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Big Data and Smarter
Analytics: What Does it Mean
to Credit Union Executives?
Presented by
David M. Wallace
SAS
Agenda
• Big Data
• Business Analytics
• Visualization: Where Big Data and Business
Analytics Meet
• Where and How: The ‘Sweet Spot’ Areas for
Credit Unions
• Can We Do This?
• Questions
Big Data: What Is It?
VOLUME
VARIETY
VELOCITY
VALUE
TODAY THE FUTURE
DATASIZE
THRIVING IN THE BIG DATA ERA
Big Data: Growth in Volume and Variety
Source: CEB TowerGroup, Gain New Insight from Unstructured Data, 2013.
“…the broad use of data and quantitative analysis for
decision-making within organizations."
Business Analytics: What is It?
Source: Thomas H. Davenport, The New World of Business Analytics, March, 2010
“Business analytics empowers people in the
organization to make better decisions, improve
processes and achieve desired outcomes."
“It brings together the best of data management,
analytic methods, and the presentation of results—all
in a closed-loop cycle for continuous learning and
improvement.”
5 Stages of Analytical Maturity
Source: Thomas H. Davenport, Competing on Analytics
Don’t Be Here
Aim for Here
Evolution of Analytics
Source: Jack Phillips and Tom Davenport, Analytics 3.0: The Era of Impact, International Institute for Analytics, April 2013
Evolution of Analytics
Source: Jack Phillips and Tom Davenport, Analytics 3.0: The Era of Impact, International Institute for Analytics, April 2013
Evolution of Analytics
Source: Jack Phillips and Tom Davenport, Analytics 3.0: The Era of Impact, International Institute for Analytics, April 2013
What Are Advanced Analytics?
Visualization
Visualization: 3 Capabilities
EXPLORATION AND
VISUALIZATION
POWER OF ANALYTICS RAPID DELIVERY OF
MOBILE INSIGHTS
Visualization: Value of Predictive
Analytics
DATA VISUALIZATION ANALYTIC VISUALIZATION
EXPLORATION DISCOVERY
Visualization: Increase Use of
Analytics and BI
• Self-service
• Easy to use Analytics
• Work with more data
• Reporting and Dashboards
• Mobile BI
• Collaboration
FORECAST
Visualization: What Can You Do?
Visualization: For Business and IT
FOR BUSINESS
• Easy-to-use analytics create a starting point for building and
analytics driven culture
• Visual exploration of data, combined with analytics, fuel
insight discovery for competitive advantage
• Rapid delivery of insights to colleagues via the Web and
mobile promote collaboration and fact based decisions
FOR IT
• Control governance and empower colleagues with easy
access to all data
• Leverage a highly scalable environment for cost effective
growth when the business needs it
Why Visualization
with Analytics?
Visualization: Summary
Applying Analytics to Credit Unions
Member
Experience
& Marketing
Risk &
Regulatory
Compliance
Operations
Fraud &
Financial
Crimes
Example: Analytics for Financial
Crimes
Getting Started
10 Practical Steps for Making
Analytics Work
1. Expand the use of business
analytics where feasible.
2. Integrate analytics across
the organization.
3. Deploy analytics on specific
business tasks.
4. Use a variety of analytics
tools, including more
sophisticated ones.
5. Create a data-management
strategy that includes ready
access to data.
6. Deploy the necessary
analytical technology.
7. Develop formal data-
management processes.
8. Secure executive support.
9. Deliver and communicate
value.
10. Hire and develop the right
analytical talent.
Source: Bloomberg Business Week, Making Business Analytics Work: Lessons from Effective Analytics Users, May 2012. n = 930.
4 Keys to Analytical Talent
1. Put talent before technology
– Maximize analytics tool investments by getting talent in place
first
2. Emphasize “soft” skills in addition to technical skills
– Critical thinking and problem solving capabilities
– “ability to deal with the world through an analytical lens”
3. Invest in ongoing staff development
– Training existing employees  creating a fact-based decision
culture
4. Be creative when looking outside for new talent
– Go beyond traditional areas (examples: engineering, math)
– Partner with local universities; tap provider resources
Source: Bank Systems & Technology, 4 Keys to Building an Analytical Workforce, February 2012
What to Look For in a Business
Analytics Solution
• Robust visualization
• Support for advanced analytics
• Prebuilt analytical models and task support
• Suited for range of users
• Ease of use
• Balance of user autonomy and IT control
• Modular
• Fully integrated
• Availability of training and technical support
• Low total cost of ownership
Source: IT Business Edge, You’re Never Too Small for Business Analytics, September 2011
For More Information
• Kristin Locklear –
Kristin.Locklear@sas.com
• Mary Jones – Mary.Jones@sas.com
SAS is the NAFCU Services Preferred Partner for Business
Intelligence, Predictive Analytics Software & Risk
Assessment. Learn more at www.nafcu.org/SAS.
Thank You!
David.M.Wallace@sas.com
Presentation Summary
• Big Data and Smarter Analytics: What Does it Mean to Credit Union
Executives?
• In this session, we will discuss how investment in business analytics and
Big Data solutions can help credit unions achieve data-driven insight. Learn
how technologies like predictive analytics, use of Big Data, and data
visualization can help your CU enhance member relationships and restore
member confidence; improve risk management while rebuilding liquidity and
your overall capital positions; and engage and manage regulators and other
stakeholders in a new era of intense oversight and scrutiny. Also discover
how business analytics can help you reduce operational losses and combat
financial crime while allowing you to identify new ways to drive income and
enhance member value

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SAS Institute: Big data and smarter analytics

  • 1. Big Data and Smarter Analytics: What Does it Mean to Credit Union Executives? Presented by David M. Wallace SAS
  • 2. Agenda • Big Data • Business Analytics • Visualization: Where Big Data and Business Analytics Meet • Where and How: The ‘Sweet Spot’ Areas for Credit Unions • Can We Do This? • Questions
  • 3. Big Data: What Is It?
  • 5. Big Data: Growth in Volume and Variety Source: CEB TowerGroup, Gain New Insight from Unstructured Data, 2013.
  • 6. “…the broad use of data and quantitative analysis for decision-making within organizations." Business Analytics: What is It? Source: Thomas H. Davenport, The New World of Business Analytics, March, 2010 “Business analytics empowers people in the organization to make better decisions, improve processes and achieve desired outcomes." “It brings together the best of data management, analytic methods, and the presentation of results—all in a closed-loop cycle for continuous learning and improvement.”
  • 7. 5 Stages of Analytical Maturity Source: Thomas H. Davenport, Competing on Analytics Don’t Be Here Aim for Here
  • 8. Evolution of Analytics Source: Jack Phillips and Tom Davenport, Analytics 3.0: The Era of Impact, International Institute for Analytics, April 2013
  • 9. Evolution of Analytics Source: Jack Phillips and Tom Davenport, Analytics 3.0: The Era of Impact, International Institute for Analytics, April 2013
  • 10. Evolution of Analytics Source: Jack Phillips and Tom Davenport, Analytics 3.0: The Era of Impact, International Institute for Analytics, April 2013
  • 11. What Are Advanced Analytics?
  • 13. Visualization: 3 Capabilities EXPLORATION AND VISUALIZATION POWER OF ANALYTICS RAPID DELIVERY OF MOBILE INSIGHTS
  • 14. Visualization: Value of Predictive Analytics DATA VISUALIZATION ANALYTIC VISUALIZATION EXPLORATION DISCOVERY
  • 15. Visualization: Increase Use of Analytics and BI • Self-service • Easy to use Analytics • Work with more data • Reporting and Dashboards • Mobile BI • Collaboration
  • 17. Visualization: For Business and IT FOR BUSINESS • Easy-to-use analytics create a starting point for building and analytics driven culture • Visual exploration of data, combined with analytics, fuel insight discovery for competitive advantage • Rapid delivery of insights to colleagues via the Web and mobile promote collaboration and fact based decisions FOR IT • Control governance and empower colleagues with easy access to all data • Leverage a highly scalable environment for cost effective growth when the business needs it Why Visualization with Analytics?
  • 19. Applying Analytics to Credit Unions Member Experience & Marketing Risk & Regulatory Compliance Operations Fraud & Financial Crimes
  • 20. Example: Analytics for Financial Crimes
  • 22. 10 Practical Steps for Making Analytics Work 1. Expand the use of business analytics where feasible. 2. Integrate analytics across the organization. 3. Deploy analytics on specific business tasks. 4. Use a variety of analytics tools, including more sophisticated ones. 5. Create a data-management strategy that includes ready access to data. 6. Deploy the necessary analytical technology. 7. Develop formal data- management processes. 8. Secure executive support. 9. Deliver and communicate value. 10. Hire and develop the right analytical talent. Source: Bloomberg Business Week, Making Business Analytics Work: Lessons from Effective Analytics Users, May 2012. n = 930.
  • 23. 4 Keys to Analytical Talent 1. Put talent before technology – Maximize analytics tool investments by getting talent in place first 2. Emphasize “soft” skills in addition to technical skills – Critical thinking and problem solving capabilities – “ability to deal with the world through an analytical lens” 3. Invest in ongoing staff development – Training existing employees  creating a fact-based decision culture 4. Be creative when looking outside for new talent – Go beyond traditional areas (examples: engineering, math) – Partner with local universities; tap provider resources Source: Bank Systems & Technology, 4 Keys to Building an Analytical Workforce, February 2012
  • 24. What to Look For in a Business Analytics Solution • Robust visualization • Support for advanced analytics • Prebuilt analytical models and task support • Suited for range of users • Ease of use • Balance of user autonomy and IT control • Modular • Fully integrated • Availability of training and technical support • Low total cost of ownership Source: IT Business Edge, You’re Never Too Small for Business Analytics, September 2011
  • 25. For More Information • Kristin Locklear – Kristin.Locklear@sas.com • Mary Jones – Mary.Jones@sas.com SAS is the NAFCU Services Preferred Partner for Business Intelligence, Predictive Analytics Software & Risk Assessment. Learn more at www.nafcu.org/SAS.
  • 27. Presentation Summary • Big Data and Smarter Analytics: What Does it Mean to Credit Union Executives? • In this session, we will discuss how investment in business analytics and Big Data solutions can help credit unions achieve data-driven insight. Learn how technologies like predictive analytics, use of Big Data, and data visualization can help your CU enhance member relationships and restore member confidence; improve risk management while rebuilding liquidity and your overall capital positions; and engage and manage regulators and other stakeholders in a new era of intense oversight and scrutiny. Also discover how business analytics can help you reduce operational losses and combat financial crime while allowing you to identify new ways to drive income and enhance member value