record
Establish authoritative source
for data elements
Single Source of Truth
Master Data Management
Critical data elements
MDM Software
Semantic Modeling
Business Terminology
Self-service BI & Analytics
Azure Analysis Services

Ensuring Compliance with Azure Governance
Firewall
Protection
Traditional On-Premise
Protection
Establishing
Identity
Azure Active Directory
Group Based
Security
Managing access at Scale
Hierarchies
Policy and
Blueprints
Tracking Compliance
Managing Policies

Establishing Data Integrity and Accountability
Service Level Agreements
Commitment to availability and quality
Penalties
Data orchestration
Data movement and transformation
Azure Data Factory

Accountability of The Data Steward
Ownership
Ensure data quality
Communication
Monitoring
Retroactive & Proactive
Process Improvement

13
Continuous integration (CI)
Continuous delivery (CD)
Continuous deployment
with CI/CD
Development Lifecycle with Azure DevOps

Azure Modern Data Warehouse and Advanced Analytics

Data Governance Takeaways
⇢ Cloud BI presents many data governance challenges over traditional on-premise
solutions
⇢ Azure offers a rich suite of tools to help overcome these challenges
⇢ Data quality, compliance, integrity and accountability can all be accomplished with a
strong data governance program
⇢ The data steward plays a crucial role in the success of the data governance program
Conclusion

Introducing BI Vantage
Modern Data Warehousing Offering
§ Establish a foundation for delivering data
analytics to your business decision makers
§ Provides a low TCO solution coupled with a quick
and iterative implementation window
§ Allows your organization to right-size the
implementation to address business
requirements
§ Enables a “pay as you go” scalable solution that
grows with the needs of your business over time
§ Brings together the industry leading Visual BI
data warehousing experience coupled with the
Microsoft Azure data platform
Fast Time
to Value

Q&A

www.visualbi.com
THANK YOU! gopal
@visua
lbi.com
Chandler Stevens
for your Time
chandlers@visualbi.com
www.visualbi.com
VP, Microsoft BI & Analytics
Clint Vallandingham
clintv@visualbi.com
Sr. Manager BI & Analytics

Data governance in a Cloud BI world

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