Interview: Lloyd Tabb, Chairman & CTO, Looker on Front-line Analytics and Data Democratization
We discuss the capabilities of Looker, data democratization across organization, change in the tools being used by analytics-savvy business managers, front-line analytics, competitive landscape and more.

Here is my interview with him:
Anmol Rajpurohit: Q1. First of all, I would like to start with congratulating you for the success of your innovative product. Looker was mentioned in the list of 20 red-hot pre-IPO companies in 2014 B2B Tech by IDG Connect. According to you, what are the top three features of Looker? What other unique benefits of Looker are worth mentioning here?
Lloyd Tabb: Looker is focused on empowering data analysts to share their analytical capabilities across an entire organization.

AR: Q2. Currently, there seems to be a lot of talk but hardly any action around "decentralization and democratization of data across the organization". How do you expect Looker to change this trend?
LT: There’s a saying that insanity is doing the same thing over and over again and expecting different results. At Looker, we’re doing things differently, and we’re driving new and better results. By coupling a web-first interface with a modeling layer that enables a simplified—but complete—end-user view of the data, we’ve been able to effect real change in customer organizations.
AR: Q3. How does Looker help organizations tackle the talent crunch for data scientists? What sort of learning curve is involved here for Business Mangers to get started on using Looker?

The data teams in companies are typically made up of smart folks with brains that gravitate toward numbers and economics. They’re people with innate curiosity and some basic technical abilities. I don't see that changing much. What’s changing are the tools they use.
Looker is very easy to learn for a data analyst—they can learn it in 30 minutes. Business users can learn to query Looker in even less time. No matter what kind of talent you have in your organization, Looker makes your people better and more effective at their jobs.
AR: Q4. How do you define "Front-line Analytics"? Can you share a few use cases of how Looker empowers decision-makers?
LT: Looker can help anyone in the company. In a web world, customer acquisition is a cost and revenue center; tracking customers to

Marketing managers can drive micro-focused campaigns that target very specific customers. For example, they can send an email only to people who have ordered more than 10 times but have not ordered within the last 60 days.
AR: Q5. How do you look at Looker's competitive landscape, particularly companies such as Tableau, QlikView and Birst? What do you consider as Looker's sustainable strategic differentiation?

Looker also takes deep advantage of very powerful databases. We run on Amazon Redshift, HP Vertica, Pivotal Greenplum, and the like. These are huge computational clusters, and our LookML models can see everything in them. The legacy systems you mention have their own data engines that are only looking only at a subset of the data.
AR: Q6. Why do you think it is high time for firms to shift away from the cliche of "Daily Active Users (DAU)" (or similar metrics) and move towards more meaningful characterization of users? What approach would you recommend to analyze event data for business insights?
LT: The problem with Daily Active Users is that it doesn’t really tell you anything about who your customers are. Growth does matter,

When you can measure engagement and characterize your users, you have what you need to build an audience and build a business.
AR: Q7. Data Scientist has been termed as the sexiest job of 21st century. Do you agree? What advice would you give to people aspiring a long career in Data Science?

Don't stop being curious. The job is discovery. The tools will change, but the discovery-oriented way of thinking won't. If you’re the kind of person who gets causation-vs-correlation, then you’re the right candidate for a career in data science.
Helpful majors are econ and computer science (and maybe math or even accounting). You need to be competent at computer science and math, but more crucial is economics—the study of cause and effect.

LT: I like Ben Horowitz's new book The Hard Thing About Hard Things. I love Seth Godin and most of the things he's written. Behavioral economics is an area of intense curiosity for me. When I'm not working, I'm usually thinking about working. I love my work.
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