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Cloudera - CCA Data Analyst

Duration

Duration:

Only 3 Days

Method

Method:

Classroom / Online / Hybrid

Next date

Next date:

28/9/2020 (Monday)

Overview

On this accelerated 2-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.

Seven reasons why you should sit your course with Firebrand Training

  1. Two options of training. Choose between residential classroom-based, or online CCA Data Analyst courses
  2. You'll be CCA Data Analyst certified in just 3 days. With us, you’ll be CCA Data Analyst trained in record time
  3. Our CCA Data Analyst course is all-inclusive. A one-off fee covers all course materials, exams, accommodation and meals. No hidden extras
  4. Pass CCA Data Analyst first time or train again for free. This is our guarantee. We’re confident you’ll pass your course first time. But if not, come back within a year and only pay for accommodation, exams and incidental costs
  5. You’ll learn more. A day with a traditional training provider generally runs from 9am – 5pm, with a nice long break for lunch. With Firebrand Training you’ll get at least 12 hours/day quality learning time, with your instructor
  6. You’ll learn CCA Data Analyst faster. Chances are, you’ll have a different learning style to those around you. We combine visual, auditory and tactile styles to deliver the material in a way that ensures you will learn faster and more easily
  7. You’ll be studying CCA Data Analyst with the best. We’ve been named in Training Industry’s “Top 20 IT Training Companies of the Year” every year since 2010. As well as winning many more awards, we’ve trained and certified 76283 professionals, and we’re partners with all of the big names in the business

Benefits

Benefits of Training with Firebrand

  • Two options of training - Residential classroom-based, or online courses
  • A purpose-built training centre – get access to dedicated Pearson VUE Select facilities
  • Certification Guarantee – pass first time or train again free (just pay for accommodation, exams and incidental costs)
  • Everything you need to certify – you’ll sit your exam at the earliest available opportunity after the course - either immediately after your classroom course, or as soon as there are slots available, if you've taken it online
  • No hidden extras – one cost covers everything you need to certify

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. 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 (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 76283 students and asked them all to review our Accelerated Learning. Currently, 96.74% 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.


"I was fairly foreign to most components of the CCNA course. The Firebrand instructor made all parts of the course clear leading to many "AHA!" moments. "
P.L., IBM CLoud. (3/8/2020 (Monday) to 8/8/2020 (Saturday))

"Provided with the appropriate materials to get through the course. Instructor was very knowledgeable and covered all the topics required."
A.H., NHS North of England CSU. (3/8/2020 (Monday) to 8/8/2020 (Saturday))

"The instructor was very knowledgeable about the course material, the course did run very fast which I understand was the point of it so whilst it may have been a bit too fast for me, I appreciate how well the instructor kept on track and taught the class as well as answering the questions"
C.M., i-dash. (3/8/2020 (Monday) to 8/8/2020 (Saturday))

"Excellent course so much in-depth information passed on. Excellent instructor - course was intensive no doubt about it. But will be back later in 2020 for some more education. "
Adele Reed. (3/8/2020 (Monday) to 6/8/2020 (Thursday))

"The course really keyed in all the topics of the exam. The material slides, documentation, labs was well written and presented. The instructor really knew his stuff and you could tell he was passionate about the subject. When also considering the difficult times we live in with COVID-19, the training and the staff were superb."
Chuck Ashmore. (27/7/2020 (Monday) to 31/7/2020 (Friday))

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