Most would agree that by now, "Big Data" is a household concept in the strategic enterprise technology circuit. In this post I take an actual example of Big Data use and explore the implications of adopting and integrating it into a traditional business process. While there is a formal Gartner model defining the essential three dimensions of Big Data, for my purpose, a simple working definition might be that it is massive amounts of data, often unstructured (for example free flowing human readable text as in this blog post, as opposed to structured data in relational databases) generated either by humans or devices, that can be analyzed using advanced tools and may lead to unprecedented business insights.
Below is a demo video from IBM which delves into a specific business application of Big Data. I specially like it since it gives "just right" amount of detail (okay I'm speaking for myself here) to understand the usage. The commentary is neither at a thirty thousand foot marketing level nor so technical so as to lose the big picture.
The departmental unit in focus here is the Office of Technology Transfer, which is present at most research universities, corporate research and government research organisations (such as the National Institutes of Health OTT). The unit hangs in delicate balance at a point where incoming resources are thin while the expected output business value (from licensing and selling of IP assets) is enormous, potentially worth millions of dollars in licensing deals. Sounds like a familiar predicament? In fact, especially in universities, where the OTT is critical for creating a steady alernate revenue stream out of IP assets, the unit is frequently understaffed. The staff comprising of a mix of students and full time staff analysts are left to their own devices to perform the arduous task of sifting through massive amounts of heavy duty scholarly content strewn across the Internet hoping to make the crucial match between demand and supply that will result in a signed deal. The video illustrates what it means to apply Big Data to such a business model and how a company may use new capabilities gained from this to its advantage.
So does this mean Big Data is a panacea for all enterprise business analytics ailments?
Here are some of my takeaways from the video:
Below is a demo video from IBM which delves into a specific business application of Big Data. I specially like it since it gives "just right" amount of detail (okay I'm speaking for myself here) to understand the usage. The commentary is neither at a thirty thousand foot marketing level nor so technical so as to lose the big picture.
The departmental unit in focus here is the Office of Technology Transfer, which is present at most research universities, corporate research and government research organisations (such as the National Institutes of Health OTT). The unit hangs in delicate balance at a point where incoming resources are thin while the expected output business value (from licensing and selling of IP assets) is enormous, potentially worth millions of dollars in licensing deals. Sounds like a familiar predicament? In fact, especially in universities, where the OTT is critical for creating a steady alernate revenue stream out of IP assets, the unit is frequently understaffed. The staff comprising of a mix of students and full time staff analysts are left to their own devices to perform the arduous task of sifting through massive amounts of heavy duty scholarly content strewn across the Internet hoping to make the crucial match between demand and supply that will result in a signed deal. The video illustrates what it means to apply Big Data to such a business model and how a company may use new capabilities gained from this to its advantage.
So does this mean Big Data is a panacea for all enterprise business analytics ailments?
Here are some of my takeaways from the video:
