From the beginning of Looker, reusability has been at the core of our product philosophy. It started with reusability around SQL queries, and today we are targeting reusability with Data Apps. We have long observed that the best new tech companies are building on top of Looker--literally. At first, these uses of Looker would come to us as a surprise. We never imagined, for example, that someone could get any insight in Looker without actually “looking” at the data. Until, of course, someone actually did exactly that-connecting Amazon Echo to Looker so they could yell questions and get answers (they sent us an awesome video of it!).
Our customers are constantly creating and using Looker in new and incredibly powerful ways to make their jobs and lives better. With Data Apps, we’ve taken everything we’ve learned from our customers and created applications that make data more accessible and useful for everyone in every department. This means that everyone can benefit from the best frontier minds. A functionality built by one smart team can be realized across other teams with similar business problems.
I remember my early days at Looker nearly two years ago: we already had all the basic LookML concepts: views, explores, dimensions and measures. While that was enough to get our customer to basic explorations, the team here was driven to get deep insights that our customers would not uncover anywhere else. To do that, we came up with much more complex LookML patterns. It made us look very technically proficient, but we knew there was a better way to learn from each other, than to crawl github repos to find the best logic for a funnel analysis.
To solve this, our founder, Lloyd, created Learn. Learn is a Looker instance that supports the embedding of Looks, explores, and LookML models, right within the Looker product. But more importantly, it gave all of us at Looker a place to share and annotate analytical patterns.
Ultimately, these analytical patterns were turned into Blocks, a godsend for any analyst. Finally there was a way to represent generic code, allowing customer to re-use generic pieces of a model and have this code work seamlessly alongside the rest of the model.
However, blocks are meant as resource for a technical analyst. Using the above analogy for git repos, with blocks you still have to search through repos of models and then you need to tie them up with the rest of your LookML model. What we didn’t have was an easy way to tie blocks together and deploy them as an end to end solution.
Looking across customer use-cases today, while Looker continues to be a data discovery tool, we also see that entire departments run sometimes solely on Looker - be that in operations, sales or financial risk management. We’ve created APPS to address the needs of these types of data driven teams. For the first time, a VP of sales expecting a standard core functionality throughout a daily routine, can rely on Looker to be the platform to execute all these functions around the company’s data--at least, in so far as data goes.
This brings us to the future. When major thinkers from Silicon Valley come together, they often talk about what technologies will dominate 10 years from now. Today the conversations increasingly touch on electric vehicles (Tesla), self-driving cars (Google, Uber), and private space shuttles (Jeff Bezos' Blue Origin, Elon Musk’s SpaceX). I want to now focus on the later.
In 1998 we saw the launch of the first piece of International Space Station called Zarya. It was an amazing accomplishment for all of us on Earth. Continued flights have delivered many more modules and have expanded this platform. But more importantly, the platform helped build the US Space Shuttle program and allowed us to reliably bring astronauts back to earth.
As we launch Data apps today, in some ways we are only launching the first module. We are well aware that we don’t know all the use cases that are out there. While we have seen all kinds of businesses, there remain business problems that we probably have not even heard of. And yet it does not matter, because we’ve just launched something much larger. Our new platform will allow the next Elon Musk to build her own shuttle. And we can’t wait to see more of our customers succeed.