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