Links for Oct 21 2012

Technology Consultant - Eric D. Brown | Image for link posts
  • Big Data Hype (and Reality) – Gregory Piatetsky-Shapiro – Harvard Business Review

    Quote: Big data analytics can improve predictions, but the biggest effects of big data will be in creating wholly new areas. Google, for example, can be considered one of the first successes of big data; the fact of its growth suggests how much value can be produced. While analytics may be a small part of its overall code, Google’s ability to target ads based on queries is responsible for over 95% of its revenue. Social networks, too, will rely on big data to grow and prosper. The success of Facebook, Twitter, and LinkedIn social networks depends on their scale, and big data tools and analytics will be required for them to keep growing.

  • I’m sorry, you’re just not incompetent enough to get it

    Quote: Enterprise software is expensive. It is so, because enterprises have money. Obscene amounts of money. You can’t walk into an Enterprise and offer them a simple, effective solution for a reasonable amount, because they simply won’t believe (you) that it works. Enterprises have been bred into the belief system that expensive equals good. They do so, because they lack knowledge of prior events, and because they are afraid to let go of their mental models unless forced to do so.

  • New ethics for a new world – O’Reilly Radar

    Quote: Big data is about reducing the cost of analyzing our world. The resulting abundance is triggering entirely new ways of using that data. Visualizations, interfaces, and ubiquitous data collection are increasingly important, because they feed the machine — and the machine is hungry.

  • Your C-Suite Needs a Chief Data Officer – Anthony Goldbloom and Merav Bloch – Harvard Business Review

    Quote: Identifying how data can be used to support the company’s most important priorities. Some data use cases are obvious. Others are less so. Companies don’t necessarily realize, for example, that they can use cross-selling algorithms to increase customer depth, or lead-prioritization algorithms to increase sales conversion rates. When meeting companies for the first time, we’ve learned not to ask, “Which problems can we help you with?” but rather, “What are your most pressing business problems?” Nine times out of 10, data has something to say about those problems — it’s just that the company doesn’t realize it.