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Building a Near Real-Time Analytical Application with Kudu Training Video

Building a Near Real-Time Analytical Application with Kudu Training Video

A Practical Training Course That Teaches Real World Skills

In this project-based Building a Near Real-Time Analytical Application with Kudu video tutorial series, you'll quickly have relevant skills for real-world applications.

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  • A quick grasp of even the most complex Building a Near Real-Time Analytical Application with Kudu subjects because they're broken into simple, easy to follow tutorial videos

Practical working files further enhance the learning process and provide a degree of retention that is unmatched by any other form of Building a Near Real-Time Analytical Application with Kudu tutorial, online or offline... so you'll know the exact steps for your own projects.

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SKU: 02469 | Duration: 1 hours - 7 tutorial videos | Date Released: 2017-03-09
Works on: Windows PC or Mac | Format: Download | Instructor: Ryan Bosshart

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Course Description

Building near real-time analytical applications that combine real-time data inserts, updates, and fast analytics is almost impossible with any single Hadoop storage technology. The introduction of Apache Kudu and the "KIKS" stack breaks through this barrier, making it possible to build near real-time analytical applications that are simple, fast, and reliable. In this course, designed for developers, architects, and engineers with some experience working with common Hadoop components (Kafka, Hive, Spark, Impala, etc.), you'll use "KIKS" to create an app that demonstrates the real-time ingestion, persistence, and visualization of time-series events.

Kudu is at the center of this architecture. It combines real-time inserts, random lookups, and fast analytics into a single storage layer without the need for the complexities of the lambda architecture, making time-series and IOT use-cases much easier to conquer than with previous generation big data technologies. The app you'll build uses real-time financial data, but it also applies to use cases in IOT, retail, manufacturing, and other industries with real-time analytical needs.

* Gain hands-on experience building a powerful near real-time analytical application

* Discover how Kudu combines random lookups and fast analytics into a single storage layer

* See how Kudu eliminates the need for the complexities of lambda architecture

* Understand how the "KIKS" stack works to make apps that are fast, simple, and reliable

Ryan Bosshart is a Principal Systems Engineer at Cloudera, where he leads a specialized team focused on Hadoop ecosystem storage technologies such as HDFS, Hbase, and Kudu. An architect and builder of large-scale distributed systems since 2006, Ryan is co-chair of the Twin Cities Spark and Hadoop User Group. He speaks about Hadoop technologies at conferences throughout North America and holds a degree in computer science from Augsburg College.

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