Big Data Quotes of the Week

“All the lenders are data poor. We hope we can make them data rich, insight rich”–  Douglas Merrill, ZestFinance

“Many companies have these Fort Knox data depots, where they collect enormous amounts of critical data that’s inaccessible, or just not analyzed regularly”–Doug Levin, Quant5

“I don’t do pure research. The objective of all the analysis I do is to enable some kind of functionality, some kind of real-world functionality. If all I do is collect data without presenting it in a compelling way that inspires further action, then I’ve only done half my job”—Edwin Chen, Twitter   

“I actually think that a lot of the conversation right now in data science is very focused on engineering‑type questions, which we’re pretty good at specifying and solving in a specific way…  getting back to this thesis that I have, that data science is really about understanding human behavior and trying to find interesting patterns about that so that we can form lots of problem areas that we haven’t been able to address yet. Things like social policy, health care and medicine, local, national, and international policies about national security and war and peace and things like that, we haven’t really addressed those before”–Drew Conway, NYU

The primary motivation for Jake [Porway] and I to form DataKind was that we did not have an outlet for using our skills for social good. We knew social organizations had lots of data, and we knew there were many data scientists that wanted to help the analyze it, but we just didn’t know how to connect the two communities. The response to DataKind has been overwhelming, which thoroughly convinced us that data science for social good is not only a viable career path, but also a necessary part of defining data science as a discipline”–Drew Conway, NYU

“The value of Hadoop lies not in the technology itself, but in the real world problems it can solve”—Jeff Hammerbacher, Cloudera

“Hadoop is a strange tool. You have to write a program, and then you have to write a program on that data, and then you’ll get some numbers, and you have to interpret that data yourself”–Suhail Doshi, MixPanel

“You’re really going to be consuming Hadoop… The question’s only whether you want to customize it, or whether you want to consume a packaged application”–Charles Zedlewski, Cloudera

“While traditional BI is interested in the ‘what and the where,’ data scientists are interested in the ‘how and why’”–Amit Mehta, EMC

“Essentially, Big Data can handle more data and is way faster than BI, which means exploration and interactivity and in some cases delivering results in less time than it takes to load a web page”–Subroto Das, IBM

“After graduating from CMU in 2006, Hooman [Radfar, co-founder of AddThis,] started AddThis, diving head first into a space that had been largely unexplored, big data… During the recession in 2008, Hooman doubled down on a value exchange model, which was very risky at the time. AddThis had a bunch of sharing plugins and analytics that they had made free… it was time to show that their business model could generate revenue. Hooman decided that they would continue to offer the service for free and instead build a business around the aggregated data. Turns out that was the right decision, because AddThis has grown from 600 million users in 2009 to 1.3 billion today, processing 10 terabytes of data a day in real time”–Amanda Schwab, PandoDaily

About GilPress

I launched the Big Data conversation; writing, research, marketing services; https://whatsthebigdata.com/ & http://infostory.com/
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1 Response to Big Data Quotes of the Week

  1. Douglas Merrill:
    Fair Isaac is now FICO – there Credit Scoring technology started at SRI International in 1958 – BEST physicists and mathematician in the country with a devotion to operations research applications developed an unparalleled infrastructure for Big Data Analytics – SaaS – All banks are customers of a Credit Scoring product.
    http://www.myfico.com/crediteducation/creditscores.aspx

    Equifax with their Experian product – did marvel in their field for modeling financial behavior at the household level
    http://www.experian.com/credit-report-partner/index-g.html?WT.srch=ECDG1&bcd=tnKm6tJF&mkwid=stnKm6tJF&pcrid=7293527469&kwid=equifax&match=e

    “All the lenders are data poor. We hope we can make them data rich, insight rich”–

    The reality is the Lenders are data rich, analytics rich, insight rich – however, the POLICY of lending can be divorced from the evidence based practice.

    Doug Levin, Edwin Chen — agree with both of you !!

    Like

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