Evolution of Data Analysis

By Monica Holtforster

History of Audit Analytics

• Cobol / Easytrieve• DOS• Windows• Server Technology

In the Beginning

DOS Based Data Analytics

Today’s Audit Software

Impact of Technology on Software

• Speed of processing / file size accommodated• Ease of use• Import options available• Graphical repesentation• Technical level of user

Data created and captured worldwide

Source: “Digital Universe” study 2008

Exabytes

Tenfold growth observed in five years

ATMsERPs

Transactional data CRM , Accounting

databases, new compliance requirements, new medias etc…

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

Evolution of Data Analysis Techniques

Source: ISACA– July2011

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

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

Evolution of Data Analysis techniques

Source: ISACA– July2011

PC based audit software

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

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

Source: ISACA– July2011

Evolution of Data Analysis techniques

Server based software

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

Source: ISACA– July2011

Evolution of Data Analysis techniques

CM software running on a server

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.

Future Expectations

Predictive pre-canned analysisIncreased intelligence in the

softwareIntegration of different toolsUse of external sources for

comparison

Conclusion

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