Big Data: Some resources

For the CAs and CISAs, looking for the coles notes version of what's going in the world of big data, check out the following podcast by David Linthicum and company; some of the most knowledgeable people on Cloud computing. Chris Daly (who works with Dave) provides a good nine item list based on this article. Chris did us all a big favour by breaking down the slideshow into a nice list of nine points. I will let you click on the link to see what they are, but I thought it was interesting to comment on the first two:

• "Define the business drivers". It's pretty amazing how this single premise is one of the most critical concepts on business-technology, that requires constant attention! Ironically, I just finished answering a question to a fellow accounting profession who is taking a course on IT controls to emphasize this point. What I explained to him was that the fundamental concept here is that technology changes are driven by business. In other words, IT Strategy or investments must be driven by the overall value drivers of the business.As for why you would not make changes to the system because of technological improvements is because those technologies may have no actual "Return on Investment" (ROI) for the business. In other words, companies should not adopt technology for the sake of technology. 
• "Discover the data and it’s location". Wow! For those of IT-auditors that run computer assisted audit techniques (CAATS) can really appreciate how these six words can represent a mountain of work! When I teach the computer-assisted audit techniques course at University of Waterloo, I always make a point of warning my students of the practical limits of running CAATs: getting the data can be the hardest aspect of the whole process. For those of you not familiar what CAATs are, they are basically  automated tests that auditors will run using "generalize audit software" on data that is used to support items on the financial audit. You can also use these technique to identify security issues or fraud; see IDEA's Caseware. (Full disclosure: Caseware is a both a sponsor of the Center that supports this blog as well as the course I teach at UW). For example, these tools help perform full analysis of a set of data e.g. identify all the negative amounts in an inventory file or link files to together using a unique identifier to compare the data from one file (e.g. credit limits) to the data in another file (e.g. total amounts owing by the customer. Also, check out the wikipedia entry it's pretty good. 

For other sources, check out the massive (and free) report from McKinsey on Big Data, which they have even made available to run on your Kindle App on your Android or iOS device. Also, check out this CAMagazine article on the topic. This HBR blog post has provides a look at the overall issues, including privacy problems. 

If you have any other resources, especially from an IT Auditor (i.e. security, data integrity, etc), perspective, please do share.