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Using analytics in auditing big data

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Big data is defined by the large amounts of structured and unstructured data from multiple sources. Auditing big data is becoming a concern especially when we learn that 80% of currently accumulated data was generated over the past 2 or 3 year, and the fact that big data cannot be analyzed by traditional systems.

From an audit point of view, there are 5 key areas for auditors and security professionals to focus on when reviewing big data systems, IoT systems and their deployments.

These 5 areas are:
● Structured data sources—databases, spreadsheets
● Unstructured data sources—chats, GPS data
● Real-time data feeds—Facebook, Twitter
● Time-sensitive data—log files
● Metadata about data—the description of data elements.

This is a challenge in itself as companies lack the guidance on what data should be made available to auditors and the traditional auditing process still dominates current standards, where samples of data are analyzed as opposed to the entire breadth of data, which would intuitively provide more insight.

One of the solutions to this challenge is the integration of big data and analytics. In fact, both suggest a promising solution which would enable auditors to identify financial reporting, fraud and operational business risks and develop an approach to deliver a better audit recommendations.

ISACA defines Big Data Analytics (BDA) as “the application of emerging statistical, processing and analytics techniques to big data for the purpose of advancing the business”.

But the usage of analytics in auditing is still challenging because auditing is a regulated industry and there are certain considerations to be made when introducing analytics in the audit process. Outstanding questions need answers such as: What will be the source of the audit reports? How do you identify the audit evidence? What is the precision level the auditors require of data analytics

The move into the next generation of auditing is facing regulatory and legal complexity that raises question on the readiness of the audit industry to embrace this transformation. There are different players in this industry and their response to the change is different. Big data is not only changing the way audits are performed, but also is opening the door for challenging the existing audit standards and processes.

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