San Francisco Professional Events List

Successful Audit Data Analytics - ITP250

Nov 13, 2017 - 08:30 AM - Nov 15, 03:00 PM
MIS Training Institute
MicroTek Computer Lab SF
655, Montgomery St

San Francisco,
ZIP: 94111

​“Very well organized. I enjoyed the classroom exercises and breakout sessions; great course as my team is starting to think about a Data Analytics program.”
- IT Audit Manager, ING U.S.

In this three-day seminar attendees will learn everything needed about effectively integrating data analytics, or CAATs (Computer Assisted Audit Techniques), into an audit process. You will learn how technology can be used to more efficiently and effectively achieve desired results and brainstorm analytics across most major business cycles. You will learn how to progress from basic analytics into a fully automated/repetitive mode, and learn the basics of Continuous Auditing. We will review common hurdles and hear how the most successful organizations in the world have been able to exploit the power of data analysis to achieve visible and sustainable value.

Whether you are in audit management, directing a team where you may never personally use the technology, or the person who will ultimately be performing data analysis techniques, this seminar provides critical experience. Participants in audit management will learn how to design effective strategies and programs to ensure sustainable results. Those who will play a hands-on role with analytics programs will get the opportunity to work on real-world scenarios with sample data files. Each participant will practice designing effective tests and critiquing and QAing the work of others.

As the course progresses, you will move quickly from understanding basic analytic techniques such as stratifications, summarizations, and duplicate identification into more advanced techniques such as fuzzy matching, Benford’s Law, and statistical and regression analysis. You will explore cutting-edge topics such as visual analytics, risk score carding, and spatial analysis. Regardless of the tool you currently use or plan to use in your department - whether generic like MS Excel or MS Access, audit-centric like ACL or IDEA, or more IT-oriented like SQL or SAS - the standard pseudo-code used throughout the course will allow you to easily take what you have learned and quickly code it in your tool of choice. Participants are encouraged to bring a laptop to practice techniques on real data files using their tool of choice. 

Prerequisite: Fundamentals of Internal Auditing (OAG101)​IT Auditing and Controls (ITG101)​​ or equivalent experience
Advanced Preparation: None
Learning Level: Intermediate    
Field: Auditing
Delivery Method: Group-Live

Who Should Attend

Internal and External Auditors; Audit Managers, Directors, and Executives; IT Auditors, Managers, and Directors; QA personnel; IT Security Managers and Directors; CIOs; Consultants 

CPEs: 24
INSTRUCTOR: Jim Tarantino
LEVEL: Intermediate
Tuition:  $2,595


What You Will Learn​

1. The Business Case for Audit Analytics
• industry benchmarks/guidance
• challenges with traditional audit process
• success stories and common benefits

2. Integrating Data Analytics across the Audit Process
• enterprise risk assessment
• audit planning
• fieldwork and testing
• reporting
• follow-up and monitors

3. Pros and Cons of Common Data Analysis Tools
• MS Office: MS Excel, MS Access
• Excel add-ins: TeamMate Analytics, ActiveData
• audit-centric client/server: ACL, Arbutus, IDEA, InfoZoom
• statistically-based:  SPSS, SAS, R
• IT-centric: SQL, Alteryx, Lavastorm
• business intelligence: Cognos, Business-Objects, PowerBI
• specialized:  SAP
• dashboarding: Tableau, Qlikview, Spotfire, Lumira

4. Analytic Development Cycle
• program strategy and approach
• analytic planning and design
• data access and validation
• coding/development
• testing/QA
• implementation and optimization
• process differences for ad-hoc vs. continuous testing

5. Planning for Data Access
• understanding various data access techniques
• effective negotiation with IT
• data verification procedures
• data security and retention

6. Exploring Data Access Options and File Types
• native database tools
• flat/delimited files
• adobe PDF reports
• unstructured data

7. Common Analyses in Major Business Processes
• Record-to-Report (R2R)
• Purchase-to-Pay (P2P)
• Forecast-to-Stock (F2S)
• Order-to-Cash (O2C)
• Hire-to-Retire (H2R)
• Process-to-Application (P2A)

8. Advanced Analytic Design Techniques
• complex string comparisons
• address comparisons
• fuzzy matching techniques
• trending
• Benford’s analysis
• smarter sampling techniques
• statistical and regression analysis

9. Verifying Standard Data
• employee SSNs
• vendor EINs
• vendor TINs
• zip codes
• area codes
• address abbreviations
• credit card numbers

10. Leveraging External Data Sources
• OFAC list
• US Postal Service address standards
• SIC codes

11. Developing Appropriate Standards
• code documentation
• requirements definition
• data verification
• QA and testing
• security and archiving

12. Making Analytics Repetitive
• scripting and automation
• design considerations
• automating data access

13. Moving towards Continuous Auditing
• strategy considerations
• effect on audit process
• changes to data extraction and analytic logic

14. Common Implementation Hurdles
• getting management buy-in
• dealing with false positives
• strategies for disparate systems
• international issues
• incongruent processes/policies
• outsourced IT
• external and cloud-based data

15. People and Process Issues
• organizing the team
• developing and maintaining skills
• prioritizing analytics
• measurement and KPIs

16. Reporting and Interpreting Results
• presenting results in a meaningful way
• overlapping results
• analytic precision

17. Advanced Topics and the Evolution of Analytics
• continuous monitoring
• dashboard and visual analytics
• score carding
• predictive analytics
• spatial relationships and mapping

Event Categories
Keywords: fun, analysis, access , business , class , design , Designing, Fun , iOS, jo


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