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Google boosts BI chops with new Looker features, roadmap

Google boosts BI chops with new Looker features, roadmap

looker-dashboard.png

Looker has revamped its core dashboard capabilities


Credit: Looker

Modern business intelligence (BI) provider Looker, at its JOIN@Home online conference today, will announce important new features that bring it more to parity with longer-established self-service and enterprise BI platforms. Now that Looker is firmly on-boarded and an important part of Google Cloud, the time is right to shore up its enterprise BI credibility.

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Dashboards on the big screen, apps on the small one

First off, Looker has improved its dashboard facility, adding cross filtering capabilities. Cross-filtering allows users to click on particular data elements in one visualization in order to filter the data used by the other visualizations. It makes dashboards more interactive and better able to work as entry-level discovery interfaces, before users drill down to more sophisticated, dedicated analysis views. The figure at the top of this post shows a Looker dashboard created with the new authoring platform.

Next, Looker is introducing its first native mobile apps. While Looker’s Web interface was fully responsive and mobile-friendly before, the mobile apps for iOS and Android will likely provide a more enticing, lower-friction interface for corporate BI users. Mobile BI apps are great for conveying key performance indicators (KPIs) and high-level data visualizations. Most of Looker’s major competitors have had mobile apps for years, and so the time was right for Looker to get that capability out to its users.

Enabling developers

Looker is also beefing up its developer story, another critical pillar for a successful business intelligence platform. To begin with, Looker is adding to its previously announced Extension Framework, which allows application developers to create components that can be located within the Looker environment. Looker is publishing its own extension for entity relationship diagrams, which can be used to visualize data models.

For developers who want

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