This course is part of the Modern Big Data Analysis with SQL Specialization

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stars
283 ratings

Ian Cook +1 more instructor

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Offered By

Modern Big Data Analysis with SQL SpecializationCloudera

About this Course

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In this course, you'll learn how to manage big datasets, how to load them into clusters and cloud storage, and how to apply structure to the data so that you can run queries on it using distributed SQL engines like Apache Hive and Apache Impala. You’ll learn how to choose the right data types, storage systems, and file formats based on which tools you’ll use and what performance you need.
By the end of the course, you will be able to
• use different tools to browse existing databases and tables in big data systems;
• use different tools to explore files in distributed big data filesystems and cloud storage;
• create and manage big data databases and tables using Apache Hive and Apache Impala; and
• describe and choose among different data types and file formats for big data systems.

To use the hands-on environment for this course, you need to download and install a virtual machine and the software on which to run it. Before continuing, be sure that you have access to a computer that meets the following hardware and software requirements:
• Windows, macOS, or Linux operating system (iPads and Android tablets will not work)
• 64-bit operating system (32-bit operating systems will not work)
• 8 GB RAM or more
• 25GB free disk space or more
• Intel VT-x or AMD-V virtualization support enabled (on Mac computers with Intel processors, this is always enabled;
on Windows and Linux computers, you might need to enable it in the BIOS)
• For Windows XP computers only: You must have an unzip utility such as 7-Zip or WinZip installed (Windows XP’s built-in unzip utility will not work)

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

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Course 3 of 3 in the

Modern Big Data Analysis with SQL Specialization

Beginner Level

Approx. 20 hours to complete

English

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What you will learn

Use different tools to browse existing databases and tables in big data systems
Use different tools to explore files in distributed big data filesystems and cloud storage
Create and manage big data databases and tables using Apache Hive and Apache Impala
Describe and choose among different data types and file formats for big data systems

Skills you will gain

Data Management
Distributed File Systems
Cloud Storage
Big Data
SQL

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 3 of 3 in the

Modern Big Data Analysis with SQL Specialization

Beginner Level

Approx. 20 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructors

Instructor rating

4.85/5 (57 Ratings)

Ian Cook

Staff Curriculum Developer

Cloudera

27,325 Learners

2 Courses

Glynn Durham

Offered by

Cloudera

At Cloudera, we believe that data can make what is impossible today, possible tomorrow. We empower people to transform complex data into clear and actionable insights. Cloudera delivers an enterprise data cloud for any data, anywhere, from the Edge to AI. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises.

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Syllabus - What you will learn from this course

Content Rating95%(1,128 ratings)

Week1

Week 1

3 hours to complete

Orientation to Data in Clusters and Cloud Storage

3 hours to complete

7 videos (Total 56 min), 3 readings, 1 quiz

7 videos

Welcome to the Course4mBrowsing Tables with Hue7mBrowsing Tables with SQL Utility Statements6mBrowsing HDFS with the Hue File Browser13mBrowsing HDFS from the Command Line9mUnderstanding S3 and Other Cloud Storage Platforms6mBrowsing S3 Buckets from the Command Line8m

3 readings

Review and Preparation30mInstructions for Downloading and Installing the Exercise Environment30mTroubleshooting the VM5m

1 practice exercise

Week 1 Graded Quiz30m

Week2

Week 2

5 hours to complete

Defining Databases, Tables, and Columns

5 hours to complete

7 videos (Total 33 min), 12 readings, 2 quizzes

7 videos

Week 2 Introduction3mIntroduction to the CREATE TABLE Statement5mUsing Different Schemas on the Same Data12mSpecifying TBLPROPERTIES2mExamining, Modifying, and Removing Tables1mHive and Impala Interoperability2mImpala Metadata Refresh3m

12 readings

Creating Databases and Tables with Hue30mCreating Databases and Tables with SQL15mPermissions to Create Databases and Tables5mThe ROW FORMAT Clause25mThe STORED AS Clause15mThe LOCATION Clause20mCREATE TABLE Shortcuts10mUsing Hive SerDes15mWorking with Unstructured and Semi-Structured Data15mExamining Table Structure10mDropping Databases and Tables5mModifying Existing Tables35m

2 practice exercises

Week 2 Practice Quiz30mWeek 2 Graded Quiz30m

Week3

Week 3

3 hours to complete

Data Types and File Types

3 hours to complete

5 videos (Total 14 min), 12 readings, 2 quizzes

5 videos

Week 3 Introduction1mOverview of Data Types1mChoosing the Right Data Types4mOverview of File Types3mChoosing the Right File Types3m

12 readings

Integer Data Types5mDecimal Data Types10mCharacter String Data Types10mOther Data Types5mExamining Data Types10mOut-of-Range Values5mText Files5mAvro Files5mParquet Files5mORC Files5mOther File Types5mCreating Tables with Avro and Parquet Files20m

2 practice exercises

Week 3 Practice Quiz20mWeek 3 Graded Quiz30m

Week4

Week 4

5 hours to complete

Managing Datasets in Clusters and Cloud Storage

5 hours to complete

8 videos (Total 48 min), 13 readings, 3 quizzes

8 videos

Week 4 Introduction3mRefresh Impala's Metadata Cache after Loading Data2mLoading Files into HDFS with Hue's Table Browser10mLoading Files into HDFS with Hue's File Browser6mLoading Files into HDFS from the Command Line8mLoading Files into S3 from the Command Line10mUsing Hive and Impala to Load Data into Tables3mConclusion2m

13 readings

More about HDFS Shell Commands10mChaining and Scripting with HDFS Commands5mHDFS Permissions5mOther Ways to Load Files into S35mS3 Permissions10mMissing Values15mCharacter Sets5mUsing Sqoop to Import Data15mMore Sqoop Import Options5mUsing Sqoop to Export Data5mSQL LOAD DATA Statements10mSQL INSERT Statements10mSQL INSERT ... SELECT and CTAS Statements15m

2 practice exercises

Week 4 Practice Quiz30mWeek 4 Graded Quiz30m

Reviews

4.7

65 reviews

5 stars
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3 stars
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2 stars
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1 star
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TOP REVIEWS FROM MANAGING BIG DATA IN CLUSTERS AND CLOUD STORAGE

by RAMay 27, 2020

The course spanned across multiple areas. It was great learning.

by ANApr 15, 2020

This is one of the best courses I've attended on Coursera! Kudos to the course organizers and instructors.

by XYJun 25, 2021

Super useful course with a lot of hands on practices. Though the VM is running slow on my computer.

by MNAug 7, 2020

Absolutely amazing! Have learnt a lot from this course!

View all reviews

About the Modern Big Data Analysis with SQL Specialization

This Specialization teaches the essential skills for working with large-scale data using SQL.

Maybe you are new to SQL and you want to learn the basics. Or maybe you already have some experience using SQL to query smaller-scale data with relational databases. Either way, if you are interested in gaining the skills necessary to query big data with modern distributed SQL engines, this Specialization is for you. Most courses that teach SQL focus on traditional relational databases, but today, more and more of the data that’s being generated is too big to be stored there, and it’s growing too quickly to be efficiently stored in commercial data warehouses. Instead, it’s increasingly stored in distributed clusters and cloud storage. These data stores are cost-efficient and infinitely scalable. To query these huge datasets in clusters and cloud storage, you need a newer breed of SQL engine: distributed query engines, like Hive, Impala, Presto, and Drill. These are open source SQL engines capable of querying enormous datasets. This Specialization focuses on Hive and Impala, the most widely deployed of these query engines. This Specialization is designed to provide excellent preparation for the Cloudera Certified Associate (CCA) Data Analyst certification exam. You can earn this certification credential by taking a hands-on practical exam using the same SQL engines that this Specialization teaches—Hive and Impala.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
What are the hardware and software requirements for the exercise environment?
• Windows, macOS, or Linux operating system (iPads and Android tablets will not work) • 64-bit operating system (32-bit operating systems will not work) • 8 GB RAM or more • 25GB free disk space or more • Intel VT-x or AMD-V virtualization support enabled (on Mac computers with Intel processors, this is always enabled; on Windows and Linux computers, you might need to enable it in the BIOS) • For Windows XP computers only: You must have an unzip utility such as 7-Zip or WinZip installed (Windows XP’s built-in unzip utility will not work)

More questions? Visit the Learner Help Center.

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Managing Big Data in Clusters and Cloud Storage

About this Course

What you will learn

Skills you will gain