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Cloudera - CCA Data Analyst

Varighed

Varighed:

Kun 3 dage

Metode

Metode:

Klasseværelse / Online / Hybrid

Næste dato

Næste dato:

24/6/2024 (Mandag)

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

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 Gratis 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

Det hele er inkluderet! Du får en alt-inklusiv kursuspakke, som er målrettet til dine behov. Vi tager os af enhver detalje, så det eneste du skal fokusere på er dine lærings- og certificeringsmål.

  • Transport til/fra specifikke afhentningssteder
  • Overnatninger, samtlige måltider samt adgang til forfriskninger, snacks, kaffe og the.
  • Intensiv Hands-on uddannelse med vores unikke (Lecture | Lab | Review)TM metode
  • Omfattende kursusmaterialer og labmanualer
  • Et helt igennem instruktørstyret program
  • 24 timers adgang til både undervisningslokale og instruktøren
  • Samtlige måltider samt adgang til forfriskninger, snacks, kaffe og the.
  • Certificeringsgaranti

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.

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Kundereferencer

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"I had a great time. The instructor is very knowledgeable and his training is on point. Two exams in 2 days is a lot. But he makes it doable."
Juan van Gom, Ministry of Defense Netherlands. (19/1/2024 (Fredag) til 21/1/2024 (Søndag))

"Detailed and thorough training in a great environment."
Anonymous, SYP. (8/1/2024 (Mandag) til 12/1/2024 (Fredag))

"I attended the Cyber Crime Foundation course with very little knowledge.. The instructor was fantastic, explained subjects in depth and allowed a good amount of time for questions. I came away with lots of knowledge ready to use what I've learnt in my day-to-day role."
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"I very much enjoyed the training! It is a must for police officers new to Cyber Crime Units and is delivered at a good pace. Very good trainer with exceptional knowledge and enthusiasm."
Steve Lloyd, West Mercia Police. (8/1/2024 (Mandag) til 12/1/2024 (Fredag))

"I have really enjoyed the course, although I have been a self-professed nerd for many years, there was still some knowledge I took from this course. The tutorials on practical applications is something I will take away and use."
Joseph Ingram-Gettins, West Midlands Police. (8/1/2024 (Mandag) til 12/1/2024 (Fredag))

Kursusdatoer

Starter

Slutter

Tilgængelighed

Sted

Tilmelding

19/2/2024 (Mandag)

21/2/2024 (Onsdag)

Afsluttet - Giv feedback

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24/6/2024 (Mandag)

26/6/2024 (Onsdag)

Venteliste

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5/8/2024 (Mandag)

7/8/2024 (Onsdag)

Begrænsede pladser

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16/9/2024 (Mandag)

18/9/2024 (Onsdag)

Tilgængelige pladser

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28/10/2024 (Mandag)

30/10/2024 (Onsdag)

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9/12/2024 (Mandag)

11/12/2024 (Onsdag)

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