1. Evolution of Data Analysis
By Monica Holtforster

2. History of Audit Analytics
Cobol / Easytrieve
DOS
Windows
Server Technology

3. In the Beginning

4. DOS Based Data Analytics

5. Today’s Audit Software

6. Impact of Technology on Software
Speed of processing / file size accommodated
Ease of use
Import options available
Graphical repesentation
Technical level of user

7. Data created and captured worldwide
Exabytes
ATMs
ERPs
Transactional data
CRM , Accounting databases, new compliance requirements, new medias etc…
Tenfold growth observed in five years
Source: “Digital Universe” study 2008

8. IDC Study highlights In 2011, digital data was 10 times size of 2006
44-fold in the next ten years
Data growth can not be ignored
Tools are in place and proven

9. Evolution of Data Analysis Techniques
Source: ISACA– July2011

10. Where is your company’s use of data analysis on this chart?

11. Definition of Ad Hoc Typically used for initial investigation
Typically run to support specific projects
Rarely performed directly on production systems
May be difficult to repeat if steps not well documented
Often relies on skill of selected skilled individuals

12. Evolution of Data Analysis techniques
PC based audit software
Source: ISACA– July2011

13. Definition of Repeatable
Predefined and scripted to perform the same tests on similar data
Data access tools may be used to import data directly from production systems
Reliance on skilled individuals significantly reduced
The quality of analysis is improved and remains consistent as the data acquisition process is partially or fully automated

14. Centralized Analytics
Centralized approach for the development, storage and operation of repeatable DA
Standards for development of DA are documented
Applications are set up and scheduled to run against the centralized data on a regular basis
Data can either be pushed or pulled from different sources

15. Evolution of Data Analysis techniques
Server based software
Source: ISACA– July2011

16. Continuous Monitoring
Analytics are fully automated and running at regularly scheduled intervals
may be embedded directly into a production system
often developed and owned by operations management

17. Evolution of Data Analysis techniques
CM software running on a server
Source: ISACA– July2011

18. Recommendations
Do simple process development first, using existing software
Automate data extraction and validation
Reduce false positives
Prioritize by likelihood of recovery
Refine and document the testing process over several cycles.

19. Future Expectations Predictive pre-canned analysis
Increased intelligence in the software
Integration of different tools
Use of external sources for comparison

20. Conclusion
As the definition of data changes, who knows what additional changes we will see incorporated into data analytics?