Data Mining & Analytics
RVACFES 53 – Data Mining & Analytics – 3 CPE – To purchase this lecture add it to your Cart and follow the on-screen instructions …
Data mining and data analytics have been proclaimed in some circles as representing the future of all types of auditing in the twenty-first century. The actual data mining task is the automatic or semi-automatic analysis of large quantities of data to extract previously unknown interesting patterns such as groups of data records (cluster analysis), unusual records (anomaly detection) and dependencies (association rule mining). This involves using database techniques such as spatial indexes. These patterns can then be seen as a kind of summary of the input data, and may be used in further analysis or, for example, in machine learning and predictive analytics. For example, the data mining step might identify multiple groups in the financial data under analysis by the Fraud Examiner, which can then be used to obtain more accurate prediction results by a decision support system. Neither the data collection, data preparation, nor result interpretation and reporting are part of the data mining step, but do belong to the overall data analysis process as additional steps.
This lecture is a good introduction to the data mining process for CFE’s, CPA’s and any type of auditor wrestling with making sense of large caches of client data.
100 minutes of self study plus 10 minutes to answer 10 questions for a total of 110 minutes.
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