In 2011, Pope John Paul II was beatified, Prince William married Kate Middleton, "Game of Thrones" premiered, and Xplenty was born. On a quiet sycamore tree-lined street in Tel Aviv, Israel, breathing distance from Kiryat Sefer Park, the then-startup had just launched a game-changing Extract, Transform, Load (ETL) tool to process, transform, and move data at speed and generate big data analytics at scale. It would become the most advanced data pipeline platform on the planet.

With 9.5, we've focused on providing new capabilities and enhancements for everyone involved in the data to design workflow - analysts, developers, users - that streamline processes, introduce functional improvements and enrich the analytic experience for all. For the full list of updates, please read the release notes and check out our release highlights video below to see some of these new enhancements in action for yourself.

Automated testing for web apps has been around for well over a decade. For much of that time, Selenium has reigned supreme as the go-to testing framework for virtually any type of testing need that involves a browser-based app. But as the world of test automation continues to evolve, newer tools have emerged. Chief among them is Cypress, a testing framework that is becoming an increasingly popular alternative to Selenium. Is Selenium or Cypress a better choice for your automated testing needs?

Our obsessive focus on customer success is at the heart of all things we do.

We’ve partnered with SEMrush to remove API limitations for Databox users so you can track your SEO metrics for you (and your clients) without hassle.

13 more integrations have been updated to support custom date range functionality in Databox.

It’s been a real pleasure to work with Huawei — both for the first and the second time. Now, we wanted to go even further by bringing you another amazing Verified Step to make your life even easier. Introducing the Huawei AppGallery Connect Reports Step. ✨ Let’s see how can it help you!

Cloud Dataprep by Trifacta is Google Cloud’s intelligent data service for visually exploring, cleaning, and preparing structured and unstructured data for analytics and machine learning. Due to its serverless architecture, Dataprep does not need any infrastructure to deploy or manage, and is fully scalable.

Onboarding institutional clients is one of a financial services institution’s most critical functions, with direct implications for client experience, servicing, and relationships, that all significantly impact profits. What’s at stake during the onboarding process? Client loyalty, experience, referrals, and profitability. How many touch points across departments—front office, operations, risk, legal, credit, compliance, tax—can potentially elongate the onboarding process?

As companies grow and become more data-dependent, data engineers find themselves in huge demand. Employers are snapping up all the best data engineering talent they can find, and some businesses have invested in fast-track professional development paths for DBAs and other more junior data positions. But here’s the thing — data engineers work best when they’re part of a balanced team, just like every other professional. Some organizations overlook this point.