Hybrid Cloud For Dummies

Supporting an Analytics Strategy

What good is all that data if you can’t do anything active with it? The lure of analytics in the cloud is cloud elasticity. Your data can be processed across clusters of computers. This means that the analysis is occurring across machines. If you need more compute power, you can get it from the cloud.

Big data analytics

Here are some examples of where analytics get big and may require cloud resources:

Financial services: Imagine using advanced analytics technologies like predictive analytics to analyze millions of credit card transactions to determine whether they might be fraudulent. Or, on the unstructured side, picture the text in insurance claims being analyzed to determine what might constitute fraud.

For example, take a worker’s compensation claim submitted by a worker who may have been reprimanded several times by his boss. This data (or the claim), which came from unstructured sources, can be utilized together with structured data to train an analytical system on what patterns might indicate fraud. As new claims come in, the system can automatically kick out the ones that may need to be investigated.

Retail: Just think about the recommendation engines from Amazon and eBay. They’re becoming more sophisticated. eBay is utilizing advanced technologies ...