Looker Rolls New Google BigQuery Tools

Addressing the growing need to gain insights from ever-larger data sets, an analytical tool vendor specializing in Google’s BigQuery database is releasing new platform components designed to expand availability and use of the Google platform across the enterprise.

Looker, Santa Cruz, Calif., said Tuesday (Nov. 10) it is following up the release in September of Looker “Blocks” that are compatible with Google BigQuery with new blocks plus other features to connect the analytics tools with the Google Cloud.

As with an increasing number of analytics vendors, Looker is positioning its block tools as a way to expand enterprise access to terabytes of data on Google BigQuery via its in-database architecture.

Like Google (NASDAQ: GOOG), Looker emphasizes scale. The new analytics tools aim to leverage BigQuery’s nearly infinite storage capability and consistent performance in order to elastically scale query-processing power and storage. Those attributes are designed to make it easier to access and churn through massive data sets.

The startup argues that previous analytics tools targeting extremely large data sets are too complicated and slow for use beyond company data scientists. That weakness has forced business users to limit analysis to subsets of data, a practice that encourages information silos across enterprises.

The Looker tools are designed to handle all data in BigQuery rather than extracting subsets of data. The company also touts its tools as being able to leverage BigQuery’s speed in handling the entire database so that results are more widely available.

Hence, the company claims theirs are more than just a data visualization tools that only look at subsets of data.

New components that can be connected to the Google Cloud include a “Table Data Range Analytics” block that leverages BigQuery’s data partitioning capability to speed query performance. That, Looker said, makes it easier to understand event data over time.

A “Query Size Estimator” block can determine the size of a query within Looker’s data platform before it is run as a way to manage database performance.

Lastly, a Google analytics “premium block” divides events into individual sessions for each user. It also includes a suite of web analytics and can be customized with in-house metrics.

The new blocks and analytics tools are available now. Looker said it plans to release additional BigQuery-focused blocks to its software-as-a-service business intelligence platform over the next few months.

Looker launched its data platform in 2012 and claims a growing list of customers that include Uber, container application specialist Docker, Sony and Etsy. Along with Google BigQuery, the platform incorporates integrates with Spark, Impala, Hive, Amazon Redshift, Microsoft Azure DW, Teradata Aster, HP Vertica, IBM dashDB, Snowflake and others.

The startup closed a Series B funding round in March that raked in $30 million.