Gaining Insights: Interana ushers the era of data democratization
Back when I was a General Manager at Cisco nearly a decade ago, I was responsible for managing dozens of different product lines—each of which came with inordinate amounts of data. There was data about customers, geographies, pricing, sales linearity, discounting, competitors, market share, and these were just the start. It was a slog to sort through.
Luckily, I had a data analyst on my team whose job was to help me find insights within all that information. Whenever I needed stats about how well a certain product was selling in France versus Germany over a three-month period, I would ask him to crunch the numbers for me. It would usually take him about two to three days to return with answers to my queries—and another three days if I wanted any variation on the data, such as looking at year-over-year sales instead of just three months.
At the time, I thought this process was fantastic. Looking back now, of course, the process seems unreasonably slow, labor intensive, and expensive—not to mention only available to those at large corporations. Plus, the results were only accessible to me, and not to my larger team.
What a difference eight years makes. Today, big data processing speeds are faster than ever and in my opinion, data insights are one of the top three trends we should be watching in 2015. However, a fundamental problem remains: How can everyday businesses actually derive useful insights from massive quantities of data to make better business decisions?
This is where Interana comes in. Founded by three engineers in 2014, Interana provides big data insights to large numbers of people within an organization quickly, easily, and cost effectively. By storing their data in columns, not rows, they’re able to maximize efficiency and have already helped companies like Asana, Bloomboard, and Orange Silicon Valley dig deep into their customer data history, along with beta customers Jive, Sony, and Tinder.
Today, we’re happy to welcome Interana to the Index family. We couldn’t be more delighted to be working with their talented founding team, which includes the dynamic husband and wife duo of CEO Ann Johnson and CTO Bobby Johnson, and Lior Abraham, their head of product vision. Ann comes to Interana from Intel and Bobby from Facebook, where he was responsible for the infrastructure engineering team that helped scale the company from a college networking site to the global behemoth it is today. Lior, another Facebook alumnus, is the mastermind behind the social media giant’s popular internal analytics tool, SCUBA.
In fact, it was SCUBA that first brought Interana to our attention. At Index, we’ve long been interested in the category of analytics and business intelligence—broadly, the notion of making sense of your data—so tools like SCUBA are of intense interest to us. While reading Lior’s blog post, about the tool he created, we learned he was now starting up his own company. We immediately set up a meeting with what’s now the Interana team and fell in love with their idea to bring Facebook-quality insights to all companies, big or small.
What really sets Interana apart is that their solution combines pieces of a product that usually gets separated into different silos. The current standard for big data analysis is for companies to pair a large data warehouse with some kind of graphical technology, and then manually run a long set of scripted queries to get the desired results. Interana has fundamentally gone against the grain of how people think about this system and instead built a fully vertical stack that produces complex visual analyses quickly and inexpensively.
The end result is what we think of as data elasticity. By making it easier for users to analyze key data-driven business metrics—like growth, engagement and conversion rates—in mere seconds, people will continue to use and access the system more and more.
While Interana’s underlying technology is very fancy and cool, what matters most is that it can enable decision makers across a broad spectrum of industries to make better business decisions. We are delighted to be partnering with Ann and Bobby—who, by the way, have been together since studying at CalTech in the 1990s—and Lior have built and continue to refine, and are excited to see how they can further simplify and expand the data-based decision making process.