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Strata Data Superstream Series: Creating Data-Intensive Applications

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MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 7 Lessons (3h 37m) | Size: 3.14 GB

As the scale of data continues to grow (alongside an ever expanding ecosystem of tools to work with it), developing successful applications is an increasingly challenging proposition—and a necessity. At each stage of the process, from architecting to processing and storing data to deployment, there are a range of aspects to consider. Things like scalability, consistency, reliability, efficiency, and maintainability. It can be hard to figure out the right way forward.

In this event, you’ll gain insight into design and engineering best practices through interactive sessions and live coding demos. Join us to learn how to make the right decisions for your applications.

About the Strata Data Superstream Series: This four-part series of half-day online events gives attendees an overarching perspective of key topics that will help your organization maximize the business impact of your data.

What you’ll learn-and how you can apply it

Learn how to build, scale, and test robust data pipelines
Get an overview of next-generation technologies for developing underlying data architectures
Explore design considerations to make your applications successful and reliable
Understand how to ask the right questions when developing ethical data products
This Superstream is for you if…

You need to know the latest trends in data workflows, techniques, and tools.
You want to improve the scalability, reliability, security, and maintainability of your applications.
You want to better understand the systems you already use and the distributed systems on which modern databases are built.
You want to learn the best ways to integrate data governance and ethical data practices into your applications.
Prerequisites

Come with your questions
Have a pen and paper handy to capture notes, insights, and inspiration

Strata Data Superstream Series: Creating Data-Intensive Applications

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