This content, written by Keenan Rice, was initially posted in Looker Blog on Jan 13, 2015. The content is subject to limited support.
The most exciting part of my job at Looker is seeing firsthand how some of the most innovative tech companies think about data, continually using it to compete against established traditional players. Each of these emerging companies know from the outset that data is their most strategic competitive weapon in the 'David and Goliath' scenario they face in their markets. Why? It's easy to collect, effective to utilize, and the tools to do so are pervasive; almost everyone runs Google Analytics, Adobe Site Catalyst, Mixpanel, or something similar.
While these tools are easy to use and can get you from 0-60 quickly, their ease-of-use comes from the tight control these apps impose over what you can do with the data they collect. The downside of that tight control is a lack of flexibility, leaving a lot to be desired when a company is ready to do more comprehensive analytics with these data sets.
The best companies understand these limitations and have begun to pioneer new approaches to going beyond them. Instead of letting a single software vendor decide the entire package - data collection strategy, data movement scripts, architecture and databases, and visualization layers - they’re taking advantage of all the innovations in these spaces and putting the pieces together themselves.
While the build-it-yourself approach is an age-old philosophy, in the world of Web Analytics it was almost impossible to do economically until recently. Now we see modern web analytics workflows being created all the time, using best-of-breed technologies like those developed by Amazon Web Services: EMR, Kinesis, Data Pipeline, and most importantly, Redshift. The best part is that these products can be put together, deployed, and operationalized for less time and cost then it would take to implement something like Adobe Site Catalyst.
When decided to announce an offering that enabled any customer to collect, store, and access their customer and web analytics data through a hosted AWS Redshift connection we wanted to be part of it. It's an approach that gives customers an easy way to build their own analytics stack, reaping the benefits of a build-your-own approach without needing to have the technology expertise in house. With access to this data, organizations are now open to a whole new world of business intelligence and analytics platforms - especially Looker.
If you’re seeking a customizable and flexible substitute for the existing Web Analytics providers, your deployment is only going to be as good as the ability to explore, transform, and visualize the data you’ve collected into your powerful new Redshift instance. This is where we saw a very exciting opportunity to partner with the team at Segment and build a joint solution. What we developed enables organizations to do everything they'd want to do in one of their existing web analytics solutions, plus infinitely more types of analysis, completely customizable to any business.
A discovery-oriented analytics application. Looker’s approach to analytics enables anyone in an organization to put together infinite permutations of fields (measures or dimensions) to build dynamic SQL queries and find the insights they need to drive the business - without waiting for someone to write a SQL query or publish a report.
A pre-built environment for Segment SQL data. Dashboards and a LookML model have been already been built off of the core dataset that every Segment implementation collects. Immediately explore insights on sessions, events, users, and pages.
Flexible customization for any organization. From the base model data analysts can easily add in their custom event tables, dimensions, measures, reports, and dashboards that give them the data they need to effectively analyze their unique business.
Take your analytics to the next level with Looker and Segment SQL. for a free trial of the Looker + Segment SQL solution.