The Securities Litigation Expert Blog

Tableau Files for IPO

Posted by Jack Duval

Apr 10, 2013 5:38:14 AM

VentureBeat has coverage of the Tableau IPO filing.  (VB)  The S-1 can be found on EDGAR here.  Goldman Sachs will be the lead underwriter.

Revenues have ramped 10X in the past five years.  The company is only marginally profitable, but that is often true of young companies focused on growing revenue and market share.

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Topics: Statistics, analytics, Goldman Sachs, IPO, Tableau, Complexity, Predictive Analytics, Analytic Talent

SEC Using Algos to Detect Fraud

Posted by Jack Duval

Feb 19, 2013 2:51:31 AM

The SEC is using algorithmic methods to analyze financial statements from public companies to detect fraud.  (WaPo)

 (the) software package... will stream real-time trade data from the exchanges into the agency’s headquarters. Rather than build the technology from scratch at great expense, the agency purchased it from a New Jersey firm called Tradeworx. The project, called Market Information Data Analytics, or MIDAS, is in the final testing phases.

The SEC has used similar programs to analyze hedge fund returns.  See our previous coverage of SEC uses of big data techniques here.
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Topics: big data, Statistics, Data Analysis, fraud, litigation, analytics, SEC, Compliance, regulation., Predictive Analytics, Analytic Talent

Talent Analytics for Salesforce

Posted by Jack Duval

Dec 9, 2012 2:19:47 AM

Talent Analytics is a data driven HR/Recruiting company that offers an app that integrates with Salesforce. (TA)  Very interesting stuff for my recruiting friends.  The videos offer a quick introduction to their offerings.

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Topics: Statistics, HR, recruiting, Talent Analytics, Predictive Analytics, Analytic Talent

Real-Time Big Data Could Be Next

Posted by Jack Duval

Nov 29, 2012 3:40:00 PM

This blog post continues our expert analysis of complex investments and their regulation.

The New York Times Bits Section has a nice article on Jeff Hawkins and his ideas on real-time big data analysis.  (NYT)  Here's the crux:

“It only makes sense to look at old data if you think the world doesn’t change,” said Mr. Hawkins. “You don’t remember the specific muscles you just used to pick up a coffee cup, or all the words you heard this morning; you might remember some of the ideas.”

If no data needs to be saved over a long term and real-time data can stream in all the information that is needed, a big part of the tech industry has a problem. Data storage companies like EMC and Hewlett-Packard thrive on storing massive amounts of data cheaply. Data analysis companies including Microsoft, I.B.M., and SAS fetch that data and crunch the history to find patterns. They and others rely on both the traditional relational databases from Oracle, and newer “unstructured” databases like Hadoop.

Much of this will be a relic within a few years, according to Mr. Hawkins. “Hadoop won’t go away, but it will manage a lot less stuff,” he said in an interview at Numenta’s headquarters in Redwood City, Calif. “Querying databases won’t matter as much, as people worry instead about millions of streams of real-time data.” In a sensor-rich world of data feeds, he is saying, we will model ourselves more closely on the constant change that is the real world.

If true, this would be a paradigm shift.
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Topics: big data, analysis, Statistics, Data Analysis, Jeff Hawkins, real-time, Complexity, Predictive Analytics, NYT, Analytic Talent

Women Closing the Gap in Computer Science and STEM Studies/Jobs

Posted by Jack Duval

Oct 2, 2012 3:06:30 AM

Science/Technology/Engineering/Math ("STEM") fields have traditionally been dominated by men.  This is changing.  Women 2.0 has an infographic on how women are catching up quickly to men in the STEM areas.  (Women 2.0).  Some headline numbers:

  • 41 percent of Computer Science majors at Harvard are women

  • That number is up from 28.9 percent just one year ago

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Topics: Women 2.0, Statistics, STEM, Harvard, women, Analytic Talent, education

Data Scientists and the New Cool

Posted by Jack Duval

Sep 30, 2012 4:40:45 AM

Tom Davenport has an excellent mid-lenth piece out in the Harvard Business Review about how data science is the new sexy job.  Tom has been writing about this for quite some time.  (HBR)  Of particular note was his description of the Insight Data Science Program, which is a post-doc Silicon Valley feeder five week training program. (IDSP)

What is clear is that this relatively new discipline is still nascent and does not have a formal academic domain yet.  In truth, that makes it more interesting, as it brings in talent from the whole spectrum of quantitative disciplines.

Here's an excerpt:

What kind of person does all this? What abilities make a data scientist successful? Think of him or her as a hybrid of data hacker, analyst, communicator, and trusted adviser. The combination is extremely powerful—and rare.

Data scientists’ most basic, universal skill is the ability to write code. This may be less true in five years’ time, when many more people will have the title “data scientist” on their business cards. More enduring will be the need for data scientists to communicate in language that all their stakeholders understand—and to demonstrate the special skills involved in storytelling with data, whether verbally, visually, or—ideally—both.

But we would say the dominant trait among data scientists is an intense curiosity—a desire to go beneath the surface of a problem, find the questions at its heart, and distill them into a very clear set of hypotheses that can be tested. This often entails the associative thinking that characterizes the most creative scientists in any field. For example, we know of a data scientist studying a fraud problem who realized that it was analogous to a type of DNA sequencing problem. By bringing together those disparate worlds, he and his team were able to craft a solution that dramatically reduced fraud losses.

Perhaps it’s becoming clear why the word “scientist” fits this emerging role. Experimental physicists, for example, also have to design equipment, gather data, conduct multiple experiments, and communicate their results. Thus, companies looking for people who can work with complex data have had good luck recruiting among those with educational and work backgrounds in the physical or social sciences. Some of the best and brightest data scientists are PhDs in esoteric fields like ecology and systems biology. George Roumeliotis, the head of a data science team at Intuit in Silicon Valley, holds a doctorate in astrophysics. A little less surprisingly, many of the data scientists working in business today were formally trained in computer science, math, or economics. They can emerge from any field that has a strong data and computational focus.


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Topics: data science, big data, Silicon Valley, Statistics, Data Analysis, Insight Data Science Program, Tom Davenport, Harvard Business Review, Predictive Analytics, Analytic Talent, education

CIA Archives on the Tradecraft of Analysis

Posted by Jack Duval

Sep 29, 2012 5:26:23 AM

I just discovered the CIA has a Center for the Study of Intelligence that publishes unclassified research on a quarterly basis.  This is a nice resource of tradecraft ideas for anyone in the forensic analysis business.  The archives go back to 2Q 2008.  Happy reading.  (CIA)

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Topics: Data Analysis, CIA, tradecraft, Analytic Talent, education

Predicting Sporting Events and Presidential Elections

Posted by Jack Duval

Sep 18, 2012 9:20:11 AM

Sports Illustrated had a short but entertaining article on Nate Silver, which can be found here.  Silver is a predictive savant and has been turning his powers to all manner of events.  His political blog can be found here.

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Topics: Elections, Statistics, 538, Data Analysis, Sports Illustrated, Nate Silver, Predictive Analytics, Analytic Talent

Will Algos Replace Data Scientists?

Posted by Jack Duval

Sep 3, 2012 3:49:53 AM

In a Forbes article dripping with irony, the question is asked:  will data science eliminate data scientists?  It seems unlikely to me, although I do believe the lower end of data science will become widely distributed.

You can read the article here.

My worries about AI involve Skynet going live.

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Topics: data scientists, Forbes, Statistics, Data Analysis, Skynet, Predictive Analytics, Analytic Talent

Top Five Cities for Big Data Talent (It's not who you think)

Posted by Jack Duval

Aug 30, 2012 4:29:46 PM

CIOInsight is out with this list.  I'm not sure of the methodology, but it's interesting.  See the piece here.

1. San Francisco

2. McLean, Virginia

3. Boston

4. St. Louis

5. Toronto


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Topics: big data, Statistics, Data Analysis, CIOInsight, Cities, Predictive Analytics, Analytic Talent

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