Archive for the ‘Matt Turck’ Category

Deriving Big Value from Big Data

What is Big Data and what does it do to how we do business?  Ask the people doing it.  That’s what Matt Turck, of FirstMark Capital, did at the 28th Data Driven Meetup, which he organizes.  He gave four Big Data stars the mike – two entrepreneurs, a data scientist and a VC who used to be an entrepreneur.  Robbie Allen of Automated Insights, and Joe Hellerstein, of Trifacta, were the entrepreneurs; Rachel Schutt, of Newscorp, was the data scientist, and Chris Lynch, of Atlas Venture, was the VC.

So what are these companies doing?

  • Delivering automated narrative reports of quantifiable data in real time that are designed for individual user groups.
  • Enabling users to easily transform raw, complex data into clean and structured formats for analysis so that analysts can have direct access to Big Data and both analysts and data scientists can be significantly more productive in delivering business decisions.
  • Building a corporate data culture led by a cross-functional team headed by the CTO that combines data science, IT and product management in order to help journalists tell stories and develop a sustainable content/publishing/media company business model.
  • Using lessons learned from running a Big Data pioneer to help new Big Data companies understand the importance of simple messaging that dummies can understand, ease of use, security and designing the business to connect directly to user value in order to optimize monetization, even using someone else’s Big Data platform to achieve this.

Robbie Allen, CEO & Founder, Automated Insights (robbie@automatedinsights.com)

His theme:  Let Your Data Tell Its Story.  His company has developed a patented platform, called Wordsmith, that writes insightful, personalized reports from client data – reports comparable to an expert talking in plain English to each user.  Its cloud software turns raw data into compelling content customized for specific users and groups of users.  It delivers automated insights as narrative content at scale, in real time, on any device.

Visualizations require mental gymnastics to translate.  They also suffer from the baseline effect – small changes are imperceptible, which renders most dashboards useless.  But pictures don’t tell stories.  Words tell stories.  Data density can obscure meaning.  A single word can sometimes do the job best.

Media companies are the target customers for the Wordsmith platform, which creates reports from quantifiable data.

  • The data can come from anywhere – external databases, real-time data, proprietary data, and historical data.
  • The platform creates algorithms that create facts and lists of facts.
  • It then describes those facts as narrative.
  • Creates tweets and other messages

Examples:

  • Yahoo fantasy football grades users on their drafts – using any tone desired, including snarky.
  • InvestCorp – portfolio recap.  (Ultimately data scientists will be replaced b automated processes.)
  • Samsung – fitness update – “quantified self.”
  • Honda – sales reporting

Wordsmith Marketing can generate fully automated personalized websites and performance reports that replace Google Analytics.

Rachel Schutt, Chief Data Scientist, Newscorp

Newscorp owns multiple major news media.  The parent company has begun leveraging all its companies instead of acting as a holding company in order to create new business models based on their content.

Data is at the heart of its future.

Schutt, who has a PhD in statistics, reports to the CTO.  Her two peers are people who head the platform and the product. The goal is to build a data culture, investing in people rather than tools.  They build cross-functional teams, and everyone codes.

Examples of data science in action:  churn models.  Propensity analysis.  User behavior modeling.

The plan is to make data-based decisions to help journalists tell a story and to make sound business decisions that can build a longer term sustainable media business model.

Chris Lynch, Partner, Atlas Venture

Vertica was the first new database in 3 years.  Chris, previously a sales and marketing business entrepreneur, was CEO.  The engineers couldn’t communicate except to data scientists.  He had to simplify the message so it scaled.  Vertica was a real-time analytics database that was faster than others and delivered actionable insights in time to make decisions It was sold to HP for several hundred million dollars.  But Zynga was sold for billions.  Zynga was an analytics company that masqueraded as a gaming company.  It used Vertica’s real-time database to analyze user behavior and target sales of virtual products.  Vertica was disintermediated.  You need to be close to the customer for monetization – to connect directly to customer value.

Chris has been a VC for two years.  His thesis is that big data can be transformational if democratized so that it talks to dummies, not the 1 percent.  Scale, security and simplicity are issues.  Individuals will own their own digital footprints.  Simplicity means ease of use so the magic is behind the curtain and users have an intuitive interface.

Think about monetizing someone else’s platform.  Disintermediate those guys.  Leverage the apps an platforms you can put under a problem.  What’s the problem you’re solving? Moving up the stack creates more value for the customer.

What he looks for in a company is people with courage, character and conviction – people with a soul.   You need people to build stuff.

The venture model is broken.  Too much money in the market (Lazy VCs).  Too few good ideas.  Chris takes pride in being a company builder.

Joe Hellerstein, Founder & CEO, Trifacta

Trifacta has developed a platform designed to “transform the way the world works with data.”  It is designed to make it easy for analysts to have direct access to Big Data and to increase productivity for both analysts and data scientists.  They asked analysts what they did and how long it took and found that 80 percent of the work on data is cleaning data.  So, Trifacta takes raw logs and transforms them for immediate analysis.  Joe demonstrated this, transforming a typical log of restaurant violations in minutes into a straightforward list of where not to eat in San Francisco!