talk-data.com

This book, "Building Modern Data Applications Using Databricks Lakehouse," provides a comprehensive guide for data professionals to master the Databricks platform. You'll learn to effectively build, deploy, and monitor robust data pipelines with Databricks' Delta Live Tables, empowering you to manage and optimize cloud-based data operations effortlessly. What this Book will help me do Understand the foundations and concepts of Delta Live Tables and its role in data pipeline development. Learn workflows to process and transform real-time and batch data efficiently using the Databricks lakehouse architecture. Master the implementation of Unity Catalog for governance and secure data access in modern data applications. Deploy and automate data pipeline changes using CI/CD, leveraging tools like Terraform and Databricks Asset Bundles. Gain advanced insights in monitoring data quality and performance, optimizing cloud costs, and managing DataOps tasks effectively. Author(s) Will Girten, the author, is a seasoned Solutions Architect at Databricks with over a decade of experience in data and AI systems. With a deep expertise in modern data architectures, Will is adept at simplifying complex topics and translating them into actionable knowledge. His books emphasize real-time application and offer clear, hands-on examples, making learning engaging and impactful. Who is it for? This book is geared towards data engineers, analysts, and DataOps professionals seeking efficient strategies to implement and maintain robust data pipelines. If you have a basic understanding of Python and Apache Spark and wish to delve deeper into the Databricks platform for streamlining workflows, this book is tailored for you.

JavaScript remains the top programming language today with most code repositories written using JavaScript on GitHub. However, JavaScript is evolving beyond just a language for web application development into a language built for tomorrow. Everyday tasks like data wrangling, data analysis, and predictive analytics are possible today directly from a web browser. For example, many popular data analytics libraries, like Tensorflow.js, now support JavaScript SDKs.

Another popular library, Danfo.js, makes it possible to wrangle data using familiar pandas-like operations, shortening the learning curve and arming the typical data engineer or data scientist with another data tool in their toolbox. In this presentation, we’ll explore using the Node.js connector for Delta Sharing to build a data analytics app that summarizes a Twitter dataset.

Talk by: Will Girten

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc