ENTRIES TAGGED "Big Data"

Four short links: 23 April 2014

Four short links: 23 April 2014

Mobile UX, Ideation Tools, Causal Consistency, and Intellectual Ventures Patent Fail

  1. Samsung UX (Scribd) — little shop of self-catalogued UX horrors, courtesy discovery in a lawsuit. Dated (Android G1 as competition) but rewarding to see there are signs of self-awareness in the companies that inflict unusability on the world.
  2. Tools for Ideation and Problem Solving (Dan Lockton) — comprehensive and analytical take on different systems for ideas and solutions.
  3. Don’t Settle for Eventual Consistency (ACM) — proposes “causal consistency”, prototyped in COPS and Eiger from Princeton.
  4. Intellectual Ventures Loses Patent Case (Ars Technica) — The Capital One case ended last Wednesday, when a Virginia federal judge threw out the two IV patents that remained in the case. It’s the first IV patent case seen through to a judgment, and it ended in a total loss for the patent-holding giant: both patents were invalidated, one on multiple grounds.
Comment
Four short links: 22 April 2014

Four short links: 22 April 2014

In-Browser Data Filtering, Alternative to OpenSSL, Game Mechanics, and Selling Private Data

  1. PourOver — NYT open source Javascript for very fast in-browser filtering and sorting of large collections.
  2. LibreSSL — OpenBSD take on OpenSSL. Unclear how sustainable this effort is, or how well adopted it will be. Competing with OpenSSL is obviously an alternative to tackling the OpenSSL sustainability question by funding and supporting the existing OpenSSL team.
  3. Game Mechanic Explorer — helps learners by turning what they see in games into the simple code and math that makes it happen.
  4. HMRC to Sell Taxpayers’ Data (The Guardian) — between this and the UK govt’s plans to sell patient healthcare data, it’s clear that the new government question isn’t whether data have value, but rather whether the collective has the right to retail the individual’s privacy.
Comment
Four short links: 18 April 2014

Four short links: 18 April 2014

Interview Tips, Data of Any Size, Science Writing, and Instrumented Javascript

  1. 16 Interviewing Tips for User Studies — these apply to many situations beyond user interviews, too.
  2. The Backlash Against Big Data contd. (Mike Loukides) — Learn to be a data skeptic. That doesn’t mean becoming skeptical about the value of data; it means asking the hard questions that anyone claiming to be a data scientist should ask. Think carefully about the questions you’re asking, the data you have to work with, and the results that you’re getting. And learn that data is about enabling intelligent discussions, not about turning a crank and having the right answer pop out.
  3. The Science of Science Writing (American Scientist) — also applicable beyond the specific field for which it was written.
  4. earhornEarhorn instruments your JavaScript and shows you a detailed, reversible, line-by-line log of JavaScript execution, sort of like console.log’s crazy uncle.
Comment

The backlash against big data, continued

Yawn. Yet another article trashing “big data,” this time an op-ed in the Times. This one is better than most, and ends with the truism that data isn’t a silver bullet. It certainly isn’t.

I’ll spare you all the links (most of which are much less insightful than the Times piece), but the backlash against “big data” is clearly in full swing. I wrote about this more than a year ago, in my piece on data skepticism: data is heading into the trough of a hype curve, driven by overly aggressive marketing, promises that can’t be kept, and spurious claims that, if you have enough data, correlation is as good as causation. It isn’t; it never was; it never will be. The paradox of data is that the more data you have, the more spurious correlations will show up. Good data scientists understand that. Poor ones don’t.

It’s very easy to say that “big data is dead” while you’re using Google Maps to navigate downtown Boston. It’s easy to say that “big data is dead” while Google Now or Siri is telling you that you need to leave 20 minutes early for an appointment because of traffic. And it’s easy to say that “big data is dead” while you’re using Google, or Bing, or DuckDuckGo to find material to help you write an article claiming that big data is dead.

Read more…

Comment: 1
Four short links: 10 April 2014

Four short links: 10 April 2014

Rise of the Patent Troll, Farm Data, The Block Chain, and Better Writing

  1. Rise of the Patent Troll: Everything is a Remix (YouTube) — primer on patent trolls, in language anyone can follow. Part of the fixpatents.org campaign. (via BoingBoing)
  2. Petabytes of Field Data (GigaOm) — Farm Intelligence using sensors and computer vision to generate data for better farm decision making.
  3. Bullish on Blockchain (Fred Wilson) — our 2014 fund will be built during the blockchain cycle. “The blockchain” is bitcoin’s distributed consensus system, interesting because it’s the return of p2p from the Chasm of Ridicule or whatever the Gartner Trite Cycle calls the time between first investment bubble and second investment bubble under another name.
  4. Hemingway — online writing tool to help you make your writing clear and direct. (via Nina Simon)
Comments: 2

The backlash against big data, continued

Ignore the hype. Learn to be a data skeptic.

Yawn. Yet another article trashing “big data,” this time an op-ed in the Times. This one is better than most, and ends with the truism that data isn’t a silver bullet. It certainly isn’t.

I’ll spare you all the links (most of which are much less insightful than the Times piece), but the backlash against “big data” is clearly in full swing. I wrote about this more than a year ago, in my piece on data skepticism: data is heading into the trough of a hype curve, driven by overly aggressive marketing, promises that can’t be kept, and spurious claims that, if you have enough data, correlation is as good as causation. It isn’t; it never was; it never will be. The paradox of data is that the more data you have, the more spurious correlations will show up. Good data scientists understand that. Poor ones don’t.

It’s very easy to say that “big data is dead” while you’re using Google Maps to navigate downtown Boston. It’s easy to say that “big data is dead” while Google Now or Siri is telling you that you need to leave 20 minutes early for an appointment because of traffic. And it’s easy to say that “big data is dead” while you’re using Google, or Bing, or DuckDuckGo to find material to help you write an article claiming that big data is dead. Read more…

Comments: 6

5 Fun Facts about HBase that you didn’t know

HBase has made inroads in companies across many industries and countries

With HBaseCon right around the corner, I wanted to take stock of one of the more popular1 components in the Hadoop ecosystem. Over the last few years, many more companies have come to rely on HBase to run key products and services. The conference will showcase a wide variety of such examples, and highlight some of the new features that HBase developers have added over the past year. In the meantime here are some things2 you may not have known about HBase:

Many companies have had HBase in production for 3+ years: Large technology companies including Trend Micro, EBay, Yahoo! and Facebook, and analytics companies RocketFuel and Flurry depend on HBase for many mission-critical services.

There are many use cases beyond advertising: Examples include communications (Facebook messages, Xiaomi), security (Trend Micro), measurement (Nielsen), enterprise collaboration (Jive Software), digital media (OCLC), DNA matching (Ancestry.com), and machine data analysis (Box.com). In particular Nielsen uses HBase to track media consumption patterns and trends, mobile handset company Xiaomi uses Hbase for messaging and other consumer mobile services, and OCLC runs the world’s largest online database of library resources on HBase.

Flurry has the largest contiguous HBase cluster: Mobile analytics company Flurry has an HBase cluster with 1,200 nodes (replicating into another 1,200 node cluster). Flurry is planning to significantly expand their large HBase cluster in the near future.

Read more…

Comment: 1
Four short links: 2 April 2014

Four short links: 2 April 2014

Fault-Tolerant Resilient Yadda Yadda, Tour Tips, Punch Cards, and Public Credit

  1. Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing (PDF) — Berkeley research paper behind Apache Spark. (via Nelson Minar)
  2. Angular Tour — trivially add tour tips (“This is the widget basket, drag and drop for widget goodness!” type of thing) to your Angular app.
  3. Punchcard — generate Github-style punch card charts “with ease”.
  4. Where Credit Belongs for Hack (Bryan O’Sullivan) — public credit for individual contributors in a piece of corporate open source is a sign of confidence in your team, that building their public reputation isn’t going to result in them leaving for one of the many job offers they’ll receive. And, of course, of caring for your individual contributors. Kudos Facebook.
Comment

Wearable intelligence

Establishing protocols to socialize wearable devices.

The age of ubiquitous computing is accelerating, and it’s creating some interesting social turbulence, particularly where wearable hardware is concerned. Intelligent devices other than phones and screens — smart headsets, glasses, watches, bracelets — are insinuating themselves into our daily lives. The technology for even less intrusive mechanisms, such as jewelry, buttons, and implants, exists and will ultimately find commercial applications.

And as sensor-and-software-augmented devices and wireless connections proliferate through the environment, it will be increasingly difficult to determine who is connected — and how deeply — and how the data each of us generates is disseminated, captured and employed. We’re already seeing some early signs of wearable angst: recent confrontations in bars and restaurants between those wearing Google Glass and others worried they were being recorded.

This is nothing new, of course. Many major technological developments experienced their share of turbulent transitions. Ultimately, though, the benefits of wearable computers and a connected environment are likely to prove too seductive to resist. People will participate and tolerate because the upside outweighs the downside. Read more…

Comment
Four short links: 31 March 2014

Four short links: 31 March 2014

Game Patterns, What Next, GPU vs CPU, and Privacy with Sensors

  1. Game Programming Patterns — a book in progress.
  2. Search for the Next Platform (Fred Wilson) — Mobile is now the last thing. And all of these big tech companies are looking for the next thing to make sure they don’t miss it.. And they will pay real money (to you and me) for a call option on the next thing.
  3. Debunking the 100X GPU vs. CPU Myth — in Pete Warden’s words, “in a lot of real applications any speed gains on the computation side are swamped by the time it takes to transfer data to and from the graphics card.”
  4. Privacy in Sensor-Driven Human Data Collection (PDF) — see especially the section “Attacks Against Privacy”. More generally, it is often the case the data released by researches is not the source of privacy issues, but the unexpected inferences that can be drawn from it. (via Pete Warden)
Comments: 2