Best seller

The Ultimate Hands-On Hadoop: Tame your Big Data!

Udemy
Deal Score+2
Deal Score+2
The Ultimate Hands-On Hadoop: Tame your Big Data
The Ultimate Hands On Hadoop Tame your Big Data

Data Engineering and Hadoop tutorial with MapReduce, HDFS, Spark, Flink, Hive, HBase, MongoDB, Cassandra, Kafka + more!

Product Brand: Udemy

Editor's Rating:
4.6

Udemy Coupon Code for The Ultimate Hands-On Hadoop: Tame your Big Data! Course. Data Engineering and Hadoop tutorial with MapReduce, HDFS, Spark, Flink, Hive, HBase, MongoDB, Cassandra, Kafka + more!

Created by Sundog Education by Frank Kane, Sundog Education Team, Frank Kane | 14.5 hours on-demand video course

Big Data Course Overview

The Ultimate Hands-On Hadoop: Tame your Big Data!

This The Ultimate Hands-On Hadoop: Tame your Big Data! course is comprehensive, covering over 25 different technologies in over 14 hours of video lectures. It’s filled with hands-on activities and exercises, so you get some real experience in using Hadoop – it’s not just theory.

You’ll find a range of activities in this course for people at every level. If you’re a project manager who just wants to learn the buzzwords, there are web UI’s for many of the activities in the course that require no programming knowledge. If you’re comfortable with command lines, we’ll show you how to work with them too. And if you’re a programmer, I’ll challenge you with writing real scripts on a Hadoop system using Scala, Pig Latin, and Python.

You’ll walk away from this course with a real, deep understanding of Hadoop and its associated distributed systems, and you can apply Hadoop to real-world problems. Plus a valuable completion certificate is waiting for you at the end!

What you’ll learn

  • Design distributed systems that manage “big data” using Hadoop and related data engineering technologies.
  • Use HDFS and MapReduce for storing and analyzing data at scale.
  • Use Pig and Spark to create scripts to process data on a Hadoop cluster in more complex ways.
  • Analyze relational data using Hive and MySQL
  • Analyze non-relational data using HBase, Cassandra, and MongoDB
  • Query data interactively with Drill, Phoenix, and Presto
  • Choose an appropriate data storage technology for your application
  • Understand how Hadoop clusters are managed by YARN, Tez, Mesos, Zookeeper, Zeppelin, Hue, and Oozie.
  • Publish data to your Hadoop cluster using Kafka, Sqoop, and Flume
  • Consume streaming data using Spark Streaming, Flink, and Storm

Best Hands-on Big Data Practices with PySpark & Spark Tuning

Best Hands-on Big Data Practices with PySpark & Spark Tuning

Semi-Structured (JSON), Structured and Unstructured Data Analysis with Spark and Python & Spark Performance Tuning

In this Best Hands-on Big Data Practices with PySpark & Spark Tuning course, students will be provided with hands-on PySpark practices using real case studies from academia and industry to be able to work interactively with massive data. In addition, students will consider distributed processing challenges, such as data skewness and spill within big data processing. We designed this course for anyone seeking to master Spark and PySpark and Spread the knowledge of Big Data Analytics using real and challenging use cases.

BigQuery for Big data engineers – Master Big Query Internals

BigQuery for Big data engineers – Master Big Query Internals

A Complete deep knowledge BigQuery guide for Data engineers and Analysts. Hands-On Bigquery via Console, CLI, Python lib

This BigQuery for Big data engineers – Master Big Query Internals course is updated as per latest BigQuery UI and features. This Bigquery course is NOT intended to teach SQL or PostgreSQL. The focus of the course is kept to give you In-depth knowledge of Google Bigquery concepts/Internals. “BigQuery is server-less, highly scalable, and cost-effective Data warehouse designed for Google cloud Platform (GCP) to store and query petabytes of data.”

Who this course is for

  • Software engineers and programmers who want to understand the larger Hadoop ecosystem, and use it to store, analyze, and vend “big data” at scale.
  • Project, program, or product managers who want to understand the lingo and high-level architecture of Hadoop.
  • Data analysts and database administrators who are curious about Hadoop and how it relates to their work.
  • System architects who need to understand the components available in the Hadoop ecosystem, and how they fit together.

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Taught by Frank Kane

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