As of late, it’s no secret that conventional enterprise intelligence (BI) is evolving. With the rise of embedded analytics, enterprises in all places are starting to hunt out alternatives to enhance their day-to-day workflows with real-time insights. These data-augmented workflows are what Looker calls “knowledge experiences”.
A few of these experiences are straightforward to determine and implement: perhaps it’s so simple as embedding an analytics dashboard inside an present SaaS utility, like Salesforce or Zendesk. Or an organization might resolve to monetize their analytics by embedding a Looker dashboard inside their very own product, enhancing the worth of the product for customers.
However a few of these alternatives might come from embedding knowledge even deeper into functions, in order that insights can be found the second a information employee must decide. These deeper forms of experiences are the place we expect Looker really shines as a platform.
Looker’s strategy to embedded analytics is to make it simpler for our prospects to proceed to construct, adapt, and lengthen their very own knowledge experiences by integrating knowledge even deeper into their operational workflows. We additionally need to make it potential for extra of our prospects to construct these customized knowledge experiences by creating wise however versatile abstractions for builders.
Analytics as Reusable Parts
Looker dashboards are integral to the product, offering a strong interface to view, work together with, and dive deeper into your knowledge.
However knowledge consumption through dashboards is actually only one use case for knowledge. There are different knowledge experiences obtainable on the Looker platform, akin to exploration, navigation, knowledge curation, and even taking motion in your knowledge that we will make simpler for our prospects to construct.
Traditionally, constructing these experiences had been difficult, primarily as a result of most of those experiences required a totally customized font-end to be constructed from the bottom up. And generally, the period of time and sources a customized front-end on our API is prohibitive.
