Big Data, Data Analytics, and Data Visualization building your knowledge and expertise. September 15, 2015

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Patrick Gaines
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1 + Big Data, Data Analytics, and Data Visualization building your knowledge and expertise September 15, 2015

2 Today s Agenda 2! Kickoff: Glossary of Terms! Data analytics! Data visualization! Big Data! Body of Knowledge Framework a path to excellence! Auditing of Big Data / Auditing with Big Data! Case Studies (Carolinas HealthCare System, Experis, TIAA-CREF)! Visual Reporting Primer! Closing Panel

3 Data Analytics definition(s) 4! ACFE the practice of assessing bodies of data to identify potential indicators of fraud! IIA is the process of identifying, gathering, validating, analyzing, and interpreting various forms of data within an organization to further the purpose and mission of internal auditing! ISACA is the application of emerging statistical, processing, and analytics techniques for the purpose of advancing the business! Wikipedia the process of inspecting, cleaning, transforming, and modeling data with the goal of highlighting useful information, conclusions, and supporting decision making! Thomas Davenport (Harvard professor and data analysis consultant) see following slide

4 Data Analytics definition(s) from: Thomas Davenport s Analytics at Work 4 Past Present Future Information What happened? What is happening now? What will happen? Data Analysis as reporting Data Analysis as alerts Data analysis as extrapolation Insight How and why did it happen? Data analysis as modeling / design What s the next best action? Data analysis as recommendation (value add) What s the best / worst that can happen? Data analysis as prediction / simulation Source: Thomas Davenport Analytics at Work

5 Data Visualization from: Stephen Few Show me the Numbers 5 Time Series Ranking Part to Whole Deviation Distribution Correlation Geospatial Nominal Comparison (e.g. East, Central, West)

7 If your Company is investing in Big Data, should you audit that initiative? Why? How? 7 We ll hear more from Paresh on this Quick Audit program is as follows What are we trying to do? What are the risks to our success? Security and Privacy Compliance Customer loyalty How will we measure success? Any unintended consequences?

8 Body of Knowledge for Audit Data Analytics (adapted from APRA) 8 Project Management Data Acquisition and Manipulation Statistical Techniques Visual Reporting Techniques Communication (Audit and Compliance) Domain Expertise Change Management / Strategic Thinking All of these skills are needed for a successful data analytics effort. It s very rare to find all of these skills in one individual.

9 Next up Carolinas HealthCare System 12 Mitigating User Access Security & Identity Management Presented by James Kidwell and Tom Valiquette

10 Next up Citra Advisors 13 Assessing Risks and Auditing Big Data Initiatives Presented by Paresh Patel

11 Next up Experis 14 Project Management Considerations for Data Analytics Presented by Patricia Rowlett

12 Next up Visual Risk IQ 15 Picture This: Visual Reporting Fundamentals Presented by Joe Oringel

13 Next up TIAA-CREF 16 Our Data Analytics Journey, Methodology, and More Presented by Brian Karp

14 Next up Closing Panel 17

Auditing Application User Account Security and Identity Management with Data Analytics

Auditing Application User Account Security and Identity Management with Data Analytics James Kidwell, JD, CISA Senior Information Systems Auditor Audit Services Session Agenda and Learning Objectives Brief