Systems | Development | Analytics | API | Testing

As organizations run more data applications and pipelines in the cloud, they look for ways to avoid the hidden costs of cloud adoption and migration. Teams seek to maximize business results through cost visibility, forecast accuracy, and financial predictability. Watch the breakout session video from Data Teams Summit and see how organizations apply agile and lean principles using the FinOps framework to boost efficiency, productivity, and innovation. Transcript available below.

As DataOps moves along the maturity curve, many organizations are deciphering how to best balance the success of running critical jobs with optimized time and cost governance. Watch the fireside chat from Data Teams Summit where Mark Sear, Head of Data Platform Optimization for Maersk, shares how his team is driving towards enabling strong engineering practices, design tenets, and culture at one of the largest shipping and logistics companies in the world.

Customers can realize the same fully-managed experience they have with our standard connectors and bring all their data into one platform.

Once in a while I stumble upon Spark code that looks like it has been written by a Java developer and it never fails to make me wince because it is a missed opportunity to write elegant and efficient code: it is verbose, difficult to read, and full of distributed processing anti-patterns. One such occurrence happened a few weeks ago when one of my colleagues was trying to make some churn analysis code downloaded from GitHub work.

Puppeteer is a powerful Node.js browser automation library for integration testing and web scraping. However, like any complex software, it comes with plenty of potential pitfalls. In this article, I'll discuss a variety of common Puppeteer mistakes I've encountered in personal and consulting projects, as well as when monitoring the Puppeteer tag on Stack Overflow.

1. Data pipelines can improve data management strategies by enabling quick and easy data flow, transformation, and analysis. 2. Considerations when building a data pipeline include real-time data ingestion, scalability, performance optimization, data security and governance, and support for multiple sources. 3. Data mesh is a decentralized data architecture that organizes data sources by their specific business domains and must comply with the principles of the architecture. 5.

The internet was written in JavaScript. This versatile programming language is supported by all major web browsers and has been used to create over 1.8 billion websites, which amounts to 98% of the world’s total (that figure will probably have jumped a few thousand by the time you finish this article). Developers love JavaScript for the dynamic web pages it empowers them to build, with a whole bunch of interactive elements and user interfaces available on a drag-and-drop basis.

If you want to create a website, you might have heard of WordPress. It has been one of the most highly recommended content management systems (CMS) since its creation in 2003. Over the years, it has become one of the world’s most popular website publishing software. That is also why it has millions of fans and is responsible for powering about 42.9% of all websites worldwide.

Let’s make the transition together.

SAST and DAST both help to ensure that your software is secure and safeguarded against vulnerabilities. This makes the DevSecOps process easier. Here, we explain the difference between SAST vs DAST to help you better understand when you should use each one.