data governance - turning data into insight - ken jacquier
TRANSCRIPT
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 1/43
© 2013 International Business Machines Corporation
Minnesota Digi tal Governm ent Summ it
Data Governance –
Turning Data into Ins ight
July 31, 2013
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 2/43
2© 2013 International Business Machines Corporation
Data Governance – Turning Data into Insight
While we know that the velocity, variety and volumeof data continues to increase, do we really knowhow to handle it and what to do with it? This sessionwill look at implementing enterprise datagovernance including a look at the structure of datagovernance as well as some of the technologies -that can help answer questions we never thought to
ask and provide proactive solutions to problems wenever before thought could be solved.
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 3/43
3© 2013 International Business Machines Corporation
Sustainable success turning structured data into insights has
required a focused Information Governance program
Maintaining and improving Data Quali ty is
funded as cr i t ica l cont inuous improvement
co re to innovat ion and leveraging
investments fo r greatest value
People Process Technology
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 4/43
4© 2013 International Business Machines Corporation
Information Governance Structure to support
continuous improvement
DefineService or Program
Opportunity
ObtainExecutive
Sponsorship
ConductMaturity
Assessment
BuildRoadmap
EstablishOrganization
Blueprint
BuildBusinessGlossary
UnderstandData
CreateMetadata
Repository
DefineMetrics
Govern
LifecycleManagement
Govern
Security &Privacy
Govern Analytics
MeasureResults
= Mandatory
= Optional
Govern
Master DataManagement
Govern DataQuality
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 5/43
5© 2013 International Business Machines Corporation
Barriers to sustaining Information Governance:Where do we recommend you get started?
DefineService/Program
Opportunity
ObtainExecutive
Sponsorship
BuildRoadmap
EstablishState’s
OrganizationBlueprint
DefineMetrics
MeasureResults
= Mandatory
= Optional
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 6/43
6© 2013 International Business Machines Corporation
Define business problem
Information Governance Programs sustain value byfocusing on specific challenges
Need for better customer-centricity
Failed audit
Data breach
Risk due to poor quality or lack of trust of information
High expenditure managing and storing information
Inconsistent view of informationdepending on the system
This can be one problem aligned to a sponsor with funding
This can be a group of government problems with
documented business value where Data Quality is a critical enabler to success.
Current trend is to make Information Governance and Data Quality a core segment of an approved andfunded project; this is often a particular, measureable functionality such as data profiling.
Once the Information Governance program builds momentum with quick wins, it is important to make
the program a yearly line item in funding cycle This is the ultimate validation that the State
understands that information is an asset and must be managed as program and not a project.
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 7/437
© 2013 International Business Machines Corporation
Questions from Legislature
How many children under 15 also have children utilizing our services? How many people over 100 years of age receive benefits?
How many indigenous people receive income support payments?
Data Profiling by Business Intelligence department
Several one-year old children also had children
Number of people over 100 years of age exceeded the number of peoplefrom the national census
The percentage of indigenous people receiving income supportpayments was significantly lower than the average population
Outcomes
Focus on Date of Birth and Race as critical data elements People creating the situation (front office) were not the people
consuming the data (Business Intelligence)
Example of State Information Problem: Social Services Agency
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 8/438
© 2013 International Business Machines Corporation
Step 12: Securi ty and Privacy at Child Welfare Agency (Case Stud y)
The department received a complaint from a relative who cared for a family member’schild.
On numerous occasions she requested that her home address, telephone number andother details about the child remain private. The complainant was concerned about thechild’s parents’ criminal history, violence and drug use.
The complainant’s address details were included in documentation and sent to the
child’s parents by the department. As a result, the complainant moved house becauseof safety concerns. She complained to the department which provided her with somefinancial assistance as a result of the move.
The complainant requested that her new address be recorded as ‘withheld’ by thedepartment. However, the department failed to comply with this request.
The department subsequently sent documentation to the child’s parents which includedthe complainant’s new address details as well details concerning the child. Thecomplainant requested compensation to cover the cost of insurance and securitymeasures for her home, as well as increased rental costs.
The complainant’s payout was then reassessed and she was provided with a higher level of compensation.
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 9/439
© 2013 International Business Machines Corporation
Obtain Executive Sponsorship
Create virtual teams and a vision for Data Stewardship
Obtain support from senior management (front and back office)
Identify an owner for Information Governance
Are you ready for this to be a Chief Data Officer ?
Federal Reserve Board- Chief data officer since May 2013
9
Obtain execut ive sponso rship for Information Gov ernance
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 10/4310
© 2013 International Business Machines Corporation
Sample Information Governance Metrics – Provid ers with in a Healthcare Syst em
Organization Business Drivers KPI
NetworkManagement
MedicalInformatics
Ensureappropriatephysiciancoverage for members (e.g.,50% of memberswith chronic
diseases need tobe situated near a Medical Home)
Conductappropriateprovider analytics
Fraud analytics
Poor MedicaidData
PCMH – Collectdata from 30Sites (50% of members need tobe near PCMH)
% of physicians with inaccurate ZIP_CODE
% of physicians with null state license number,Medicare number, Medicaid number, DEA number
% of providers with incorrect address, phone number and email address (change in office manager)
% of providers with the correct information regardingqualified services they can provide
% of providers with missing Primary Care Physician(PCP) data related to Pay for Performance
Number of provider duplicates
% of providers with missing attributes that are using for matching (e.g., Date of Birth)
Number of providers who have been sanctioned but
now show up in a new group as a new provider (fraudanalytics)
% of physicians incorrectly mapped to the wrongphysician group
“We update physician credentials every three years.”
“The Medical Informatics team relies on accurate physician
data but the responsibility for keeping that data up-to-datefalls on the Network Management team.”
“We have a number of dead physicians in our network.”
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 11/43
11© 2013 International Business Machines Corporation
Build a roadmap-sample roadmap based on initiatives
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 12/43
12© 2013 International Business Machines Corporation
Balancing Information Strategywith just diving in and doing the hard work
Dead people in the system
Appropriate provider analytics - Medicare
Citizens with missing attributes such as date of birth
Current address of citizen- People move!!!
Speed to address state’s leadership teams queries
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 13/43
13© 2013 International Business Machines Corporation
Information Governance Structure to support
continuous improvement
DefineService or Program
Opportunity
ObtainExecutive
Sponsorship
ConductMaturity
Assessment
BuildRoadmap
EstablishOrganization
Blueprint
BuildBusinessGlossary
UnderstandData
CreateMetadata
Repository
DefineMetrics
Govern
LifecycleManagement
Govern
Security &Privacy
Govern Analytics
MeasureResults
= Mandatory
= Optional
Govern
Master DataManagement
Govern DataQuality
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 14/43
14© 2013 International Business Machines Corporation
Sustainable success turning structured data into insights has
required a focused Information Governance program
Info rmat ion pro cesses are managed as an
enab ler o f Strategic Ini t iat ives sim ilar to
Supply Chain p rocesses
People Process Technology
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 15/43
15© 2013 International Business Machines Corporation
Information is not just back office IT databases but a SUPPLY CHAIN
Analyze
Integrate
Manage
ExternalInformationSources
Cubes
Streams
Big DataMaster
Data
Content
DataStructured &Unstructured
Streaming
Information
Quality
Security &Privacy
Lifecycle
Warehouse
Standards
Transactional& Collaborative Applications
Content
Information
Governance
ODS
Data Model
IBM Big Data Platform
SystemsManagement
ApplicationDevelopment
Visualization& Discovery
Accelerators
HadoopSystem
StreamComputing
DataWarehouse
Information Integration & Governance
Business Analytics Applications
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 16/43
16© 2013 International Business Machines Corporation
Realizing new opportunities- Requires harnessing non-traditional data sources…
Transactional &
Application Data
Machine Data Social Data
Volume
• Structured
• Unstructured
• Throughput
Velocity
• Semi-structured
• Ingestion
Variety
• Highly unstructured
• Veracity
Publications
and Research
Variety
• Highly unstructured
• Volume
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 17/43
17© 2013 International Business Machines Corporation
Comprehensive Vision for Integration & Governance
Internal App Data
DataWarehouse
TraditionalSources
Structured
Repeatable
Linear
Transaction Data
ERP data
Mainframe Data
OLTP System
Data
HadoopStreams
NewSources
Unstructured
Exploratory
Iterative
Web Logs
Social Data
Text & Images
Sensor Data
RFID
DataWarehouse
HadoopStreams
TraditionalSources
NewSources
InformationIntegration &Governance
17
D t E l ti d I f ti G
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 18/43
18© 2013 International Business Machines Corporation
Find, visualize and
understand all big data to
improve business
knowledge
Shorter cycles to
sustainable InformationGovernance
• Greater efficiencies in
business processes
• Develop new business
models with resultingincreased market
presence and revenue
CM, RM, DM RDBMS Feeds Web 2.0 Email Web CRM, ERP File Systems
Connector Framework
App Builder
BigInsights
Integration & Governance
UI / User
Streams
Data Exploration and Information Governance-
Understanding your structured and unstructured data
WarehouseData Explorer
Eff i i d I t i I t t i I f t i L i f l
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 19/43
19© 2013 International Business Machines Corporation
Current
Production
Historical
Retrieve
Retrieved
Universal Access to Application Data
Application Application XML ODBC / JDBC
Eff ic iency and Innovat ion- Investments in your Information L i fecycle
prov ide cost savings to support an imp roved Inform ation Supp ly Chain
Archives
Reporting
Data
Historical
DataReference
Data
Archive
Optim
Mashup
Archiving is an intelligent process for moving inactive or infrequentlyaccessed data that still has value , while providing the ability to search and
retrieve the data
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 20/43
20© 2013 International Business Machines Corporation
Information Integration and Governance
Understand, Improve, and Act upon Insights from all your Data
Understand Improve Act
• Discover / profile data
• Determine usagepolicies
• Filter unnecessary databefore integrating
• Derive entity context
• Improve data quality
• Master data• Secure and protect
sensitive data• Manage data lifecycle
• Integrate data
• Information as a service• Define policies to share
and act upon insights
Understand databefore analyzing it
Trust and protectwith appropriate
governance levels
Integrate and act oninsights appropriately
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 21/43
21© 2013 International Business Machines Corporation
Your Information Governance journey must expand to include
structured and unstructured data
Information IsUnderstood
Information isCorrect
Information is Current Information isSecure
Information isHolistic
Information is Shared
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 22/43
22© 2013 International Business Machines Corporation
Foundational
• What happened?
• When and where?
• How much?
Advanced, Predictive
• What will happen?
• What will be the impact?
• Dashboards
• Clinical data repositories
• Departmental data marts
Data integration
Data warehouse
• Basic reporting
• Spreadsheets
Transaction
reporting
• Enterprise analytics
• Evidence-based medicine
• Outcomes analytics
Decision support
analytics
• Personalized services & care
• Engaged citizens
• Population behavior
Predictive
analytics
Cognitive
• What are potential scenarios?
• What is the best course?
• How can we pre-empt andmitigate the crisis?
22
The Journey to Turn Data into Insights-
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 23/43
23© 2013 International Business Machines Corporation
Q & A
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 24/43© 2013 International Business Machines Corporation
THANK YOU
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 25/43
25© 2013 International Business Machines Corporation
APPENDIX
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 26/43
26© 2013 International Business Machines Corporation
INNOVATION
See speaker notes
Establishing a solid integrated unified IM platform
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 27/43
27© 2013 International Business Machines Corporation
BI /Reporting
Exploration /Visualization
Functional App
Industry App
Predictive Analytics
Content Analytics
Analytic Applications
IBM Big Data Platform
Systems
Management
Application
Development
Visualization
& Discovery
Accelerators
Information Integration & Governance
HadoopSystem
StreamComputing
DataWarehouse
Volume, Variety
InfoSphere BigIns ights
QUERYABLE ARCHIVE
UNSTRUCTURED DATA
VelocityInfoSphere Streams
REAL-TIME
STREAMING ANALYTICS
VisibilityInfoSph ere Data Explo rer
DATA DISCOVERY
VolumeDW Appl iances
STRUCTURED DATA
ANALSIS
VeracityIBM InfoSphere
MATCHING, SECURING
DATA SETS
Identifying Patients-at-risk, Cost of Care, Govtmandatd metrics, Next
Best Action……
AcceleratorsData Models, Social andMachine Data
Establishing a solid, integrated, unified IM platform
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 28/43
28© 2013 International Business Machines Corporation28
Sample Master Data Governance Sco recard
Data Governance Metrics Goal Oct
2011
Sept
2011
Aug
2011
July
2011
June
2011
May2011
(Baseline)
1.Percentage of customer duplicates 5% 9% 10% 11% 12% 13% 14%
2.Percentage of non-validated emailaddresses
3% 4% 5% 7% 7% 8% 14%
3.Percentage of non-validated phone numbers 12% 12% 14%
15%
18%
21%
23%
4.Percentage of incorrect SSNs 8% 10% 10%
11% 11% 12%
15%
5.Percentage of non-validated mailing address 2% 6% 8% 12%
15%
18%
22%
Establish the Data
Governance baselineEstablish the critical data elements
with the Data Governance Council
Establish the Data Governance
acceptable threshold or goal with the
Data Governance Council
Report monthly progress to the Data Governance
Council. The Data Governance Lead should circulate
these metrics to the data stewards to monitor
ongoing performance.
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 29/43
29© 2013 International Business Machines Corporation
Government L eaders Movin g to A ddress These Chal lenges
Optimized veteran claims
adjudication, single view of vet
Greatly enhance veterans care US Veterans
Administrat ion
Automated content extraction, entityresolution and analysis from seized
assets
Child Predator Investigation Western National
Law Enforcement
Connect the dots, predict and
prevent threatsProtect The Nation Department o f
Homeland Securi ty
Robust automated enterprise
financial reportingGreatly enhance budget
planning & Execution
US Missi le
Defense
Advanced citizen and benefits
analyticsGreatly enhance citizen service,
and improved outcomes US Medicare
Shared citizen data across multipledepartments, geographies
Greatly enhanced citizenservice, and improved Western European Gov’t Social
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 30/43
30© 2013 International Business Machines Corporation30
Social Services Smarter Service imperatives
“How can I ensure that limited
resources are going to thosewho qualify?”
• Provide analytics to improveeligibility determination and on-goingcase management
“How can I achieve better
outcomes by optimizing the
programs offered?”
• Gain insight into the impact of various programs and the mix of programs that are driving the greatestsuccess
“How can I make it easier for
our clients to interact with our
Agency?”
“How can I better job
detecting and deterring
fraudulent activities”
• Know who’s who and whoknows who
• Identify individuals sharinghouseholds
• Identify clients who do notmeet current eligibility rules.
“What tools can I use today to
help caseworkers prioritize and
manage workload”
• Provide a consolidated view of information about the client and family
• Provide alerts to focus the knowledgeworker on key activities that must becompleted.
• Provide multi-channel accessto client/program information• Have a common identifier torecognize the clients across allthe programs
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 31/43
31© 2013 International Business Machines Corporation
Smarter Soc ial Services Delivery
Gain a HolisticView of Client &
Family
Improve Efficiency
ThroughStreamlined Case
Management
Reduce Fraud, Abuse and Errors
Measure, Monitor
and AnalyzePrograms
Performance and
Client Outcomes
Provides Social Services agencies with a means to improve effectivenesswhile at the same time reducing fraud and waste. The solution:-- Provides a holistic view of client and family-- Streamlines case management-- Reduces fraud, abuse, and errors-- Measures, monitors and analyzes program performance
Solution Definition
Aligns to Key Citizen Needs and Improves Agency Efficiency
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 32/43
32© 2013 International Business Machines Corporation
Tax Agency Compliance Imperatives
“How do I simplify and enhance
the taxpayer experience?”
• Intelligent access to relevant taxcode, forms and “account “ status.
• Single view of taxpayer across allchannels and touchpoints
• Straightforward taxpayer service
“How do I reduce underpaymentand fraud?”
• Enhanced taxpayer guidancethrough statistical analysis
• Enhance identity and householdinganalysis
• Better information sharing acrossthe federal ecosystem (e.g, SSA)
“How do I optimize
collection & compliance”
• Business performancemanagement & executive
dashbaoaring
How do I improve my Audit efficiencyand effectiveness
• Predictive analytics to identify anomalousbehavior
• Identity resolution to identify who is who,and how knows who
• Base management for more efficientaudit adjudication
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 33/43
33© 2013 International Business Machines Corporation
Clark County Family Services Increases Visibility, Productivity andCompliance
CCFS used IBM Business Analytics software to streamline case management andreporting practices, which increased visibility and productivity while improving its abilityto justify funding of targeted case management activities
“ In light of a fast -growing state populat ion and strugg l ing economic cl imate, we were able to not o nly boo st our qual i ty of serv ice, but also generate abou t $4 mi l l ion in new revenue. The IBM solut ion, wi th i ts abi l i ty to help ident i fy bot t lenecks and impro ve business proc esses, was inst rum ental in these successes – so m uch so that other coun ty depar tments are now implement ing the solution and mirroring our BI infrastructure.”
Eboni Washing ton, QA/QI Superv isor,
Fami ly Serv ices Department , Clark Coun ty
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 34/43
34© 2013 International Business Machines Corporation
Audit Information Logging
and Reporting
Classification and Metadata(C&M)
Data Architecture
Data Quality Management
(DQM)
Data Risk Management
(DRM) and Compliance
Information Lifecycle
Management (ILM)
Information Security and
Privacy
Organizational Structures
and Awareness
Policy
Stewardship
Value Creation
Initial Repeatable Defined Managed Optimizing
Assess current state Determine future staterequired capabilities Develop roadmaps
Inform ation Governance for Government Agency
Priority
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 35/43
35© 2013 International Business Machines Corporation
© 2013 IBM Corporation
Organizations rated their decision making as 7 or
higher on a scale of 1 to 10.
4 out of 5Organizations are improvingat 3 times the rate of
competitors.
3X Organizations show high or
very high levels of trust77%
Source: The Big Data Imperative: Why Information Governance Must Be Addressed Now, Aberdeen Group, Dec 2012
There is a Golden Opportunity – If We Govern Information
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 36/43
36© 2013 International Business Machines Corporation
Information Integration and Governance Platform
Information Integration and Governance
Metadata, Business Glossary and Policy Management and Entity Analytics
Privacy &Security
DataLifecycle
Management
InformationIntegration
Master DataManagement
DataQuality
• Extract, Transform,Load
• Replicate• Federate
• Standardize
• Validate
• Verify• Enrich
• Match
• Master multipledomains
• Registry or transaction hub
• Collaborativelyauthor
• Govern master data
• Database Archiving
• Test data
management
• Activity monitoring
• Masking
• Encryption• Redaction
• Automated data discovery
• Enterprise metadata repository• Business terminology defined in business glossary
• Define, share and execute information governance policies
• Information Governance project blueprints
• Incremental context accumulation
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 37/43
37© 2013 International Business Machines Corporation
Make decisions onuntrusted information1 in 3
60%
Don’t have necessaryinformation1 in 2
Time spent on project tounderstand information40%
Have more data than theycan use
60%
More Data, Less ConfidenceIncreasing Volume, Variety, and Velocity makes it harder to establish veracity
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 38/43
38© 2013 International Business Machines Corporation
3838
To ensure the econom ic health, welfare and secu r i ty of th eir
citizens, smart governments are working to…
STRENGTHEN SECURITY AND PUBLIC SAFETY
Enabling defense and law enforcement organizationsto achieve situational awareness, increased speed of command and combat superiority.
MANAGE RESOURCESEFFECTIVELYLeveraging businessintelligence and planning toimprove insight and elevate
performance with visibility
and control.
IMPROVE CITIZEN ANDBUSINESS SERVICES
Connecting people to programs based on
individual needs—
achieving sustainableoutcomes while reducing
operational costs and maximizing taxpayer value.
ENSURE A SUSTAINABLEENVIRONMENT
Deploying environmentally responsible operations,
from energy efficiency and conservation to
transportationmanagement and the
pursuit of renewable resources.
GOVERNMENT
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 39/43
39© 2013 International Business Machines Corporation39
Puerto Rico Treasury Dept. (Hacienda)
Challenge
Solution
• Data intake was increasing 300% annually
• Storage Costs were getting out of control
• Application performance was beingdegraded by the processing the increasingamounts of data
IBM Optim Data Growth Solut ion
• Reduce Costs associated with Data Growth
• Improve performance of overworked productionapplications
• Store data in an immutable format for audit anddiscovery purposes
Saved $2 Million in storage and CPU costs bymoving data off of the primary processingenvironment
Allowed the Treasury Dept. to continuallyarchive data to deal with the 300% annual
increasesReduced the batch processing windows for
payroll and financial reporting, allowing criticaldeadlines to be met.
Benefits
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 40/43
40© 2013 International Business Machines Corporation40
Georgia Dept of Labor
Challenge
Solution
• Secure data associated with UnemploymentInsurance benefits in test/developmentenvironments
• Reduce the amount of storage required for testing
• Improve time to launch of applicationimprovements
IBM Optim Data Privacy Solut ion
IBM Optim Test Data Management Solution
• De-identify/mask data in non-productionenvironments
• Improve time-to-market for new/upgradedapplications
• Reduce storage costs in test/developmentenvironments
Risk of sensitive data loss from non-productiondata breach has been mitigated
Storage investments can be deferred due toreduction in space required to store test data.
Reduction in time/costs to fix errors found in
the development cycle.
Benefits
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 41/43
41© 2013 International Business Machines Corporation41
Challenges
Criminal investigations were inaccurate and inefficientdue to information being spread across boroughs
Manually leverage existing investments in criminal investigations
Difficulty analyzing and synthesizing information
Inability to get information to the right people
Comprehensive Threat Prediction & Solution
IBM InfoSphere Entity Analytic Solutions, Global NameRecognition , Information Server
IBM Crime Information Warehouse
SPSS Predictive Analytics and Cognos Dashboarding
Benefits
Real time “Connect the Dots” investigative capability
Straightforward and intuitive visualization and link analysis
Sophisticated predictive analytics supports resource optimization
Crime analysts are able to spend time on proactive crime analysisrather then data manipulation
New York Police Department RTTC
Alameda County Social Services closes service gaps through better
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 42/43
42© 2013 International Business Machines Corporation
“This is a tool that will tell us
where things really are and how
they are doing, every day.”
— Don Edwards, assistant
agency director,
Alameda County Social Services
y g p guse of information
Gaining a deeper insight into case and program status
The Need:
Faced with new regulations requiring better welfare case outcomes, AlamedaCounty Social Services needed to gain a better understanding of case status andprogram performance. It needed to give its caseworkers direct access toinformation about their own cases, at the individual case level, and needed faster and better reporting.
The Solution:
Alameda County engaged IBM to develop an information system that combinesentity analytics with business intelligence to give a comprehensive view of individual cases. Known as the Social Services Integrated Reporting System(SSIRS), this data warehouse allows the county to not only track benefitrecipients, but also recognize and understand the complex relationships betweenclients and programs.
What Makes it Smarter:
A near real-time view of cases gives workers deeper insight, enabling serviceflexibility, avoiding regulatory sanctions and saving money by reducing fraud andwaste – such as payment to individuals who are no longer eligible for assistance.
Enables direct savings of over US$11 million through waste reduction.
Generates reports in minutes instead of weeks or months – allowingcaseworkers to apply their expertise by trying “what if” scenarios.
7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier
http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 43/43
Information Integration & Governance Must Scale, Handle Complexityand be Adaptive
Scale to Handle the DataExplosion
• Integration performance andscalability
• Lifecycle management toretire data
• Automation and intelligence
Understand Data DespiteComplexity
• Rapidly understand data
• Business-drivengovernance
• Automatically derive context
Provide Agility for Faster Deployments
• Act with confidence oninsights
• Adaptive and alwaysavailable - capabilities
embedded in consuming app
Sources Consumers