RWDG Webinar: Big Data & BI Analytics Require Data Governance

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Copyright © 2015 Robert S. Seiner – KIK Consulting & Educational Services / TDAN.com
Non-Invasive Data Governance™ is a trademark of Robert S. Seiner & KIK Consulting
#RWDG
@RSeiner
Real-World Data Governance
Big Data & BI Analytics Require Data Governance
Monthly Webinar Series Hosted by Dataversity
Robert S. Seiner – KIK Consulting / TDAN.com
July 16, 2015 – 2:00 p.m. EST
Robert S. Seiner
KIK Consulting & Educational Services, LLC - KIKconsulting.com
The Data Administration Newsletter, LLC - TDAN.com

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• Real-World Data Governance – Monthly Webinar Series
– August 20 – Data Governance & Data Steward Certification
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– or TDAN.com or KIKConsulting.com
* with David C. Hay
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• Non-Invasive Data Governance:
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A Strategic Data Framework Based on
Governance Best Practices

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• This webinar will cover:
– Existing Governance Applications for BI
– Future of Big Data & BI Data
– Relationship between Big Data, BI and Governance
– Articulating Value
– True Intelligence Derived from Governed Data
Abstract

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• Data Governance is the execution and enforcement of authority
over the management of data and data-related assets.
• Data Stewardship is the formalization of accountability for the
management of data and data-related assets.
Definitions

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• Non-Invasive Data Governance™
– The practice of:
• applying formal accountability & behavior
• through a non-invasive framework of roles & responsibilities
• to existing and / or new processes
• to assure that the definition, production & usage of data
• improves regulatory compliance, security, privacy & protection.
– Non-Invasive describes how governance is applied to assure
non-threatening management of valuable data assets.
– The goal is to be
» Transparent
» Supportive
» Collaborative.
Definitions

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• Big Data
– Broad term for data sets so large or complex that traditional data
processing applications are inadequate.
– Challenges include, but are not limited to:
• Analysis
• Capture
• Curation
• Search
• Sharing
– Data Governance must be applied to all of these challenges.
• Storage
• Transfer
• Visualization
• Information Privacy
Applications of Data Governance
Wikipedia

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• Business Intelligence
– Set of techniques and tools for the transformation of raw data into
meaningful and useful information for business analysis purposes.
– Common functions include, but are not limited to:
• Reporting
• Online Analytical Processing
• Process Mining
• Complex Event Processing
– Data Governance must be applied to all of these functions.
• Business Performance Management
• Benchmarking
• Predictive Analytics
• Prescriptive Analytics
Wikipedia

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• As companies generate increasingly more content (read big data),
they are coming to recognize that [big data] analytics is a
nonnegotiable.
• Gleaning business insight from [big data] analytics is still in the
early-adopter and well-hyped phase, but companies are beginning
to see results emerge in terms of smoother workflows, improved
search and better compliance [read governance] practices.
http://searchcontentmanagement.techtarget.com/tip/Content-analytics-becomes-an-enterprise-must-have

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• [Big Data] analytics is a business practice that analyzes and derives
insight from data about the amount of content being created, the
nature of that content and how it is used.
• [Big Data] analytics can help companies manage their information
lifecycle management chains by creating relevant cost and
consumption metrics.
• With business metrics in place, companies can identify which digital
content [big data] is most valuable and adjust investments in
storage and future analytics as needed.
http://searchcontentmanagement.techtarget.com/tip/Content-analytics-becomes-an-enterprise-must-have

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• How Much Data is Big?
– Bytes (8 bits)
– Kilobyte (1000 bytes)
– Megabyte (1 000 000 bytes)
– Gigabyte (1 000 000 000 bytes)
– Terabyte (1 000 000 000 000 bytes)
– Petabyte (1 000 000 000 000 000 bytes)
– Exabyte (1 000 000 000 000 000 000 bytes)
– Zetabyte (1 000 000 000 000 000 000 000 bytes)
– 2.7 Zetabytes of data existed in the digital universe as of 2012 – 35 Zetabytes to be created annually by 2020
– Yottabyte (1 000 000 000 000 000 000 000 000 bytes)
– Xenottabyte (1 000 000 000 000 000 000 000 000 000 bytes)
– Shilentnobyte (1 000 000 000 000 000 000 000 000 000 000 bytes)
– Domegemegrottebyte (1 000 000 000 000 000 000 000 000 000 000 000 bytes)
More Data Then We Can Count

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• Why does Big Data require Data Governance?
– Big Data as an Asset
– Formalized Accountability
– Following the Rules
– Consistency in Big Data Application
– Metadata to Improve Value & Understanding
– Management of Big Data Definition
– Management of Big Data Production
– Management of Big Data Usage
Why?

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• Why do BI Analytics require Data Governance?
– Data Drives Analytics
– Formalized Accountability
– Following the Rules
– Consistency in Analytical Application
– Metadata to Improve Value & Understanding
– Management of BI Data Definition
– Management of BI Data Production
– Management of BI Data Usage
Why?

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• Metadata Past and Future
– Metadata in the past was limited to :
• Names
• Definitions
• Labels
– Metadata now encompasses
• Relationships between the
– Data
– People
– Processes
– Use of Big Data
Metadata Lies at the Core

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• Metadata Required
– Metadata Continues to Evolve
• From a Data Management Asset
• To a Business Intelligence / Data Warehousing Asset
• To a Data Governance Asset
• To a Privacy and Confidentiality Asset
• To a Big Data & Analytical Asset
Metadata Lies at the Core

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• Data Governance required for:
– Structured data
– Unstructured data
– Content
– Record
– Logs
– Social Media
Governance Lies at the Core

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• Data Governance required for:
– Big Data
– Small Data
– Data Warehouse Data
– Master Data
– Metadata
– Analytical Data

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• Governing Perspectives for Big Data or Analytical Data
– Accountability Perspective
– Process Perspective
– Rules Perspective
– Inventory Perspective
– Decision Making Perspective

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– Accountability Perspective
• Definition
• Production
• Use
• Protection
• Understanding
• Retention / Elimination

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– Process Perspective
• Bill of “Rights”
• Ownership
• Participation
• Input
• Output / Outcomes
• Throughput

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– Rules Perspective
• Business Rules
• Compliance Rules
• Protection Rules
• Standard Rules

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– Inventory Perspective
• Quantitative
• Qualitative
• Ownership
• Usage

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– Decision Making Perspective
• Who makes the decision
• How they make the decision
• When they make the decision
• Who is impacted by the decision
• How they track decisions

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• To look at the future … Let’s start by looking at the past …
– Business Intelligence Strategies have evolved from …
• Hierarchical Design
• Relational Design
• Dimensional Design
• Enterprise Data Warehouses
• Data Marts / Cubes / Distributed Databases
• Data Lakes – object-based storage repository that holds data
in its native format until it is needed.
• Unstructured Data & Big Data
Future of Big Data & BI

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• OK … Now let’s look to the future …
– Business Intelligence Strategies have evolved to …
• Data Mining – looking for a needle in the haystack
• Big Data Analytics – looking at the whole haystack

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• Three Vs of Big Data
– Volume
– Velocity
– Variety
– You saw the chart – Growing exponentially
– Present state handling of the Three Vs

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• What are we going to do with all this data?
– We need to be able to make sense of the data.
– We need to be able to understand and trust the data.
– We need to be able to protect the data.
– We need to know where the data comes from.
– We need to be able to access the data.
– We need to be able to analyze the data.

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• To achieve these goals:
– We need to be able to make sense of the data.
– We need to be able to understand and trust the data.
– We need to be able to protect the data.
– We need to know where the data comes from.
– We need to be able to access the data.
– We need to be able to analyze the data.
• What do we need? Data & Process & Technology
And we need all these things to be governed.
Some call this Information Governance.

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• Value of Data Governance to Big Data
– We just spoke about this so let’s reverse it!
• Value of Data Governance to BI Analytical Data
– We just spoke about this so let’s reverse it!
» What is the value of Big Data to Data Governance?
» What is the value of BI Analytics to Data Governance?
Value of Governance

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• What is the value of Big Data to Data Governance?
• What is the value of BI Analytics to Data Governance?
• Organizations need to use these things as their crutch to
– justify the investment in …
– maximize use of resources when doing …
– provide trustable data from …
– make better decisions using …
Value to Governance

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• Bold Statement 1:
– Organizations that govern their data effectively get more value
from their Big Data and BI Analytics effort.
Value to Governance

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• Bold Statement 2:
– Organizations that do not govern their data effectively either:
• Do not embark on these activities
• Get less value from their data-driven activities
Value to Governance

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• Deriving Intelligence from Governed Data requires:
– Quality
– Understanding
– Protection
– Availability
– Accountability
True Intelligence

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– Quality
• Data Standards
• Followed Process
• Escalation Paths
• Decision Rights
• Certification
True Intelligence

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– Understanding
• Glossary
• Dictionary
• Mapping
• Validation
• Education
True Intelligence

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– Protection
• Classification
• Security
• Auditability
• Process / Education
• Enforcement / Compliance
True Intelligence

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– Availability
• Access
• Storage
• Timeliness
• Completeness
True Intelligence

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– Accountability
• Formalization
• Stewardship
• Communications
• Execution – Enforcement of Authority
True Intelligence

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@RSeiner
• Main Points Covered:
– Existing Governance Applications for BI
– Future of Big Data & BI Data
– Relationship between Big Data, BI and Governance
– Articulating Value
– True Intelligence Derived from Governed Data
Summary

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#RWDG
@RSeiner
• Real-World Data Governance – Monthly Webinar Series
– August 20 – Data Governance & Data Steward Certification
Upcoming Webinar

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#RWDG
@RSeiner
• Robert S. Seiner
KIK Consulting & Educational Services – KIKconsulting.com
The Data Administration Newsletter – TDAN.com
Post Office Box 112571, Upper St. Clair, Pennsylvania 15241
412.220.9643, 412.220.9644 (Fax)
rseiner@kikconsulting.com
rseiner@tdan.com
@RSeiner
#RWDG
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RWDG Webinar: Big Data & BI Analytics Require Data Governance

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RWDG Webinar: Big Data & BI Analytics Require Data Governance