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EIEIO / DATA SCIENCE

Cloudera Data Analyst

Course outline

4 days
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Duration

4 days

Course Overview

Cloudera is one of the biggest names in the field of Data Analytics. They offer services particularly in the Big Data domain and considered one of the key players. Cloudera Certified Data Analyst (CCA 159) is a foundational exam in mainstream Big Data tools i.e. Apache Hive and Apache Impala. You will start by delving into Hadoop and its distributed file system. Next, you’ll become well-versed with the most common Hadoop commands you'll need to work with Hadoop file systems. Later, you’ll explore the Apache Hive, starting with an introduction to it, before moving on to understanding external and managed tables. The next few sections will take you through insert and multi-insert. As you progress, the course will provide insights into different functions such as collection, conditional, Hive string functions, Hive date functions, and mathematical functions. In addition to this, you’ll learn to work with different file formats and compressions.

By the end of this course, you’ll have comprehensive knowledge of Hive and Sqoop and gained the skills you need to pass the CCA Data Analyst Exam

Outline

Introduction to Cloudera Data Analyst

Introduction

  • Apache Hadoop Fundamentals
  • Introduction to Apache Hive and Impala
  • Querying with Apache Hive and Impala
  • Common Operators and Built-in Functions
  • Data Management
  • Data Storage and Performance
  • Working with Multiple Datasets
  • Analytic Functions and Windowing
  • Complex Data
  • Analyzing Text
  • Apache Hive Optimization
  • Apache Impala Optimization
  • Extending Apache Hive and Impala
  • Choosing the Best Tool for the Job
  • Apache Kudu

Apache Hadoop Fundamentals

  • The Motivation for Hadoop
  • Hadoop Overview
  • Data Storage: HDFS
  • Distributed Data Processing: YARN, MapReduce, and Spark
  • Data Processing and Analysis: Hive and Impala
  • Database Integration: Sqoop
  • Other Hadoop Data Tools
  • Accessing the Exercise Environment and General Notes
  • Hands-On Exercise: Starting the Exercise Environment
  • Exercise Scenario
  • Hands-On Exercise: Data Ingest with Hadoop Tools

Apache Hive and Impala

  • What Is Hive?
  • What Is Impala?
  • Why Use Hive and Impala?
  • Schema and Data Storage
  • Comparing Hiva and Impala to Traditional Databases
  • Use Cases

Querying with Apache Hive and Impala

  • Databases and Tables
  • Basic Hive and Impala Query Language Syntax
  • Data Types
  • Using Hue to Execute Queries
  • Using Beeline (Hive's Shell)
  • Using the Impala Shell
  • Hands-On Exercise: Running Queries from Shells, Scripts, and Hue
  • Exercise Review: Running Queries from Shells, Scripts, and Hue

Programme scope, delivery arrangements and suitability are confirmed during enquiry.