We use cookies, including third-party cookies from Google to serve personalized ads through AdSense, to operate this site and understand how it is used. By continuing to browse, you accept this use. See our Privacy Policy and Terms of Use for details, including how to opt out of personalized advertising.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    Flat editorial illustration: The article contrasts passive follower totals with a behavioral path from attention and trust to cli
    Creator Analytics Beyond Follower Count: Seven Metrics That Measure Audience Behavior
    11 Min Read
    Flat editorial illustration: The article connects AI and marketing analytics with managerial judgment grounded in consumer behavi
    How an Online MBA in Marketing Connects AI and Data Analytics
    11 Min Read
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
    7 Min Read
    chatgpt image jul 21, 2026, 04 34 30 pm
    4 Core Benefits of Predictive Maintenance after Vibration Analysis
    10 Min Read
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Strata 2012: Big Data is Bigger than Ever!
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > Strata 2012: Big Data is Bigger than Ever!
Uncategorized

Strata 2012: Big Data is Bigger than Ever!

Daniel Tunkelang
Daniel Tunkelang
7 Min Read
Strata 2012: Big Data is Bigger than Ever!
Illustration generated with FLUX.2 [klein 4B] via Cloudflare Workers AI.
SHARE

I spent the last three days at the O’Reilly Strata Conference, an assembly of two thousand people focused on data science and its applications. While I’m wary of industry conferences from attending vendor-fests in my past life in the enterprise software world, Strata is an exceptionally good conference. The speakers were a who’s who of data science, including Lucene and Hadoop creator Doug Cutting, search user interface pioneer Marti Hearst, and Google chief economist Hal Varian. You can find the tweet stream for the conference at hash tag #strataconf.

Tuesday

I spent Tuesday in the Deep Data session, billed as a no-holds-barred program for data scientists. My two favorite talks:

  • Claudia Perlich, winner of three KDD cups, talked about using information to pick the right action and to influence people such that they behave in a way that is better for them, better for us, and possibly better for society in general.
  • Monica Rogati, my colleague at LinkedIn and the epitome of a data scientist, delivered a fantastic talk about machine learning models and training data in the real world, extending Peter Norvig‘s point about the “unreasonable effectiveness of data” to observe that more data beats clever algorithms but better data beats more data.

But the most fun that day was the Oxford-style debate featuring Pete Skomoroch, Mike Driscoll, DJ Patil, Amy Heineike, Pete Warden, and Toby Segaran. The question proposed was absurdly Manichean: if you had to hire your first data scientist and could only hire one, would you pick a domain expert or a machine learning expert? After the moderator suppressed some initial attempts to hedge (“both”, “it depends”, etc.), the debaters ripped into the question by taking extreme positions and defending them with gusto. It was a lot of fun, with enthusiastic audience participation and the debaters exploiting their inside knowledge of their opponents’ work histories. In the end, the machine learning side won by a small margin.

More Read

ETL, Data Quality and MDM for Mid-sized Business
ETL, Data Quality and MDM for Mid-sized Business
IBM Drops $1B for Merge Healthcare
3 Technologies That Are Changing How Business Continuity Is Handled
Missed It By That Much
Here Comes Web 3.0: Wolfram|Alpha Launches Today

I then had the good fortune to grab dinner with Marti Hearst and Hal Varian at Xanh – a wonderful mix of great food and conversation.

Wednesday

The Wednesday morning keynote session offered some gems:

  • Cloudera CEO Mike Olson urged big data practitioners to focus on guns, drugs, and oil.
  • Doctor and data geek Ben Goldacre delivered a mesmerizing and disturbing talk about the suppression of inconvenient medical trial results and analytical tools to discover it.

But the person who stole the show was Google’s Avinash Kaushik, who talked about making love with data to find orgasm-inducing actions to change the world and make more money. Unfortunately this was the one talk that was not recorded, but you can read the summary on Avinash’s Google+ page.

As a speaker, I held “office hours” on Wednesday. It was supposed to be a 40-minute slot for conference attendees to come and ask me question. But somehow those 40 minutes extended into three hours of conversation about everything from normalized KL divergence to interview problems — and segued into a reception with specialty big-data cocktails. By the time I got back to my apartment, my voice, brain, and liver were spent.

Thursday

I spent most of Thursday morning in the speaker lounge, recovering from the previous evening and making last touches on my presentation. But I couldn’t resist attending a two-part session on privacy. Indeed, this session was distinctive enough to merits it’s own hash tag: #strataprivacy.

The first part featured O’Reilly’s Alex Howard moderating Intelius Chief Privacy Officer Jim Adler and NYU PhD student Solon Barocas on a panel provocatively titled  ”If Data Wants to Be Free, is Privacy a Prison?” It was a great discussion, and I enjoyed the opportunity to offer my own provocative question through Twitter. Since the panelists were arguing that it was unethical to infer private facts from public data, I asked if they were trying to establish a new form of thoughtcrime.

The second panel, entitled “Pretty Simple Data Privacy“, featured Kaitlin Thaney from Digital Science, Betsy Masiello from Google, and John Wilbanks from the Kauffman Foundation for Entrepreneurship. Given that today was the first day of Google’s new privacy policy, there was no avoiding focus on the associated controversy. I did try to get Betsy to address my charge that Google doesn’t think users own their search history (cf. “Google vs. Bing: A Tweetle Beetle Battle Muddle“), but she said she was unfamiliar with the details of that event. I do wish that someone at Google with more familiarity would respond publicly.

Back to the speaker room after lunch, until my own talk with Samasource’s Claire Hunsaker on “Humans, Machines, and the Dimensions of Microwork“. I’ll post the slides (and there will be a video on the conference site), but the sound bite is that you need to keep crowdsourcing tasks simple, manage the trade-off between task value and difficulty, and watch out for systematic bias.

I wrapped up the conference by hearing William Gunn talk about how Mendeley is disrupting bibliometrics and perhaps the entire academic publishing and reputation ecosystem. I laud his ambition and wish him and Mendeley luck in this quest.

In summary, three days of great talks, conversations, and general enjoyment. My thanks to Strata organizers Edd Dumbill and Alistair Croll for putting together such an outstanding event and for giving me the opportunity to participate.

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Flat editorial illustration: The article contrasts passive follower totals with a behavioral path from attention and trust to cli
Creator Analytics Beyond Follower Count: Seven Metrics That Measure Audience Behavior
Analytics Exclusive
Flat editorial illustration: The article surveys AI finance apps that analyze and explain financial information, sometimes take a
10 Financial Apps Empowered by AI: Assistants and Agents
Artificial Intelligence Exclusive Fintech
Flat editorial illustration: The article links specialist ecommerce SEO agency evaluation to joined-up organic and paid search da
Choosing an Ecommerce SEO Agency When Search Data Drives the Decision
Big Data Exclusive
Flat editorial illustration: The article’s core relationship is that restoring a refrigeration system does not establish trustwor
After the Cyberattack, Can You Trust the Machine?
Artificial Intelligence News

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Online privacy: what’s at stake
Uncategorized

Online privacy: what’s at stake

5 Min Read
Leadership Lessons in Data Quality - Part 1
Uncategorized

Leadership Lessons in Data Quality – Part 1

9 Min Read
Can Big Data Solve the Skill vs. Luck Mystery in Fantasy Sports?
Uncategorized

Can Big Data Solve the Skill vs. Luck Mystery in Fantasy Sports?

11 Min Read
Characteristics of a Social Media Strategist
Uncategorized

Characteristics of a Social Media Strategist

5 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?