Looker, a player in the self-serve data discovery market, announced key product updates that will help the two-year-old company continue its momentum as it moves upmarket after a year of 300 percent growth. The updates include better visualization capabilities, easier in-browser application development for the data analysts curating their companies' datasets, and integration with enterprise-level databases.
With the new release, Looker will be able to work with enterprise-level databases such as HP Vertica, Teradata and Aster, and Oracle. "We're seeing a pull into larger organizations," Looker CEO Frank Bien says. Looker will also be able to support two-factor authentication, moving it toward the type of security large enterprise have in place, especially for financial data. "Folks are putting this on top of their core treasure of data, not just clickstream data, but financial data," Bien explains. While Looker has had early traction among e-commerce companies such as Gilt and Hotel Tonight, according to Bien the company has always planned to target "the organizations that had the most complex kind of data...the pipeline is now filling with everything from banks to large brick-and-mortar companies," he explains.
Another product update that will be a key selling point is the improved ability to visualize data. A new visualization framework will let users import visualizations from open sources. Looker will now also come preloaded with graphs from the D3 visualization library, a "well-regarded environment for displaying data," Bien says. Users will be able to look at and compare data better. With the tool, "there is preservation of drill paths," allowing users to easily pick up where they left off after creating a specific slice and comparison of data that might be difficult or time-consuming to re-create. "We also introduced this notion of cross-drilling, where you can drill across to another dashboard, freely exploring what would be separate systems. In Looker, that's one cohesive world."
For the data analysts that manage the self-service business intelligence for their company's employees, Looker has improved the development experience for these data scientists, who use the language LookML to create consistent parameters for their data sets. That means a company can have a consistent definition for complex calculations such as "lifetime value" across an organization. Looker is also built to "allow analysts to build things without knowing what questions the end users are going to ask," freeing them up from constant data requests by enabling end users to do those tasks themselves.
Bien has noticed that Looker is being used to do more complex analysis of Salesforce.com data, which is traditionally weak in analytics. "Salesforce.com is everywhere, even in larger companies. They have sophisticated implementations of Salesforce.com, but internal analytics isn't keeping up," Bien observes. Some Looker clients are dumping all their Salesforce.com data into Amazon Redshift, and then analyzing the data there.
Clients are also using Looker to explore data from marketing automation tools such as Eloqua and Marketo, as well as Zendesk, which Bien is seeing "widely deployed in all kinds of organizations, like Salesforce.com." Looker clients can marry data from CRM, marketing automation, and customer service systems, and then combine that with machine data about how people may be interacting with sites."We're getting to this holy grail where people are combining machine and event data," Bien sums up.