The history of Database management systems could be interpreted as a Darwinian evolution process.
The dominance of relational databases gives way to the data warehouses one, which better adapt to the earliest business intelligence requirements; then, alongside the rise of the most popular big data platforms such as Hadoop or spark, comes the era of the NoSQL…
Added by Valeria on December 30, 2019 at 1:00am — No Comments
Added by Stephanie Shen on June 23, 2019 at 7:30am — No Comments
Machine Learning / Deep Learning models can be used in different ways to do predictions. My preferred way is to deploy an analytic model directly into a stream processing application (like Kafka Streams or KSQL). You could e.g. use the …Continue
Added by Kai Waehner on July 8, 2018 at 4:26pm — No Comments
As an individual user, we are no longer living the world of one computer, rather we are living with living and distributed smart devices. Let us first explore a Single-User/Single-Server Architecture that we used in those times, which we survived, without of much hassle either, we still use this architecture most of the time.
A Single user still use to approach a network via a web application with a local front cache, which then allows user to access requested material as per the…Continue
Added by Atif Farid Mohammad on December 10, 2013 at 8:54am — No Comments
Big data analytical ecosystem architecture is in early stages of development. Unlike traditional data warehouse / business intelligence (DW/BI) architecture which is designed for…Continue
The goal is to design and build a data warehouse / business intelligence (BI) architecture that provides a flexible, multi-faceted analytical ecosystem for each unique organization.
A traditional BI architecture has analytical processing first pass through a data warehouse.
In the new, modern BI architecture, data reaches users…Continue
Added by Michael Walker on September 12, 2012 at 11:53am — No Comments