What is Streaming Analytics?
Watch this video to learn about analyzing and taking action on data in motion -- streaming analytics.
Streaming data often has a short half life. It loses value quickly. This is in contrast to conventional analytics, which takes a more historical approach. Conventional and streaming analytics are complementary. Conventional analytics can provide context for streaming analytics, helping analysts know the right questions to ask in real time.
Okay. So, what is streaming analytics? We get asked that question a lot these days. And the simple definition is that it's all about analyzing and making actionable decisions on data while it is in motion. This is data that has a very short half life.
So, for instance, if you're picking up a customer--you have a beacon in your store and you're picking up a customer in aisle five, at that point, with streaming analytics, you can make a decision in terms of should we then direct this customer to aisle seven to take a look at a product that he or she might be interested in. This is data which is valuable in the moment but would have relatively limited value, if any at all, say an hour later.
Now, this differs from conventional analytics, which takes more of a historical look where you may perform more sophisticated modeling on it. And the idea with historical analytics is this frames the context. It tells you what trends to look for and therefore what questions to ask in real time.
Streaming and Conventional Analytics are Complementary
And the fact is it's not a question of either/or. Both streaming and conventional analytics really are complementary in that one provides the context for the other, but in turn, streaming analytics can provide essentially kind of a closed loop calibration, which can basically tell you, have--as to whether the situation on the ground has changed to the point where we need to change the questions.
So, if you think about streaming analytics and conventional analytics, they really are most effective when they're used together.