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Harnessing Real Time Predictive Analytics - Part 1

MohanDani 270001P2WC | | Tags:  real processing and data streams infosphere big spss stream ibm analytics time ‎ | 7,053 Views
We speak about Big Data and need for Real Time Analytics etc. Can we really infer and make decisions if we dont have the knowledge to interpret data?, Speed to respond without content is a lost opportunity and nothing else. Hence,Harnessing knowledge which is empirical and making instant decisions which is accurate was WISHFUL thinking in the past. Streams and SPSS products come together to render this solution seamlessly.

IBM SPSS Modeler provides a state of the art environment for understanding data and producing predictive models.  InfoSphere Streams provides a scalable high performance environment for real time analysis of data in motion including traditional structured or semi-structured data to unstructured data types.  Some applications have a need for deep analytics against stored information and low latency high volume real time use of those analytics to provide scoring.  

Lets Take a look at some of the Actors in this story: 

Data Analyst – a modeling expert that knows how to use the IBM SPSS Modeler tools to build and publish predictive models.

Streams Application Developer – an InfoSphere Streams developer responsible for building applications.

Lets hear the Plot of the Movie along with Actors: The problem is in a retail scenario of Online shopping, A user browses through various products and chooses a few products into his basket to check out. For example: If a person purchases Tennis Racket we can present him with various types of tennis ball and highlight the training ball,also if we knew that this person is a championship player and consumes high quality tennis balls. that can be offered to him rather than training balls. This leveraging of past known transaction pattern analysis and predictive next step solves this problem efficiently.
 
We will discuss the Actors roles in part of the future movie. More to come in Part -2 where we see actors working their roles where a discussion ensues about when to apply what kind of algorithm and how to use it in real time.Some of the hilarious failures from these learning models and how they eventually mature the sales process in the Online retail store called "FREEFORALL" Retail Chain.
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