If you missed it, you can find an excellent overview of the market’s direction and Looker’s upcoming plans in Frank Bien’s latest blog.
This was my first time attending JOIN, and I was most impressed by by the open, informative dialog between the guests and Looker staff regarding the future direction of the Looker data platform. Nowhere was that more apparent than at the “Product Wall” where attendees were invited to vote on new features and capabilities they’d like to see added to upcoming releases of Looker.
Amazingly, nearly 1,000 individual feature suggestions and votes were submitted!
Highlighted on the Product Wall this year were a series of Looker Blocks, each focused on various topics and use cases. The Looker team was interested in gauging user interest in these types of Blocks and measuring what attendees considered most important.
If you’re not familiar with Blocks, you really should check out the Block Directory for details. You’ll find that you can leverage pre-built segments of Looker functionality to powerfully accelerate your analytics.
After two days of voting, a few of the highlights included:
Google Sheets Actions. Looker Actions allow users to perform tasks via pre-defined API calls to nearly any other application all from a single Looker interface. A frequent request at JOIN was for Looker to perform common tasks such as reformatting cells or changing cell values in Google Sheets, from within the Looker interface - and without having to open Sheets directly. Sheets integration overall remains popular with the Looker community, and Looker works well with sheets already, both as a data source and a way to export results. If you’d like to learn more about the ways Looker works with Google Sheets, one of our experts has compiled a list.
Most requested source block: Jira. An overwhelming majority of attendees requested Looker build a LookML model for Atlassian Jira. In particular, requesters were asking for help in tracking software development metrics in a simple dashboard. Several were already using the power of the Looker data platform to do this analysis on their own, but having a Source Block would be very helpful. Interestingly enough, the Looker team is already working on Jira integration, so look for this in future releases.
Data Blocks with international/global data sets. Data Blocks, coming soon to the Blocks Directory, are pre-modeled external data available to Looker users. Reflecting the increasingly global nature of the Looker community, commonly requested Data Blocks included international data sources. Among the suggestions were global demographics, international financial data, EU and Asian data sources, and a number of others. Of course, the flexibility of the Looker platforms allows data teams to import data from existing public data sources today, but if there is a set of data that’s widely requested, the Data Blocks team will determine when (and if) it’s appropriate to add that data as a Block.
On a more personal note, I was lucky enough to assist the attendees with the voting. This gave me the opportunity to chat with them as they reviewed the board and provided their feedback.
Thanks again to everyone who took the time to help Looker understand your needs. With your input we can continue to build you a better data platform into the future!
PS: Don’t forget to check out the all new features in Looker 5!