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Looker Introduces Enhanced Datafold Engine to Deliver a New Level of End-User Data Exploration and Business Analytics
[February 27, 2014]

Looker Introduces Enhanced Datafold Engine to Deliver a New Level of End-User Data Exploration and Business Analytics


(Marketwire Via Acquire Media NewsEdge) SANTA CRUZ, CA -- (Marketwired) -- 02/27/14 -- Looker, an innovative software company with a next-generation approach to business analytics, today announced its enhanced Looker Datafold Engine, with support for persistent derived tables to deliver faster, more meaningful business insights. Persistent derived tables rely on Looker's in-database architecture to empower data analysts and reduce their workloads. Analysts can now model complex raw data -- quickly and in multiple ways -- without the expensive and time-consuming overhead traditionally required to structure large datasets in advance of analysis. Instead, business users can explore raw data, reset, and dive in again with different parameters, discovering profound insights that are often obscured when using other BI tools.



Existing BI and data discovery products leave businesses blind to events on a granular level because they can't make sense of massive amounts of data, forcing organizations to aggregate and extract data in advance of exploration. This extraction often obscures the data or limits the ability to understand root cause by restricting detailed drilling. As a result, legacy approaches make it impossible to engage in real-time data discovery -- something core to Looker's value proposition, as speed-to-insight becomes more critical to today's data-driven businesses.

The Datafold Engine uses the underlying analytics database to transform raw data at query time, enabling deep exploration of ever-growing and increasingly complex datasets. And while Looker already supports derived tables, the addition of persistence greatly expands the ways derived tables can be used to extract meaningful results. By automatically refreshing tables in specified conditions, persistence conserves valuable computing resources that would otherwise be needed to query the data store. Persistent derived tables also free up precious technical talent for other business-critical projects.


Mindjet Zooms in on Customer Data to Improve Sales ProcessThe enhanced Looker Datafold Engine allows analysts to deepen their understanding of data, streamline the costs typically associated with modeling, create powerful actionable information, and share that information with people who can take advantage -- such as business unit managers, sales staff, and the C-Suite.

Mindjet, a collaborative work management software company in San Francisco, uses Looker to closely track its subscription model and identify where additional products and services would benefit customers. Due to the large amount of event information generated, the company's legacy BI tools didn't enable quick analysis into the details of its subscription sales processes. Mindjet leverages the power of the Datafold Engine to drill into its large datasets on demand, giving its analysts and business users multiple views of the data. Persistent derived tables enable them to quickly ask questions with varying parameters, without having to manually create new tables each time they need a different view of the data.

"Looker allows us to drill down into our subscription information in many different ways," said Jascha Kaykas-Wolff CMO at Mindjet. "This saves us untold amounts of time and provides powerful analytics to help us improve the sales cycle and enhance our marketing efforts." Unlocking Massive Datasets for Detailed AnalysisThe Datafold Engine works in concert with LookML, Looker's flexible modeling environment, to enable analysts to slice and dice large datasets by any combination of dimensions and measures. With a LookML model, anyone can build off of existing queries and define new parameters of the entire dataset -- on the fly -- eliminating the burden of architecting data for cubes and other BI-specific requirements.

The combination of Looker's modern approach to data discovery and its in-database architecture allows data-rich organizations to: Quickly and easily define specific dimensions and metrics Drill into detailed data, zoom out for a larger view, then drill back down in a different way Use a dashboard as a starting point for more involved analysis Access data from any application, using Looker as a general-purpose data server "The Looker Datafold Engine enables the unlocking of massive sets of data and delivers powerful value to today's businesses," said Frank Bien, CEO of Looker. "The result is a new kind of business -- one that shares and collaborates around data and drives curiosity and intelligence throughout the organization." About LookerLooker is an inventive software company with a modern approach to unlocking the value of business data. Looker's web-based business analytics platform powers the work of data analysts while fueling (and fulfilling) the business user's curiosity -- creating a discovery-driven culture throughout the customer's organization. Looker was purpose-built to interact with the next generation of analytic databases, like Amazon Redshift, Amazon RDS, HP Vertica, Greenplum, Teradata Aster, and others. The company was founded by Lloyd Tabb, Principal Engineer at Netscape and former CTO of LiveOps. Investors in Looker include Redpoint Ventures, First Round Capital, and PivotNorth Capital. The company is based in Santa Cruz, CA. You can find more information at www.looker.com.

Press Contact Whitney Akers Email Contact 415-963-4174 Source: Looker

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