Saturday, January 18, 2014

Real Time Analytics

Real-time analytics could be useful in scenarios where you have to take immediate decisions.

Real-time business intelligence (RTBI) is the process of delivering information about business operations as they occur. Real time means near to zero latency and access to information whenever it is required.

Real-time data denotes information that is delivered immediately after collection. There is no delay in the timeliness of the information provided. Real-time data is often used for navigation or tracking. Some uses of this term confuse it with the term dynamic data. In reality, the presence of real-time data is irrelevant to whether it is dynamic or static. But the data collection mechanism at grass root level is mechanical that there are delays in the time line of the information provided. This is because of absence of internet connection and other electronic data collection instruments.

Weather to run real time data analytics or not depends on the need and purpose; you consider whether you require real-time analytics or just real time action. The reason for making the distinction is that a lot of value can be created from acting in real time off the calculations performed on a periodic basis. The reason you'd rather perform such calculations on a periodic basis rather than in real time is that doing so is a lot less complicated as well as less expensive. 

Real-time analytics could be useful in scenarios where you have to take immediate decisions. If you are at consumer business in setting prices, or running a call center trying to determine whether or not you have the right coverage on a calling campaign, then you probably do need real time or real enough time analytics for "availability" or "profits". Real time is going to be useful where the volume that can vary dependent on things you can control, for example, product price/availability or SLA in e-commerce or brick and mortar environment. In each of these instances real time access may deliver a considerable portion of the value that could be delivered through real-time analytics. So, you may wish to take a careful look at what you're trying to accomplish in order not to invest more time and resources than necessary.

Real Time analytics can be a hard thing to implement. It should only be made a priority if it leads to actionable insights almost immediately. A nightly or weekly run of each customer's purchase history would allow the company to prepare for each customer's next visit by pre-populating a table with the right items. There's no need to do all these calculations in real time. Similarly, determining the correlations between the purchases of various items does not have to be calculated in real time either. It’s actually better in many cases for users not to have real time data, simply because their ability to react to it in a useful way is constrained by the speed with which real time data accumulates. There are at least two challenges in running real time analytics:
-Having a system that can support quick changes and implement them throughout the entire business process
-Having enough data to draw statistical significance

So weather to run real-time analytics or not depends on the situation and how rapidly things change, do it with clear business purpose, proven methodology and cost effective discipline. 


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