Take a guy who literally wrote the book on Python programming tools and add some of venture capital’s top investors and you have the recipe for DataPad, a new data discovery technology vendor that just raised $1.7 million.
DataPad was founded in 2013 by Wes McKinney, who wrote “Python for Data Analysis” (believe me, it’s apparently a big deal among Python programmers) and creator of Pandas, and Chang She, who was a core developer of Pandas and a former data science instructor at Columbia University.
Since its launch the two have managed to wrangle $1.7 million in very early stage funding from big name investors including Accel Partners, Google Ventures, a16z Seed Fund, SV Angel, Ludlow Ventures, and angel investors including Jeff Hammerbacher, Tom Pinckney, and Waikit Lau.
“DataPad at its core is a collaborative data discovery tool,” says McKinney. “We are able to pull data into one place and for everyone on a team to access that data and do integration within the product.”
The company’s technology has a visual interface for exploring data sets and building visualizations and pivot tables and highly interactive dashboards, according to McKinney. Those bells and whistles are important for companies that have been under-served by a current crop of mid-priced data visualization and analytics software tools, he says.
DataPad is likely to compete with companies like Tableau Software and others that are offering data visualization and integration tools for business intelligence, says McKinney.
“When you think in the analytics landscape in particular, most people are competing on step two [which is] how fancy are your analytics and how pretty are your charts,” says Accel Partners’ Jake Flomenberg. “What you really find is that a lot of that second step is good enough and the biggest problem is what you do before and what you do after.”
The company currently has eight developers on staff working on its technology and has signed up roughly six companies through its private beta. Thanks to the reputation that McKinney has, there are already 3,000 people waiting to use the product, despite its official launch from stealth today.
Photo via Flickr user Matt Wynn.