In the last few years, Python has become the go-to programming language for Data Scientists. In a way, this is kind of surprising. Python was not originally developed to do analytical tasks or data science, but it has evolved to become the ‘Swiss-army’ tool in the Data Scientist toolbox. The reason for this comes from a large number of third-party packages available for Data S...

Introduction I was incredibly excited when Talend finally released a new product called Talend Data Streams that you can access for on free on the AWS marketplace. From day one, I have been testing out a few use cases. <<...

Introduction This month, Talend released a new product called Talend Data Streams. Talend Data Streams was designed for data scientists, analysts and engineers to make streaming data integration faster, easier and more accessible.  I was incredibly excited when it finally released on the AWS marketplace and have been testing out a...

I am very excited to introduce Talend Data Streams, a brand new, cloud-native application that enables you to get streaming data integrations up and running in minutes all while providing unparalleled portability powered by Apache Beam. <<Download Talend Data Streams for AWS Now>> Why Talend Data Streams? One of the biggest challenges that businesses face toda...

Today on July 19, we released Talend Summer ’18, which is jam-packed with cloud features and capabilities. We know you are going to love the Talend Cloud automated integration pipelines, Okta Single Sign-On, and the enhanced data preparation and data stewardship functions…there is so much to explore! Taking DevOps to the Next Level with the Launch of Jenkens Maven Plug-in Support...

In my previous blog, “Talend & Apache Spark: A Technical Primer” I walked you through how Talend Spark jobs equate to Spark Submit. In this blog post, I want to continue evaluating Talend Spark confiurations with Apache Spark Submit. First, we are going to look at how you can map the options in the Apache Spark Configuration tab in the Talend Spark Job, to what you can pass as arguments to Spark Submi...

Many businesses today are scrutinizing their operations to figure out how to join the digital transformation revolution. They understand that to become more competitive and customer-centric, they need processes that are flexible, integrated, insightful and scalable. They understand harnessing data and infusing business processes with it is the key to success. Unfortunately, poor data practices,...

We all know that enterprise data needs change constantly, and recently that change has come at an increasing pace. Companies that were once processing all their big data on-prem have suddenly moved into the cloud. Frameworks we used to know and love suddenly become obsolete.  However, an interesting debate that still rages on is how to get data processed faster. There are generally two heralded ways of processing data today: Batch Processing Stream Processing...

This blog was originally published by Anand Iyer & Jean-Baptiste Onofré [@jbonofre] on the Apache Beam blog...

When it comes to real-time big data architectures, today… there are choices. Today, there is more than just Lambda on the menu of choices, and in this blog series, I’ll discuss a couple of these choices and compare them using relevant use cases.  So, how do you select the right architecture for our real-time project? Let’s get started. Real-Time Requirements Before we dive into the architecture, let’s discuss some of the requirements of real-time data...