Month: July 2017

Data Model Design & Best Practices – Part 2

  What is a Data Model?  As Talend developers, we see them every day, and we think we know what they are: A structural definition of a business system data  A graphical representation of business data  A data foundation upon which to build business solutions  These may all be true statements, but for a moment […]

Running Data Preparations on your Data Lake with Talend and Apache Beam

  You may have seen recently that the first stable version of Apache Beam (v.2.0) was recently released. Apache Beam is an advanced unified programming model designed for batch and streaming data processing. It’s extremely powerful and portable which is why we’ve been actively contributing to the project since the very beginning. Recently, we’ve integrated […]

Is Your Data Integration Platform Container Ready?

  Docker Containers are widely used and becoming even more prevalent as companies seek to streamline their operations.  Containers help decouple compute resources from applications, increasing the elasticity and hence the efficiency of IT operations.  DataDog reports that Docker usage has grown 40% over the past year, 18.8% of the DataDog sample customers use Docker.  […]

The Reality of the Artificial Intelligence Revolution

  According to Gartner, over 85% of customer interactions will be managed without a human by 2020. We have seen a machine master the complex game of Go, previously thought to be the most difficult challenge of artificial processing. We have witnessed vehicles operating autonomously, including a caravan of trucks crossing Europe with only a […]

Talend Summer ’17: What’s New in Self-Service Apps? (Part 2)

  In Part 1 of this blog series, I presented the benefits that Talend Data Preparation 2.1 (Summer ’17) delivers: in particular, an unmatched level of industrialization for IT and the integration of data preparations to any type of Big Data scenario – batch or streaming. In part 2, I’ll review the major new features we’ve added […]