Sep 2016

Going beyond Data Lakes

We often see customers start to build data lakes on Hadoop or S3 as way to get their transactional data with dimensional data in a common place. This data is cleaned and organized in a star schema like in an enterprise data warehouse. The challenge begins here since consuming data in a Hadoop data lake is not easy. The first challenge is ad hoc analytics....

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Jul 2016

Terabyte scale Data Lake analytics on S3, Hadoop with Spark

In our recent work with customers, there is one constant. The need to make sense of terabytes of fact and time-series data that lands in the datalake( Physically S3 or HDFS). Here is a typical process before we get engaged.  The first step in this process is organizing data in the datalake. A typical fact table for our customers, such as events of all advertising-exposures...

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Jun 2016

Fast B.I on Spark SQL

A typical slice and dice query on a database has the following pattern. On large datasets, the response for such interactive queries have to be in the order of 1 or 2 seconds as users navigate across different Tableau worksheets or choose filters on their web application. A standard in-memory solution may be suboptimal for such slice and dice queries. First, caching large amounts of data...

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May 2016

Analyzing a billion rows with Tableau

“How do I make Tableau go against a live table with 100+ million rows and perform ad hoc queries on various slices of data”. This is a question we get often from data teams across all industries. With growing data across Hadoop, Oracle, Teradata – whatever be the environment, the need to do dimension analysis on the data in an ad-hoc manner with timely responses is...

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Apr 2016

Fast BI – A new approach

Business Intelligence is the heart of all analysis at enterprises. Data, that is collected about business events and metrics have to be organized and analyzed to glean business insights and the industry around data warehousing and visualization of trends and metrics is enormous. But as data has grown, the tools and technologies to analyze the data have not kept pace. While tools like Tableau are...

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