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Analytics Everywhere – To be part of Transaction not Post thought.

Posted by: Manish Kampani On September 08, 2017 06:16 PM facebook linked in twitter

Ever since I first heard the term ‘Analytics Everywhere’ 3-4 months ago from one of my seniors, I had been pondering over this idea. After attending an informative session, I realized it’s already getting significant traction, some implementations are on way, and soon we will get to see more and more applications of this concept in our lives.

We are entering the next wave of Analytics - equipped with new talent, technologies, and ever-improving computing methods. Essentially, Analytics Everywhere, part of each transaction we make, implies that Analytics cannot be an afterthought. It has to be embedded seamlessly as part of each business transaction in the near future. Decision making will become not only rule-based, but more and more informed, based on a lot of data. Near real-time analytics or building Data Lake to perform analytics will exist, but when analytics and decision making become part of every transaction, it will bring immense benefits to the organization and customers.

Speaking of transactions, a lot of pertinent questions do spring up immediately. Should we wait till fraud occurs in transactions to react? Shouldn’t we rather start adding logic and patterns for detecting fraud in credit card transactions? May be not for all scenarios, but as much as we can. Learning will go on; and smarter and faster algorithms will improve it further. This may reduce the volume of claims, thus extending tremendous help to the credit card and insurance companies.

Can Anti-Money Laundering logic be embedded through cross-border transactions, rather than reporting it from Data Lakes? Should organizations wait for churn analytics algorithms to produce the list of probable customers, and then reach out to them with fresh offers? Shouldn’t the Customer Care team be informed as and when the customer is browsing the website, and learned algorithms detect chances of churn? There are so many day-to-day scenarios and use cases one can visualize right away. The applications of Analytics Everywhere can bring about such deep positive impact in business all over. A lot of validations can be shifted to left part of the life cycle of business transactions, which can improve the robustness and agility of the business.

Technologies such as Microservices, Big Data, Data Science, Machine Learning, In Memory computing and Elastic Infrastructure can/are making it happen. We can visualize an architecture with Microservice in memory, which can be elastically expanded on need, supported by the Big Data Elastic infrastructure, and already Learned Algorithms to provide inputs to each transaction via API, whenever the transaction needs them. Steadily, I am seeing this getting real, as part of several customer discussions and new age solutions - may not be end-to-end, but at least part of it as of now. And I am sure, quite soon all the components will be integrated.

As the concept of Analytics Everywhere catches up, it will call for a significant collaboration, secured methods to provide information for each API calls, infra to support the amount of data flowing into the networks, and hyper speed connectivity.

The need for Analytics Everywhere will spurt a set of innovations, which in turn, will help boost business agility and robustness manifold. Many boutique firms will evolve, offering services built on Microservices to provide real-time inputs for transactions on various cost models. This will definitely need much better infrastructure and that is already evolving much faster than one can imagine.

About Author

Manish Kampani, Global Delivery Head, BI, Big Data and Data Management Services - CME

Manish leads delivery for BI, Big Data, Analytics and Data Management services globally as part of DigitALL Strategy for Telecom and CME verticals, and directs development of Key IPs. He has successfully transformed the BI, Big Data and Data Management business at TechM, and got it into High growth Curve. His vision and focus has helped the growth of key data platforms in Big Data, Data Migration and Data Quality. Follow him @ManishKampani

Tags: Leadership Talk, In The Future
 
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