Cloudera CCA Data Analyst | 3-day course

Overview

On this accelerated 3-day Cloudera CCA Data Analyst course, you'll get the skills you need to apply traditional data analytics and business intelligence skills to big data.

Your expert instructor will introduce you to the tools and techniques you need to access, manipulate, transform, and analyse complex data sets using SQL and familiar scripting languages.

You'll learn topics such as:

The features that Pig, Hive, and Impala offer for data acquisition, storage, and analysis
The fundamentals of Apache Hadoop and data ETL (extract, transform, load), ingestion, and processing with Hadoop
How Pig, Hive, and Impala improve productivity for typical analysis tasks
Joining diverse datasets to gain valuable business insight
Performing real-time, complex queries on datasets

Access to 24/7 labs means that you can test your hands-on skills in navigating the Hadoop ecosystem whenever you like. Through our unique Lecture | Lab | Review technique, you'll gain Apache Hadoop skills faster.

On this course, you'll prepare for and sit the CCA Data Analyst exam, covered by your Certification Gurantee.

If you're a data analyst, business intelligence specialist, developer, system architect or database administrator, this course is ideal for you.

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Benefits

Other accelerated training providers rely heavily on lecture and independent self-testing and study.

Effective technical instruction must be highly varied and interactive to keep attention levels high, promote camaraderie and teamwork between the students and instructor, and solidify knowledge through hands-on learning.

Firebrand Training provides instruction to meet every learning need:

Intensive group instruction
One-on-one instruction attention
Hands-on labs
Lab partner and group exercises
Question and answer drills
Independent study

Think you are ready for the course? Take a FREE practice test to assess your knowledge!

Free Practice Test

Curriculum

Introduction Apache Hadoop Fundamentals

The Motivation for Hadoop
Hadoop Overview
Data Storage: HDFS
Distributed Data Processing: YARN, MapReduce, and Spark
Data Processing and Analysis: Pig, Hive, and Impala
Database Integration: Sqoop
Other Hadoop Data Tools
Exercise Scenarios

Introduction to Apache Pig

What is Pig?
Pig's Features
Pig Use Cases
Interacting with Pig

Basic Data Analysis with Apache Pig

Pig Latin Syntax
Loading Data
Simple Data Types
Field Definitions
Data Output
Viewing the Schema
Filtering and Sorting Data
Commonly Used Functions

Processing Complex Data with Apache Pig

Storage Formats
Complex/Nested Data Types
Grouping
Built-In Functions for Complex Data
Iterating Grouped Data

Multi-Dataset Operations with Apache Pig

Techniques for Combining Datasets
Joining Datasets in Pig
Set Operations
Splitting Datasets

Apache Pig Troubleshooting and Optimisation

Troubleshooting Pig
Logging
Using Hadoop's Web UI
Data Sampling and Debugging
Performance Overview
Understanding the Execution Plan
Tips for Improving the Performance of Pig Jobs

Introduction to Apache Hive and Impala

What is Hive?
What is Impala?
Why Use Hive and Impala?
Schema and Data Storage
Comparing Hive 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

Apache Hive and Impala Data Management

Data Storage
Creating Databases and Tables
Loading Data
Altering Databases and Tables
Simplifying Queries with Views
Storing Query Results

Data Storage and Performance

Partitioning Tables
Loading Data into Partitioned Tables
When to Use Partitioning
Choosing a File Format
Using Avro and Parquet File Formats

Relational Data Analysis with Apache Hive and Impala

Joining Datasets
Common Built-In Functions
Aggregation and Windowing

Complex Data with Apache Hive and Impala

Complex Data with Hive
Complex Data with Impala

Analysing Text with Apache Hive and Impala

Using Regular Expressions with
Hive and Impala
Processing Text Data with SerDes in Hive
Sentiment Analysis and n-grams in Hive

Apache Hive Optimisation

Understanding Query Performance
Bucketing
Indexing Data
Hive on Spark

Apache Impala Optimisation

How Impala Executes Queries
Improving Impala Performance

Extending Apache Hive and Impala

Custom SerDes and File Formats in Hive
Data Transformation with

Custom Scripts in Hive
User-Defined Functions
Parameterised Queries

Choosing the Best Tool for the Job

Comparing Pig, Hive, Impala, and Relational Databases

Exam Track

On this course, you'll prepare for and take the following exam at the Firebrand Training centre, covered by your Certification Guarantee.

CCA Data Analyst Exam (CCA159)

Number of questions: 8-12
Format: performance-based
Duration: 120 minutes
Passing Score: 70%

What's Included

On this course, you'll receive:

Official Cloudera Data Analyst courseware

Your accelerated course includes:

Accommodation *
Meals, unlimited snacks, beverages, tea and coffee *
On-site exams **
Exam vouchers **
Practice tests **
Certification Guarantee ***
Courseware
Up-to 12 hours of instructor-led training each day
24-hour lab access
Digital courseware **

* For residential training only. Accommodation is included from the night before the course starts. This doesn't apply for online courses.
** Some exceptions apply. Please refer to the Exam Track or speak with our experts
*** Pass first time or train again free as many times as it takes, unlimited for 1 year. Just pay for accommodation, exams, and incidental costs.

Prerequisites

Before attending this course, you should have knowledge of:

SQL
Linux command line
At least one scripting language (e.g., Bash scripting, Perl, Python, Ruby).

You don't need to have experience in Apache Hadoop.

Unsure whether you meet the prerequisites? Don’t worry. Your training consultant will discuss your background with you to understand if this course is right for you.

Reviews

Here's the Firebrand Training review section. Since 2001 we've trained exactly 134561 students and asked them all to review our Accelerated Learning. Currently, 96.41% have said Firebrand exceeded their expectations.

Read reviews from recent accelerated courses below or visit Firebrand Stories for written and video interviews from our alumni.

"Training was very good, explanation was very clear and teacher detailed a lot, so for a 3 day course and to have a first understanding of POWER BI is good."
Rosanna Seerattan Cruz, JTI. (19/3/2024 (Tuesday) to 21/3/2024 (Thursday))

"The instructor and the structure of the course were very clear."
EK, JTI. (19/3/2024 (Tuesday) to 21/3/2024 (Thursday))

"CEH is a very hard training, but it's doable thanks to the friendly employees at Firebrand and the accommodations."
Kas Ramjiawan, ITQM. (4/3/2024 (Monday) to 8/3/2024 (Friday))

"Heavy stuff! Long days and almost no time for some leisure or preparing for exam... I thought there was more hands-on training involved."
MR. (4/3/2024 (Monday) to 8/3/2024 (Friday))

"The course was well structured and concise with a knowledgeable and personable instructor. I will recommend Firebrand courses to all colleagues"
LT. (6/3/2024 (Wednesday) to 8/3/2024 (Friday))

Course Dates

Start	Finish	Status	Location
19/2/2024 (Monday)	21/2/2024 (Wednesday)	Finished - Leave feedback	-
24/6/2024 (Monday)	26/6/2024 (Wednesday)	Wait list	Nationwide
5/8/2024 (Monday)	7/8/2024 (Wednesday)	Limited availability	Nationwide
16/9/2024 (Monday)	18/9/2024 (Wednesday)	Open	Nationwide
28/10/2024 (Monday)	30/10/2024 (Wednesday)	Open	Nationwide
9/12/2024 (Monday)	11/12/2024 (Wednesday)	Open	Nationwide

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Cloudera - CCA Data Analyst