Digital Transformation & Software Engineering Services

Cascading Lingual Makes it Easy to Migrate Enterprise Data Warehouse (EDW) to a Hadoop Data Lake

In the world of Big Data, companies are increasingly leveraging Cascading Lingual to facilitate the adoption of enterprise Hadoop because it makes it easy for SQL users to utilize their existing skills to quickly create and run applications on Hadoop. Bhushan Pargaonkar, Lead – Technical, explores Lingual’s heritage and the reasons that make it the […]read more »
A photograph of a matrix

Big Data in 2016

Big Data is still an emerging field, with far too many products, promises and pratfalls. Despite all that, this is the season when industry pundits make fearless predictions about how Big Data will evolve in 2016. Many prognosticators take a high-risk approach, titillating the reader with highly speculative projections. If it comes true, the pundit […]read more »

Amazon Redshift: Vendor Lock-In Never Felt So Good

The Hadoop ecosystem has a well-known hole: there is no good tool for near-real time analytics on Big Data. For example, suppose you have 500 milliseconds to calculate the average temperature reading from a set of sensors, based on some ad hoc user-specified criteria such as location, time and sensor type. Pre-aggregation is not feasible, […]read more »