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© 2014 IBM Corporation
IBM Big Data Governance
© 2014 IBM Corporation2
What you’ll learn…
 The opportunity
 Big data governance:
 Requirements
 How it works
 Capabilities
 A holistic approach
 Next steps
© 2014 IBM Corporation3
Veracity: Can I trust what I am seeing?
What Is Big Data?
 Immense volume, variety and velocity of data, in context, beyond what was
previously possible
 Opportunity to derive new insights – challenged by questionable veracity
Volume
Prevent customer churn
call detail records per day
500million
Velocity
trade events per second
Identify potential fraud
5 million
is images, video, documents
Improve customer satisfaction
80%
Variety
from surveillance cameras
Monitor events of interest
100’s of video
feeds
of data
growth
meter readings per annum
350billion
Analyze product sentiment
of Tweets create daily
12 terabytes
Predict power consumption
© 2014 IBM Corporation4
Utilities
• Weather analysis
• Smart grid management
Retail
• 360° View of the customer
• Real-time promotions
Law Enforcement
• Multimodal surveillance
• Cyber security detection
Transportation
• Logistics optimization
• Traffic congestion
Financial Services
• Fraud detection
• 360° View of the customer
Information Technology
• System Log Analysis
• Cybersecurity
Health & Life Sciences
• Epidemic early warning
• ICU monitoring
Telecommunications
• Geomapping/marketing
• Network monitoring
What Can You Do With Big Data?
© 2014 IBM Corporation5
c
cc
c
cMake decisions on
untrusted information1in 3
60%
Don’t have necessary
information1in 2
Time spent per big data project
to find, prepare, understand &
defend information due to lack
of context
80%
Have more data than
they can use60%
So, How Are We Doing?
© 2014 IBM Corporation6
American’s in a recent survey
don’t want personalized
on-line advertising
When you tell them the
information you collect and
store in order to do it
66%
Increasing to
86%
© 2014 IBM Corporation7
Context, Agility and Security are Essential Requirements to
Meet Business Objectives in a Big Data Environment
Agility
A business framework
(policies) for determining
how and where to use
big data.
Context
Flexibility to establish
and maintain context
independent of the
volume, variety and
velocity of data.
Security
Protection of data privacy and access; compliance with data
security and other regulatory requirements
Essential
Requirements
© 2014 IBM Corporation8
Context Requires Governance;
Agility Requires a Unique Big Data Approach to Governance
Traditional approach Big data approach
Govern data to the highest standard.
Store it, then use it for multiple purposes
Understand data and usage. Govern to
the appropriate level. Use it, and iterate
RepositoryGovern
to
Perfection
UseData
Data
Explore/
Understand
Govern Appropriately
Use
How does an organization achieve agility in creating and
continually evolving a safe and secure context in big data environments?
© 2014 IBM Corporation9
ACT
Implement
planned
projects with
governed
data search,
preparation,
defense and
security
Begin by
defining the
business
problem to
solve with big
data
Obtain
Executive
Sponsorship
2
Align
Teams
3
Understand
Data Risk and
Value
4
Define
Business
Problem
1
Measure
Results
6
Implement
Analytical /
Operational
Project(s)
5
ACT
ASSESSPLAN
Defend Secure and
Comply
PrepareFind
Big Data Governance is a Holistic Approach
Obtain
executive
sponsor to
finalize
priorities and
goals
Update
governance
roles to
account for
big data
Categorize
data to
understand
risk exposure
Assess
governance
results and
adjust
© 2014 IBM Corporation10
Key Data Scenarios for Big Data Governance
Find Prepare Defend Secure and Comply
Establish context to
find, visualize, and
understand data for
improved decision
making
Understand context to
extract, cleanse,
integrate and monitor
data properly, to
increase integrity and
trustworthiness for
subsequent usage
Build confidence in
information by making it
defensible against
challenges
Protection of data
privacy and access;
compliance with data
security and other
regulatory requirements
Analytical use Operational use
© 2014 IBM Corporation11
Find
Establish context to find,
visualize, and understand
data for improved decision
making
Capabilities to Consider
The Cost
is High
of data scientists’
time on big data projects is
spent finding and preparing data
80%
Connectivity
to sources
Real-time
queries
(SQL, etc)
Enterprise
search
Automated
data
discovery
Data profiling
Key Data Scenarios for Big Data Governance
© 2014 IBM Corporation12
Key Data Scenarios for Big Data Governance
Prepare
Understand context to
extract, cleanse, integrate
and monitor data properly
to increase integrity and
trustworthiness for
subsequent usage
Capabilities to Consider
The Risk
is Real
Highly
scalable data
integration
Define terms
and policies
Data
cleansing
Quality
dashboarding
Rich
annotation
© 2014 IBM Corporation13
Capabilities to Consider
Maintain data
lineage
Data quality
dashboarding
Master data
management
Make decisions on untrusted
information
Defend
Build confidence in
information by making it
defensible against
challenges
The Risk
is Real
1 in 3
Key Data Scenarios for Big Data Governance
© 2014 IBM Corporation14
Capabilities to Consider
Secure data
at rest and in
motion
Data
masking
Governed
data
retention
Test data
management
Governance
reporting
$200 million
just to replace
cards!
Secure and
Comply
Protection of data privacy
and access; compliance
with data security and
other regulatory
requirements
The Risk
is Severe
Key Data Scenarios for Big Data Governance
© 2014 IBM Corporation15
Organizations rated their
decision making as
7 or higher on a scale
of 1 to 10
4 out of 5
Organizations are
improving at 3 times the
rate of competitors
3X
Of organizations show
high or very high levels
of trust
77%
Source: The Big Data Imperative: Why Information Governance Must Be Addressed Now, Aberdeen Group, Dec 2012
IBM Big Data Governance Offers a Golden Opportunity
© 2014 IBM Corporation16
All Hadoop Vendors Talk About Their Big “Data Lake”.
ONLY IBM Delivers Consumable Big Data From The Swamp.
Clean Hadoop LakeHadoop Data Swamp
IBM Big Data Governance–including quality, security, and data lineage–
transforms your Hadoop Data Swamp to a consumable Big Data Lake.
© 2014 IBM Corporation17
A Complete Big Data Solution Is More Than Just An Engine
© 2013 IBM Corporation
IBM Teradata Pivotal INFA Cloudera Horton
Hadoop Distribution  Horton    
Hadoop Available via Appliance     ORCL & HP Teradata
Hadoop SQL Engine  Postgre    
Streaming Data    
Flume/
Storm
Flume/
Storm
Data Exploration Tools      
Enterprise Reporting      
Data Provisioning Tools  IBM, INFA   Scripting Talend
Security Monitoring  Protegrity    
ELT, ETL & Replication  IBM, INFA    Talend
Metadata & Lineage  Revelytix    
Profile & Cleanse (native)  IBM, INFA    Talend
Hadoop Matching (native)  IBM, INFA    
Reference Data Mgmt.      
Data Masking on Hadoop  IBM, INFA    
Archiving on Hadoop      
© 2014 IBM Corporation18
Reduces reporting time
from 2 to 3 days to minutes
“The IBM analytics solution greatly improves our ability
to define and monitor business KPIs, and it brings much
greater transparency to reporting. We now have a
single version of the truth and a single comprehensive
report for each topic.”
— Irfan Zafar, Chief Technology Innovation Officer
and Senior General Manager of Customer Services,
Sui Southern Gas Company Limited
Enables timely analytics
combining real-time operational
and geographic data from over
5000 sources
Single source to
information
that is reliable and provides better
clarity into the supply chain
Chemicals & Petroleum, Energy & Utilities
The transformation: Deployed an analytics solution
that overlays digital maps with real-time operational
and financial data, enabling SSGC to analyze data in
a real-world context.
IBM Software–Information Management
Sui Southern Gas Company
Mitigates Business Risk Through Insights Into Supply and Demand
Learn more: https://ibm.biz/bigdatagovernance
© 2014 IBM Corporation20
Legal Disclaimer
• © IBM Corporation 2014. All Rights Reserved.
• The information contained in this publication is provided for informational purposes only. While efforts were made to verify the completeness and accuracy of the information contained
in this publication, it is provided AS IS without warranty of any kind, express or implied. In addition, this information is based on IBM’s current product plans and strategy, which are
subject to change by IBM without notice. IBM shall not be responsible for any damages arising out of the use of, or otherwise related to, this publication or any other materials. Nothing
contained in this publication is intended to, nor shall have the effect of, creating any warranties or representations from IBM or its suppliers or licensors, or altering the terms and
conditions of the applicable license agreement governing the use of IBM software.
• References in this presentation to IBM products, programs, or services do not imply that they will be available in all countries in which IBM operates. Product release dates and/or
capabilities referenced in this presentation may change at any time at IBM’s sole discretion based on market opportunities or other factors, and are not intended to be a commitment to
future product or feature availability in any way. Nothing contained in these materials is intended to, nor shall have the effect of, stating or implying that any activities undertaken by
you will result in any specific sales, revenue growth or other results.
• If the text contains performance statistics or references to benchmarks, insert the following language; otherwise delete:
Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will
experience will vary depending upon many factors, including considerations such as the amount of multiprogramming in the user's job stream, the I/O configuration, the storage
configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results similar to those stated here.
• If the text includes any customer examples, please confirm we have prior written approval from such customer and insert the following language; otherwise delete:
All customer examples described are presented as illustrations of how those customers have used IBM products and the results they may have achieved. Actual environmental costs
and performance characteristics may vary by customer.
• Please review text for proper trademark attribution of IBM products. At first use, each product name must be the full name and include appropriate trademark symbols (e.g., IBM
Lotus® Sametime® Unyte™). Subsequent references can drop “IBM” but should include the proper branding (e.g., Lotus Sametime Gateway, or WebSphere Application Server).
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一比一原版(IIT毕业证)伊利诺伊理工大学毕业证成绩单
 

Why You Need to Govern Big Data

  • 1. © 2014 IBM Corporation IBM Big Data Governance
  • 2. © 2014 IBM Corporation2 What you’ll learn…  The opportunity  Big data governance:  Requirements  How it works  Capabilities  A holistic approach  Next steps
  • 3. © 2014 IBM Corporation3 Veracity: Can I trust what I am seeing? What Is Big Data?  Immense volume, variety and velocity of data, in context, beyond what was previously possible  Opportunity to derive new insights – challenged by questionable veracity Volume Prevent customer churn call detail records per day 500million Velocity trade events per second Identify potential fraud 5 million is images, video, documents Improve customer satisfaction 80% Variety from surveillance cameras Monitor events of interest 100’s of video feeds of data growth meter readings per annum 350billion Analyze product sentiment of Tweets create daily 12 terabytes Predict power consumption
  • 4. © 2014 IBM Corporation4 Utilities • Weather analysis • Smart grid management Retail • 360° View of the customer • Real-time promotions Law Enforcement • Multimodal surveillance • Cyber security detection Transportation • Logistics optimization • Traffic congestion Financial Services • Fraud detection • 360° View of the customer Information Technology • System Log Analysis • Cybersecurity Health & Life Sciences • Epidemic early warning • ICU monitoring Telecommunications • Geomapping/marketing • Network monitoring What Can You Do With Big Data?
  • 5. © 2014 IBM Corporation5 c cc c cMake decisions on untrusted information1in 3 60% Don’t have necessary information1in 2 Time spent per big data project to find, prepare, understand & defend information due to lack of context 80% Have more data than they can use60% So, How Are We Doing?
  • 6. © 2014 IBM Corporation6 American’s in a recent survey don’t want personalized on-line advertising When you tell them the information you collect and store in order to do it 66% Increasing to 86%
  • 7. © 2014 IBM Corporation7 Context, Agility and Security are Essential Requirements to Meet Business Objectives in a Big Data Environment Agility A business framework (policies) for determining how and where to use big data. Context Flexibility to establish and maintain context independent of the volume, variety and velocity of data. Security Protection of data privacy and access; compliance with data security and other regulatory requirements Essential Requirements
  • 8. © 2014 IBM Corporation8 Context Requires Governance; Agility Requires a Unique Big Data Approach to Governance Traditional approach Big data approach Govern data to the highest standard. Store it, then use it for multiple purposes Understand data and usage. Govern to the appropriate level. Use it, and iterate RepositoryGovern to Perfection UseData Data Explore/ Understand Govern Appropriately Use How does an organization achieve agility in creating and continually evolving a safe and secure context in big data environments?
  • 9. © 2014 IBM Corporation9 ACT Implement planned projects with governed data search, preparation, defense and security Begin by defining the business problem to solve with big data Obtain Executive Sponsorship 2 Align Teams 3 Understand Data Risk and Value 4 Define Business Problem 1 Measure Results 6 Implement Analytical / Operational Project(s) 5 ACT ASSESSPLAN Defend Secure and Comply PrepareFind Big Data Governance is a Holistic Approach Obtain executive sponsor to finalize priorities and goals Update governance roles to account for big data Categorize data to understand risk exposure Assess governance results and adjust
  • 10. © 2014 IBM Corporation10 Key Data Scenarios for Big Data Governance Find Prepare Defend Secure and Comply Establish context to find, visualize, and understand data for improved decision making Understand context to extract, cleanse, integrate and monitor data properly, to increase integrity and trustworthiness for subsequent usage Build confidence in information by making it defensible against challenges Protection of data privacy and access; compliance with data security and other regulatory requirements Analytical use Operational use
  • 11. © 2014 IBM Corporation11 Find Establish context to find, visualize, and understand data for improved decision making Capabilities to Consider The Cost is High of data scientists’ time on big data projects is spent finding and preparing data 80% Connectivity to sources Real-time queries (SQL, etc) Enterprise search Automated data discovery Data profiling Key Data Scenarios for Big Data Governance
  • 12. © 2014 IBM Corporation12 Key Data Scenarios for Big Data Governance Prepare Understand context to extract, cleanse, integrate and monitor data properly to increase integrity and trustworthiness for subsequent usage Capabilities to Consider The Risk is Real Highly scalable data integration Define terms and policies Data cleansing Quality dashboarding Rich annotation
  • 13. © 2014 IBM Corporation13 Capabilities to Consider Maintain data lineage Data quality dashboarding Master data management Make decisions on untrusted information Defend Build confidence in information by making it defensible against challenges The Risk is Real 1 in 3 Key Data Scenarios for Big Data Governance
  • 14. © 2014 IBM Corporation14 Capabilities to Consider Secure data at rest and in motion Data masking Governed data retention Test data management Governance reporting $200 million just to replace cards! Secure and Comply Protection of data privacy and access; compliance with data security and other regulatory requirements The Risk is Severe Key Data Scenarios for Big Data Governance
  • 15. © 2014 IBM Corporation15 Organizations rated their decision making as 7 or higher on a scale of 1 to 10 4 out of 5 Organizations are improving at 3 times the rate of competitors 3X Of organizations show high or very high levels of trust 77% Source: The Big Data Imperative: Why Information Governance Must Be Addressed Now, Aberdeen Group, Dec 2012 IBM Big Data Governance Offers a Golden Opportunity
  • 16. © 2014 IBM Corporation16 All Hadoop Vendors Talk About Their Big “Data Lake”. ONLY IBM Delivers Consumable Big Data From The Swamp. Clean Hadoop LakeHadoop Data Swamp IBM Big Data Governance–including quality, security, and data lineage– transforms your Hadoop Data Swamp to a consumable Big Data Lake.
  • 17. © 2014 IBM Corporation17 A Complete Big Data Solution Is More Than Just An Engine © 2013 IBM Corporation IBM Teradata Pivotal INFA Cloudera Horton Hadoop Distribution  Horton     Hadoop Available via Appliance     ORCL & HP Teradata Hadoop SQL Engine  Postgre     Streaming Data     Flume/ Storm Flume/ Storm Data Exploration Tools       Enterprise Reporting       Data Provisioning Tools  IBM, INFA   Scripting Talend Security Monitoring  Protegrity     ELT, ETL & Replication  IBM, INFA    Talend Metadata & Lineage  Revelytix     Profile & Cleanse (native)  IBM, INFA    Talend Hadoop Matching (native)  IBM, INFA     Reference Data Mgmt.       Data Masking on Hadoop  IBM, INFA     Archiving on Hadoop      
  • 18. © 2014 IBM Corporation18 Reduces reporting time from 2 to 3 days to minutes “The IBM analytics solution greatly improves our ability to define and monitor business KPIs, and it brings much greater transparency to reporting. We now have a single version of the truth and a single comprehensive report for each topic.” — Irfan Zafar, Chief Technology Innovation Officer and Senior General Manager of Customer Services, Sui Southern Gas Company Limited Enables timely analytics combining real-time operational and geographic data from over 5000 sources Single source to information that is reliable and provides better clarity into the supply chain Chemicals & Petroleum, Energy & Utilities The transformation: Deployed an analytics solution that overlays digital maps with real-time operational and financial data, enabling SSGC to analyze data in a real-world context. IBM Software–Information Management Sui Southern Gas Company Mitigates Business Risk Through Insights Into Supply and Demand
  • 20. © 2014 IBM Corporation20 Legal Disclaimer • © IBM Corporation 2014. All Rights Reserved. • The information contained in this publication is provided for informational purposes only. While efforts were made to verify the completeness and accuracy of the information contained in this publication, it is provided AS IS without warranty of any kind, express or implied. In addition, this information is based on IBM’s current product plans and strategy, which are subject to change by IBM without notice. IBM shall not be responsible for any damages arising out of the use of, or otherwise related to, this publication or any other materials. 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