SlideShare une entreprise Scribd logo
1  sur  19
3/27/2014 1
Social Security
Administration
Herb Strauss
Assistant Deputy Commissioner
for Systems and Deputy CIO
Social Insurance in the Age of Big Data
March 26, 2014
The Mayflower Hotel, Washington, D.C.
Key Topics
2
1. About Your SSA – What We Do In Public Service
2. Social Insurance – In an Age of Big Data
3. Charting SSA’s Path in Big Data – Becoming a More Data-driven
Enterprise
Deliver Social Security services that meet
the changing needs of the public
MISSION
Provide the highest standard of considerate
and thoughtful service for generations to come
VISION
SSA Mission and Vision
3
SSA Benefits and Services
( C o r e W o r k l o a d s )
 Issue Social Security Numbers and
Cards
 Verify Eligibility
 Accept, Verify, Process and Correct
Earnings Information
 Accept Application for Benefits
 Verify Identity
 Determine Entitlement
 Determine Benefit
 Pay Beneficiary
 Verify Continued Entitlement
 Accept Application for Benefit Payment
 Verify Identity
 Determine Non-Medical Eligibility
 Determine Medical Eligibility
 Determine Payment
 Pay Beneficiary/Recipient
(Under Disability/SSI Program)
 Verify Continued Eligibility
 Accept Application for Insurance
Coverage
 Verify Identity
 Determine Eligibility
 Determine Low Income Subsidy
Eligibility
 Collect Insurance Premium
 Accept Application for Payment
 Verify Identity
 Determine Eligibility
 Determine Payment
 Pay Recipient
 Verify Continued Eligibility
Supplemental Security Income
EarningsEnumeration
Disability
Medicare
Retirement and Survivors
4
 Provide Data Exchange
 Verify SSNs
Data Sharing
 Conduct Hearings and Appeals
 Validate Program Integrity
Other
Where We Are
Field Offices
1,220
Teleservice
Centers
30
Disability
Determination
Services
54
National
Hearing
Centers
5
5
Hearings
Offices
162
Regions
10
Foreign
Offices
21
About 1 in 4 households
receives income form
Social Security:
 36.9 million retired
workers
 8.8 million disabled
workers
 4.3 million widows and
widowers
 2.4 million spouses
 1.0 million adults
disabled since
childhood
 3.4 million children
Last year, SSA paid over $850
billion to almost 63 million
people for Social Security
benefits, in one of three
categories:
Retirement insurance
Survivor insurance
Disability insurance
6
SSA Benefits America
 SSA handled over 53 million transactions on our
National 800 Number Network;
 Received over 68 million calls to field offices
nationwide;
 Served about 43 million visitors in over 1,200 field
offices nationwide;
 Completed over 8 million claims for benefits
and 794,000 hearing dispositions; and
 Completed over 429,000 full medical continuing
disability reviews (CDRs).
7
SSA Connects
with America
WE COLLECT, ANALYZE AND RETAIN AN ENORMOUS AMOUNT OF DATA
THROUGH THESE TRANSACTIONS
SOCIAL INSURANCE IN THE AGE OF
BIG DATA
VOLUME, VARIETY, VELOCITY AND VERACITY
Office of the Deputy Commissioner for Systems
and Chief Information Officer
8
Big Data?…Analytics?
Big Data Analytics
The use of data and related
insights developed through
applied disciplines (e.g.
statistical, contextual, quantit
ative, predictive, cognitive
and other models) to drive
fact-based
planning, decisions, execution
, management, measurement
and learning. Analytics may
be descriptive, predictive or
prescriptive.
9
High-volume, high-
velocity and high-variety
information assets that
demand cost-
effective, innovative
forms of information
processing for enhanced
insight and decision
making.
Volume, Variety, Vel
ocity, Veracity
10
Data Is Growing
Exponentially
Along With Demand to Use It
Transactional Data
Documents
Video
Text
Audio
Images
IT/OT
11
ENTERPRISE ELEMENTS
Blended IT Workforce: 4,000
Databases: IDMS, DB2, Oracle
Data Stores: 24 Petabytes
Software Applications: 700
BI Architecture/Big Data Lab
Computing Platforms:
• Mainframe Servers
• Mid-range Servers
• Commodity x86 Servers
Network – SSANet
• Eithernet LANs
• MPLS WANs
IT Security- 2 24/7 SOCs
Continuous Monitoring
The SSA Enterprise
“Big Data is in our DNA”
BIG DATA CREATES VALUE
IN SEVERAL WAYS
12
More easily accessible to relevant stakeholders in a timely
manner -- fosters transparency
Enables experimentation
Create highly specific segmentations to customize actions
Improve decision making, minimize risks, and unearth valuable
insights
Innovate new business models and services
Detect and predict fraud and other crimes
CHARTING SSA’S PATH IN BIG
DATA
BECOMING A MORE DATA-DRIVEN ENTERPRISE
Office of the Deputy Commissioner for Systems
and Chief Information Officer
13
Data-driven
Organization
Manage the Data Understand the Data Act on the Data
Information Management Analytics Skills and Tools Data-driven Culture
Mature information
foundation.
Develop analytic skills as a
core discipline.
Fact-driven leadership
Standardize data
management practices.
Enabled by a robust set of
tools and solutions.
Use Analytics as a strategic
asset.
Make insights accessible
and available.
Develop action-oriented
insights.
Data-driven insights guide
strategy and operations.
14
 Map the Business Processes
 Gather Actionable Data
 Analyze and Visualize Data
 Experiment With Analyses
 Improve Heuristics
 Review and Act on Results
15
Enterprise Information: Adopt A
Management Framework
Source: Gartner 2014
Information management competency: The use of
methodologies, techniques and technologies that address data
architecture, extraction, transformation, movement, storage, integration and
governance of enterprise information and master data management.
16
SSA’s Path to
Big Data Transformation
Source: MIT Sloan Management Review. Analytics the Widening Divide Fall, 2011
17
Our Challenge: Balance
Modernization & Transformation
• Big Data and Business Analytics offer SSA new and
enhanced capabilities across our programmatic and
administrative missions.
• Big Data and Business Analytics are transformative –
business-driven -- change management is critical.
• New management methods and thinking are as vital as
tools, techniques and technology investments are in
realizing successful outcomes.
• Recent experiments validate further investment.
• In-house knowledge and experience is nascent; industry
and academe knowhow is vital.
18
Closing Comments
3/27/2014 19
THANK YOU FOR YOUR ATTENTION
YOUR QUESTIONS PLEASE
19
SOCIAL SECURITY ADMINISTRATION
Office of the Deputy Commissioner
for Systems and CIO
6401 Security Boulevard
Baltimore, MD 21235
www.SSA.Gov

Contenu connexe

En vedette

En vedette (20)

SECON'2014 - Андрей Устюжанин - Маленькие секреты больших данных
SECON'2014 - Андрей Устюжанин - Маленькие секреты больших данныхSECON'2014 - Андрей Устюжанин - Маленькие секреты больших данных
SECON'2014 - Андрей Устюжанин - Маленькие секреты больших данных
 
שיטות הסתברותיות תרגול 6
שיטות הסתברותיות תרגול 6שיטות הסתברותיות תרגול 6
שיטות הסתברותיות תרגול 6
 
Юлмарт. История создания, Дмитрий Завалишин (DZ Systems)
Юлмарт. История создания, Дмитрий Завалишин (DZ Systems)Юлмарт. История создания, Дмитрий Завалишин (DZ Systems)
Юлмарт. История создания, Дмитрий Завалишин (DZ Systems)
 
Xtrem n p1560t
Xtrem n p1560tXtrem n p1560t
Xtrem n p1560t
 
ITMO RecSys course. Autumn 2014. Lecture 6
ITMO RecSys course. Autumn 2014. Lecture 6ITMO RecSys course. Autumn 2014. Lecture 6
ITMO RecSys course. Autumn 2014. Lecture 6
 
ИТМО Machine Learning 2015. Рекомендательные системы
ИТМО Machine Learning 2015. Рекомендательные системыИТМО Machine Learning 2015. Рекомендательные системы
ИТМО Machine Learning 2015. Рекомендательные системы
 
ИТМО Machine Learning. Рекомендательные системы — часть 2
ИТМО Machine Learning. Рекомендательные системы — часть 2ИТМО Machine Learning. Рекомендательные системы — часть 2
ИТМО Machine Learning. Рекомендательные системы — часть 2
 
Антон Конушин (НИУ ВШЭ)
Антон Конушин (НИУ ВШЭ)Антон Конушин (НИУ ВШЭ)
Антон Конушин (НИУ ВШЭ)
 
Алексей Натекин (Deloitte)
Алексей Натекин (Deloitte)Алексей Натекин (Deloitte)
Алексей Натекин (Deloitte)
 
Александр Петров (E-contenta)
Александр Петров (E-contenta)Александр Петров (E-contenta)
Александр Петров (E-contenta)
 
Григорий Бакунов (Яндекс)
Григорий Бакунов (Яндекс)Григорий Бакунов (Яндекс)
Григорий Бакунов (Яндекс)
 
Александр Семенов (НИУ ВШЭ)
Александр Семенов (НИУ ВШЭ)Александр Семенов (НИУ ВШЭ)
Александр Семенов (НИУ ВШЭ)
 
NVIDIA Deep Learning.
NVIDIA Deep Learning. NVIDIA Deep Learning.
NVIDIA Deep Learning.
 
Лекция №7 "Машина опорных векторов"
Лекция №7 "Машина опорных векторов" Лекция №7 "Машина опорных векторов"
Лекция №7 "Машина опорных векторов"
 
Лекция №6 "Линейные модели для классификации и регрессии"
Лекция №6 "Линейные модели для классификации и регрессии" Лекция №6 "Линейные модели для классификации и регрессии"
Лекция №6 "Линейные модели для классификации и регрессии"
 
Кадомский Сергей - Как продать аналитику бизнесу - Wargaming
Кадомский Сергей - Как продать аналитику бизнесу - WargamingКадомский Сергей - Как продать аналитику бизнесу - Wargaming
Кадомский Сергей - Как продать аналитику бизнесу - Wargaming
 
Александра Кирсанова "Использование Data mining"
Александра Кирсанова "Использование Data mining"Александра Кирсанова "Использование Data mining"
Александра Кирсанова "Использование Data mining"
 
ITMO RecSys course. Autumn 2014. Lecture 5
ITMO RecSys course. Autumn 2014. Lecture 5ITMO RecSys course. Autumn 2014. Lecture 5
ITMO RecSys course. Autumn 2014. Lecture 5
 
Thorny Path to the Large Scale Graph Processing, Алексей Зиновьев (Тамтэк)
Thorny Path to the Large Scale Graph Processing, Алексей Зиновьев (Тамтэк)Thorny Path to the Large Scale Graph Processing, Алексей Зиновьев (Тамтэк)
Thorny Path to the Large Scale Graph Processing, Алексей Зиновьев (Тамтэк)
 
Григорий Сапунов (eclass)
Григорий Сапунов (eclass)Григорий Сапунов (eclass)
Григорий Сапунов (eclass)
 

Plus de GovLoop

Week Three
Week ThreeWeek Three
Week Three
GovLoop
 
FHWA Week Two
FHWA Week TwoFHWA Week Two
FHWA Week Two
GovLoop
 
Social Media Presentation for The Center for Organizational Effectiveness
Social Media Presentation for The Center for Organizational EffectivenessSocial Media Presentation for The Center for Organizational Effectiveness
Social Media Presentation for The Center for Organizational Effectiveness
GovLoop
 

Plus de GovLoop (20)

How is GovLoop Transforming Learning for Government?
How is GovLoop Transforming Learning for Government?How is GovLoop Transforming Learning for Government?
How is GovLoop Transforming Learning for Government?
 
Teaching vs learning
Teaching vs learningTeaching vs learning
Teaching vs learning
 
Next Gen: Critical Conversations Slide Deck
Next Gen: Critical Conversations Slide DeckNext Gen: Critical Conversations Slide Deck
Next Gen: Critical Conversations Slide Deck
 
Internet of Things: Lightning Round, Sargent
Internet of Things: Lightning Round, SargentInternet of Things: Lightning Round, Sargent
Internet of Things: Lightning Round, Sargent
 
Internet of Things: Lightning Round, Ronzio
Internet of Things: Lightning Round, RonzioInternet of Things: Lightning Round, Ronzio
Internet of Things: Lightning Round, Ronzio
 
Internet of Things: Lightning Round, Hite
Internet of Things: Lightning Round, HiteInternet of Things: Lightning Round, Hite
Internet of Things: Lightning Round, Hite
 
Internet of Things: Lightning Round, Fritzinger
Internet of Things: Lightning Round, FritzingerInternet of Things: Lightning Round, Fritzinger
Internet of Things: Lightning Round, Fritzinger
 
Internet of Things: Lightning Round, McKinney
Internet of Things: Lightning Round, McKinneyInternet of Things: Lightning Round, McKinney
Internet of Things: Lightning Round, McKinney
 
Internet of Things: Government Keynote, Randy Garrett
Internet of Things: Government Keynote, Randy GarrettInternet of Things: Government Keynote, Randy Garrett
Internet of Things: Government Keynote, Randy Garrett
 
Leap Not Creep Participant Guide Pre-Course Through Week 3 - 20140722
Leap Not Creep Participant Guide Pre-Course Through Week 3 - 20140722Leap Not Creep Participant Guide Pre-Course Through Week 3 - 20140722
Leap Not Creep Participant Guide Pre-Course Through Week 3 - 20140722
 
Week Three
Week ThreeWeek Three
Week Three
 
FHWA Week Two
FHWA Week TwoFHWA Week Two
FHWA Week Two
 
Building Powerful Outreach - Executive Research Brief
Building Powerful Outreach - Executive Research BriefBuilding Powerful Outreach - Executive Research Brief
Building Powerful Outreach - Executive Research Brief
 
Turning Big Data into Big Decisions
Turning Big Data into Big DecisionsTurning Big Data into Big Decisions
Turning Big Data into Big Decisions
 
Examining the Big Data Frontier
Examining the Big Data FrontierExamining the Big Data Frontier
Examining the Big Data Frontier
 
The Need for NoSQL - MarkLogic
The Need for NoSQL - MarkLogicThe Need for NoSQL - MarkLogic
The Need for NoSQL - MarkLogic
 
Capitalizing on the Cloud
Capitalizing on the CloudCapitalizing on the Cloud
Capitalizing on the Cloud
 
Build Better Virtual Events & Training for your Agency
Build Better Virtual Events & Training for your AgencyBuild Better Virtual Events & Training for your Agency
Build Better Virtual Events & Training for your Agency
 
Social Media Presentation for The Center for Organizational Effectiveness
Social Media Presentation for The Center for Organizational EffectivenessSocial Media Presentation for The Center for Organizational Effectiveness
Social Media Presentation for The Center for Organizational Effectiveness
 
Guide to Managing the Presidential Management Fellows (PMF) Application Proce...
Guide to Managing the Presidential Management Fellows (PMF) Application Proce...Guide to Managing the Presidential Management Fellows (PMF) Application Proce...
Guide to Managing the Presidential Management Fellows (PMF) Application Proce...
 

Dernier

Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
panagenda
 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
?#DUbAI#??##{{(☎️+971_581248768%)**%*]'#abortion pills for sale in dubai@
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 

Dernier (20)

Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
 
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsMS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectors
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
 
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
 
CNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In PakistanCNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In Pakistan
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challenges
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
 
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptx
 
[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
AXA XL - Insurer Innovation Award Americas 2024
AXA XL - Insurer Innovation Award Americas 2024AXA XL - Insurer Innovation Award Americas 2024
AXA XL - Insurer Innovation Award Americas 2024
 

Social Insurance in the Age of Big Data

  • 1. 3/27/2014 1 Social Security Administration Herb Strauss Assistant Deputy Commissioner for Systems and Deputy CIO Social Insurance in the Age of Big Data March 26, 2014 The Mayflower Hotel, Washington, D.C.
  • 2. Key Topics 2 1. About Your SSA – What We Do In Public Service 2. Social Insurance – In an Age of Big Data 3. Charting SSA’s Path in Big Data – Becoming a More Data-driven Enterprise
  • 3. Deliver Social Security services that meet the changing needs of the public MISSION Provide the highest standard of considerate and thoughtful service for generations to come VISION SSA Mission and Vision 3
  • 4. SSA Benefits and Services ( C o r e W o r k l o a d s )  Issue Social Security Numbers and Cards  Verify Eligibility  Accept, Verify, Process and Correct Earnings Information  Accept Application for Benefits  Verify Identity  Determine Entitlement  Determine Benefit  Pay Beneficiary  Verify Continued Entitlement  Accept Application for Benefit Payment  Verify Identity  Determine Non-Medical Eligibility  Determine Medical Eligibility  Determine Payment  Pay Beneficiary/Recipient (Under Disability/SSI Program)  Verify Continued Eligibility  Accept Application for Insurance Coverage  Verify Identity  Determine Eligibility  Determine Low Income Subsidy Eligibility  Collect Insurance Premium  Accept Application for Payment  Verify Identity  Determine Eligibility  Determine Payment  Pay Recipient  Verify Continued Eligibility Supplemental Security Income EarningsEnumeration Disability Medicare Retirement and Survivors 4  Provide Data Exchange  Verify SSNs Data Sharing  Conduct Hearings and Appeals  Validate Program Integrity Other
  • 5. Where We Are Field Offices 1,220 Teleservice Centers 30 Disability Determination Services 54 National Hearing Centers 5 5 Hearings Offices 162 Regions 10 Foreign Offices 21
  • 6. About 1 in 4 households receives income form Social Security:  36.9 million retired workers  8.8 million disabled workers  4.3 million widows and widowers  2.4 million spouses  1.0 million adults disabled since childhood  3.4 million children Last year, SSA paid over $850 billion to almost 63 million people for Social Security benefits, in one of three categories: Retirement insurance Survivor insurance Disability insurance 6 SSA Benefits America
  • 7.  SSA handled over 53 million transactions on our National 800 Number Network;  Received over 68 million calls to field offices nationwide;  Served about 43 million visitors in over 1,200 field offices nationwide;  Completed over 8 million claims for benefits and 794,000 hearing dispositions; and  Completed over 429,000 full medical continuing disability reviews (CDRs). 7 SSA Connects with America WE COLLECT, ANALYZE AND RETAIN AN ENORMOUS AMOUNT OF DATA THROUGH THESE TRANSACTIONS
  • 8. SOCIAL INSURANCE IN THE AGE OF BIG DATA VOLUME, VARIETY, VELOCITY AND VERACITY Office of the Deputy Commissioner for Systems and Chief Information Officer 8
  • 9. Big Data?…Analytics? Big Data Analytics The use of data and related insights developed through applied disciplines (e.g. statistical, contextual, quantit ative, predictive, cognitive and other models) to drive fact-based planning, decisions, execution , management, measurement and learning. Analytics may be descriptive, predictive or prescriptive. 9 High-volume, high- velocity and high-variety information assets that demand cost- effective, innovative forms of information processing for enhanced insight and decision making.
  • 10. Volume, Variety, Vel ocity, Veracity 10 Data Is Growing Exponentially Along With Demand to Use It Transactional Data Documents Video Text Audio Images IT/OT
  • 11. 11 ENTERPRISE ELEMENTS Blended IT Workforce: 4,000 Databases: IDMS, DB2, Oracle Data Stores: 24 Petabytes Software Applications: 700 BI Architecture/Big Data Lab Computing Platforms: • Mainframe Servers • Mid-range Servers • Commodity x86 Servers Network – SSANet • Eithernet LANs • MPLS WANs IT Security- 2 24/7 SOCs Continuous Monitoring The SSA Enterprise “Big Data is in our DNA”
  • 12. BIG DATA CREATES VALUE IN SEVERAL WAYS 12 More easily accessible to relevant stakeholders in a timely manner -- fosters transparency Enables experimentation Create highly specific segmentations to customize actions Improve decision making, minimize risks, and unearth valuable insights Innovate new business models and services Detect and predict fraud and other crimes
  • 13. CHARTING SSA’S PATH IN BIG DATA BECOMING A MORE DATA-DRIVEN ENTERPRISE Office of the Deputy Commissioner for Systems and Chief Information Officer 13
  • 14. Data-driven Organization Manage the Data Understand the Data Act on the Data Information Management Analytics Skills and Tools Data-driven Culture Mature information foundation. Develop analytic skills as a core discipline. Fact-driven leadership Standardize data management practices. Enabled by a robust set of tools and solutions. Use Analytics as a strategic asset. Make insights accessible and available. Develop action-oriented insights. Data-driven insights guide strategy and operations. 14  Map the Business Processes  Gather Actionable Data  Analyze and Visualize Data  Experiment With Analyses  Improve Heuristics  Review and Act on Results
  • 15. 15 Enterprise Information: Adopt A Management Framework Source: Gartner 2014 Information management competency: The use of methodologies, techniques and technologies that address data architecture, extraction, transformation, movement, storage, integration and governance of enterprise information and master data management.
  • 16. 16 SSA’s Path to Big Data Transformation Source: MIT Sloan Management Review. Analytics the Widening Divide Fall, 2011
  • 18. • Big Data and Business Analytics offer SSA new and enhanced capabilities across our programmatic and administrative missions. • Big Data and Business Analytics are transformative – business-driven -- change management is critical. • New management methods and thinking are as vital as tools, techniques and technology investments are in realizing successful outcomes. • Recent experiments validate further investment. • In-house knowledge and experience is nascent; industry and academe knowhow is vital. 18 Closing Comments
  • 19. 3/27/2014 19 THANK YOU FOR YOUR ATTENTION YOUR QUESTIONS PLEASE 19 SOCIAL SECURITY ADMINISTRATION Office of the Deputy Commissioner for Systems and CIO 6401 Security Boulevard Baltimore, MD 21235 www.SSA.Gov

Notes de l'éditeur

  1. GovLoop -- Examining the Big Data Frontier ConferenceMach 26, 2014The Mayflower HotelWashington D.C.A Presentation by theUnited StatesSocial Security AdministrationHerb StraussAssistant Deputy Commissioner for Systemsand Deputy Chief Information OfficerSocial Security Administration6401 Security BoulevardBaltimore, MD 21235
  2.  
  3. GovLoop -- Examining the Big Data Frontier ConferenceMach 26, 2014The Mayflower HotelWashington D.C.A Presentation by theUnited StatesSocial Security AdministrationHerb StraussAssistant Deputy Commissioner for Systemsand Deputy Chief Information OfficerSocial Security Administration6401 Security BoulevardBaltimore, MD 21235