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Shirish Netke

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Fintech in 2017: Risk management takes center stage

A day in the life of the gentleman banker was once described by the 3-6-3 rule – accept deposits at three percent, loan money at six percent and tee off at the golf course at 3 p.m. The financial services industry can rightfully state that it has come a long way since then. It has implemented technological innovation and managed risk in a constantly changing economic environment over several decades. The gentleman banker has since evolved into a sophisticated financial risk manager who works within a complex framework of rules and regulations with tens of trillions of dollars of assets under management. 

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Topics: big data, banking, AML, fintech, regtech, regulation, machine learning, money laundering, risk management

2015 Year in “PreReview” in Technology

The summer of 2015 marked the release of the blockbuster Sci-fi movie, “Terminator Genisys,” which grossed a record $350 million at the box office and further popularized the notion of time travel. In addition to sequels and prequels, Hollywood has now adopted plots for movies in which the audience can choose among alternate storylines and follow them to their logical conclusion. The future, as we know it, is plural. This year in our PreReview of 2015, we once again present a few alternative scenarios for the future from our vantage point at the end of 2014. 

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Topics: PreReview, marketing, analytics, 2015, wearable computing, big data, advanced analytics, social media, Big Data practicioner, quantitative analytics, MoSoLoCo, data scientist, data analytics infrastructure, Big Data Prescriptions, predictive analytics

Big Data Performance Anxiety and Data Grids

In Memory Data Grid (IMGD) is a data structure that is being increasingly cited as a solution to the problem of scaling big data applications. Unlike in-memory applications, IMGDs distribute only the data across RAM over multiple servers.  With memory prices continuing to fall and the volume of data for an application continuing to rise, solutions based on memory are looking more attractive to address the performance bottlenecks of applications using Big Data. Should IMGD be on your radar screen for a Big Data application? In order to understand this and other questions on IMGDs, Carpe Datum Rx spoke to Miko Matsumura, VP of Marketing and Developer Relations at Hazelcast, who has seen recent adoption of this technology in banks, telcos and technology companies. Here is an extract from our discussion.

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Topics: analytics, big data, advanced analytics, NoSQL, data analytics infrastructure, Big Data Prescriptions, CIO

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