Continuous Integration Best Practices - Part 2

This is the second part of my blog series on CI/CD best practices. For those of you who are new to this blog, please refer to Part 1 of the same series and for those who want to see the first 10 best practices. Also, I want to give a big thank you for all the support and feedback! In my last blog, we saw the first ten best practices when working with Continuous integration. In this blog, I want to touch on some more best practices. So, with that, let’s jump right in!

The Four Fundamental Ways Data is Changing the Face of Business

You have access to more data than ever before. Are you truly using it to your advantage? And where are you most likely to get results when you do? Businesses around the world are using data to transform every aspect of operations - but some use cases are more powerful, and more profitable, than others.

Big Data. Big Insights. Big Impact.: 8 Tales of Business Transformation

Collecting "big data" was once big news. But companies are realizing that big data projects aren't delivering their expected ROI because building a repository is just part of the equation. Read this eBook to see how Qlik helps organizations like biopharmaceutical company Shire plc, Texas Children's Hospital, online gaming developer King.com, and more gain big insights from big data-for big impact.

Machine Learning Sandbox - Recommendation Engine

Talend’s Big Data and Machine Learning Sandbox is a virtual environment that utilizes Docker containers to combine the Talend Real-time Big Data Platform with some sample scenarios that are pre-built and ready-to-run. This example uses Talend's machine learning capabilities to implement a personalized recommendation model based on user input.

Machine Learning Sandbox - Data Warehouse

Talend’s Big Data and Machine Learning Sandbox is a virtual environment that utilizes Docker containers to combine the Talend Real-time Big Data Platform with some sample scenarios that are pre-built and ready-to-run. This example demonstrates a Data Warehouse Optimization approach that utilizes the power of Spark to perform analytics of a large dataset before loading it to the Data Warehouse.