Data Lake

Of all enterprise IT workloads, data-based infrastructure has been the hardest to deliver using a cloud-based deployment model. Data assets are typically the last to move over to a cloud…

The previous blog in this four-part series on Big Data & Kubernetes discussed integration points between Spark and Kubernetes. Let us now consider multiple integration possibilities for Hadoop/Spark with a…

Introduction Even before using Kubernetes for orchestration, the advantages to packaging Big Data applications and their dependent libraries using containers are manifold. A huge bugbear in advanced Big Data &…

Starting this week, we will do a series of four blogposts on the intersection of Spark with Kubernetes. The first blog post will delve into the reasons why both platforms…

In 2018 we are rapidly entering what I would like to call ‘Big Data 3.0’. This is the age of ‘Converged Big Data’ where its various complementary technologies – Data…

“Any enterprise CEO really ought to be able to ask a question that involves connecting data across the organization, be able to run a company effectively, and especially to be…

The first post in this four part series on Data lakes will focus on the business reasons to create one. The second post will delve deeper into the technology considerations & choices around data…

“In God we trust. All others must bring data.” – Dr. Edwards Deming, statistician, professor, author, lecturer, and consultant. The first post in this three part series described key ways in…

The first post in this three part series brought to the fore critical strategic trends in the Wealth & Asset Management (WM) space – the most lucrative portion of Banking. This…

The term ‘Data In Motion’ is widely used to represent the speed at which large volumes of data are moving into corporate applications in a broad range of industries. Big…