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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