Some suppliers of goods and services love the idea of “big data,” the ability to mine huge amounts of internal structured and unstructured data, while correlating that data with other external sources to develop a very granular view of business processes, whether that is retail customer behavior, inventory processes or changes in asset prices and volumes.
For suppliers of analytics software, data storage and cloud computing, “big data” requires huge amounts of new storage and processing. Many organizations “rationally” purge old data, to save money. But loss of that data means tracking of many changes, over time, which is not possible.
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The more data that can be stored at the right cost, the more effective a business can be, Microsoft argues.
An equally big challenge is integrating semi-structured and unstructured data. Massive amounts of data are generated from corporate blogs and collaboration tools, security events, radio tags, remote monitors and sensors. In other cases, clickstream and keystroke data might also be available.
But access to huge amounts of external and unstructured data types is also a part of the value of “big data.” That often includes social media and web analytics, or geographical, meteorological and public safety information.
The ability to mine data and then derive insights in real time, or nearly real time, also is crucial. The faster insights are drawn from data sources, the sooner they can be acted upon. That is obvious in parts of the financial services industry involved in real-time trading. It can be true in healthcare.
The demand for real time analysis is arguably less time sensitive in retailing. But it is pretty obvious that suppliers of information technology initially might derive more business benefit from big data than most enterprises deploying it. The reason is simply that big data will require “re-architecting” enterprise information processes.
That always is expensive and difficult. And, as always, it will take time for the benefits to be realized. In fact, as always, there is a substantial probability that some adopters will not actually reap gains, while some will reap minimal gains. Big IT projects are like that.