The AMPS Model: Master the Data

• Data Accessibility – can we get the needed data to answer the question posed?

• Data Reliability – is the data clean?

• Data Integrity – is the data accurate, valid and consistent over time?

• Data Ethics – was the data gathered and protected in a morally responsible way?

• Data Type – is the data structured? is the data internal? are there privacy concerns with the data?

Extract, Transform, and Load

• Before data can be analyzed and be useful, it must be scrubbed from extraneous data and noise.

• Reformatting, cleansing, and consolidating large volumes of data from multiple sources and platforms can be especially time consuming. Data analytics professionals estimate that they spend between 50 percent and 90 percent of their time cleaning data for analysis. 

• The cost to scrub the data includes the salaries of the data analytics scientists and the cost of the technology to prepare and analyze the data. As with other information, there is a cost to produce these data. 

Audit Data Standards

• If both the provider and the user (for example, a company and its external auditor) of the data had the same data standards for their data, this cost of cleaning and formatting the data could be alleviated.

• Audit Data Standards (A D S) is a set of standards for data files and fields typically needed to support an external audit in a given financial business process area.

• Link to Audit Data Standards.

Audit Data Standards Benefits

• Reduces the time and effort involved in accessing data.

• Works well with standard audit and risk analytic tests often run against datasets in specific accounts or groups of accounts (such as inventory or accounts receivable or sales revenue transactions).

• Allows software vendors (such as A C L Inc.) to produce data extraction programs for given enterprise systems to help facilitate fraud detection and prevention and risk management.

• Facilitates testing of the full population of transactions, rather than just a small sample.

• Connects/interacts well with XBRL GL Standards