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analytics (3)

  • Price discrimination and downward demand spiral are widely used analytical concepts/practices in the Airlines and Hospitality industries respectively, long before the term Big Data Analytics was even coined. Incidentally, these concepts have been taught in global elite b-schools for decades. So, how come Analytics, which has been there in practice for decades experience a meteoric rise suddenly? To answer this question, we need to get the Big Picture. Given below are key factors that led to huge buzz around analytics today.

    • Proliferation of Data Sources – Every day we create…
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  • The advent of sharing economy has brought a sea change in the way urban populace commute locally. The Ubers, Lyfts and many other local players have made taxi riding convenient, affordable and safe. These rides have emerged as a strong alternative to the public transport clocking millions of rides per month in some cities. The emergence of hyper-local delivery models to optimize the supply chain has also led to a large number of daily trips by these vehicles.

    These developments have mandated the installations of either standalone or smartphone app-based GPS devices to keep track of and better regulate these rides and a fleet of taxis. These GPS systems spew a ton of data generating up to GBs of…

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  • R + Hadoop = Data Analytics Heaven

    Hadoop (MapReduce where code is turned into map and reduce jobs, and Hadoop runs the jobs) is the most well known technology used for "Big Data" because it allows an organization to store huge quantities of data at very low costs. R is a programming language and software environment for statistical computing and graphics. Put the two together to provide easy to use R interfaces for the distributed computing Hadoop environment and you have one king-hell data crunching tool for serious data analytics. RHadoop is a small, open-source package developed by Revolution Analytics that binds R to Hadoop and allows for the representation of MapReduce algorithms using R - allowing data scientists access to Hadoop’s scalability from their favorite language, R. It allows users to write general MapReduce programs, offering the full power and ecosystem of an existing, established programming language.
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