Mining the Company Data

Data mining is the process of extracting patterns from data.  Data mining is seen as an increasingly important tool by modern business to transform data into business intelligence giving an informational advantage.  It is currently used in a wide range of profiling practices, such as marketing, surveillance, fraud detection, and scientific discovery.  (Source: Wikipedia definition of data mining)

Most business software allows one to extract data very easily by downloading it into Microsoft Excel or other types of files.   The data can be downloaded to included a number of data field combinations within each record. Once the information is in Excel it can be manipulated with
 the use of data or pivot tables to sort and provide valuable information about the business.

One use of this data in practice is an accountant's test of internal controls or the existence of fraud or errors as part of an internal or financial audit.  Accountants extract records from a company database and sort the data to identify transactions that are exceptions to company policies or look irregular.  Some procedures include, comparing vendor master records to employee master records for data matches, checking for gaps in sequence of invoices numbers, review minimum and maximum prices paid for inventory items, duplicate journals or amount, etc.  These are test performed to identify potential errors or irregularities.  Accountants will typically use special software that perform these test very easily.  With the ability to download data into Excel a lot of the same test can be performed without any additional software.

The mining of one's data is not exclusive to accountants.  There are a number of other potential uses for example marketing and sales research.  The record of sales transactions contains information about what products are selling and to whom.   A little creativity and time digging into the data can provide valuable information about your business.  The data can tell for example who your most profitable customers are.  This information can be used to segment your customer base to focus on your best ones! 

It's important to note that data mining generally implies the use of statistical analysis.  The techniques I reference above do not involve statistical analysis which is outside the scope of this posting.  Statistical analysis involves extraction of samples from the data to formulate predictive information.  This form of data mining is a prospective look which is a more proactive use of the data. 

For more information on this subject please contact me at:  ajordancpa@comcast.net