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

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stars
509 ratings

Ian Cook

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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 get an in-depth look at the SQL SELECT statement and its main clauses. The course focuses on big data SQL engines Apache Hive and Apache Impala, but most of the information is applicable to SQL with traditional RDBMs as well; the instructor explicitly addresses differences for MySQL and PostgreSQL.
By the end of the course, you will be able to
• explore and navigate databases and tables using different tools;
• understand the basics of SELECT statements;
• understand how and why to filter results;
• explore grouping and aggregation to answer analytic questions;
• work with sorting and limiting results; and 
• combine multiple tables in different ways.

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

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Coursera Labs

Includes hands on learning projects.

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Course 2 of 3 in the

Modern Big Data Analysis with SQL Specialization

Beginner Level

Approx. 17 hours to complete

English

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What you will learn

Understand the basics of SELECT statements
Understand how and why to filter results
Explore grouping and aggregation to answer analytic questions
Work with sorting and limiting results

Skills you will gain

Apache Hive
Apache Impala
Data Analysis
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 2 of 3 in the

Modern Big Data Analysis with SQL Specialization

Beginner Level

Approx. 17 hours to complete

English

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

Try Coursera for Business

Instructor

Instructor rating

4.91/5 (119 Ratings)

Ian Cook

Staff Curriculum Developer

Cloudera

27,325 Learners

2 Courses

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%(2,588 ratings)

Week1

Week 1

3 hours to complete

Orientation to SQL on Big Data

3 hours to complete

9 videos (Total 47 min), 5 readings, 2 quizzes

9 videos

Welcome to the Course4mReview and Preparation4mUsing the Hue Query Editors7mRunning SQL Utility Statements6mRunning SQL SELECT Statements5mUnderstanding Different SQL Interfaces4mOverview of Beeline and Impala Shell2mUsing Beeline8mUsing Impala Shell3m

5 readings

Instructions for Downloading and Installing the Exercise Environment30mTroubleshooting the VM5m(Optional) What about Spark SQL?10mExpectations for Learners10m(Optional) Using Other SQL Engines10m

2 practice exercises

Week 1 Core Quiz30mWeek 1 Honors Quiz5m

Week2

Week 2

3 hours to complete

SQL SELECT Essentials

3 hours to complete

16 videos (Total 83 min), 4 readings, 2 quizzes

16 videos

Introduction2mSQL SELECT Building Blocks2mIntroduction to the SELECT List7mExpressions and Operators7mData Types6mColumn Aliases5mBuilt-In Functions7mData Type Conversion5mThe DISTINCT Keyword5mIntroduction to the FROM Clause3mIdentifiers7mFormatting SELECT Statements4mUsing Beeline in Non-Interactive Mode5mUsing Impala Shell in Non-Interactive Mode4mFormatting the Output of Beeline and Impala Shell4mSaving Hive and Impala Query Results to a File5m

4 readings

Order of Operations5mDivision and Modulo Operators15mCommon String Functions15mCase (In)Sensitivity in SQL10m

2 practice exercises

Week 2 Core Quiz30mWeek 2 Honors Quiz5m

Week3

Week 3

3 hours to complete

Filtering Data

3 hours to complete

14 videos (Total 85 min), 6 readings, 2 quizzes

14 videos

Introduction1mAbout the Datasets4mIntroduction to the WHERE Clause2mUsing Expressions in the WHERE Clause9mComparison Operators9mData Types and Precision4mLogical Operators7mOther Relational Operators4mUnderstanding Missing Values8mHandling Missing Values6mConditional Functions9mUsing Variables with Beeline and Impala Shell7mCalling Beeline and Impala Shell from Scripts6mQuerying Hive and Impala in Scripts and Applications2m

6 readings

Data Reference5m(Optional) Unicode Characters10mWorking with Literal Strings15mMissing Values with Logical Operators10mMissing Values in String Columns5m(Optional Exercise) Change VM Desktop Color30m

2 practice exercises

Week 3 Core Quiz30mWeek 3 Honors Quiz5m

Week4

Week 4

3 hours to complete

Grouping and Aggregating Data

3 hours to complete

15 videos (Total 82 min), 6 readings, 2 quizzes

15 videos

Introduction1mIntroduction to Aggregation2mCommon Aggregate Functions2mUsing Aggregate Functions in the SELECT Statement8mIntroduction to the GROUP BY Clause6mChoosing an Aggregate Function and Grouping Column4mGrouping Expressions6mGrouping and Aggregation, Together and Separately5mNULL Values in Grouping and Aggregation4mThe COUNT Function7mTips for Applying Grouping and Aggregation7mFiltering on Aggregates2mThe HAVING Clause8mUnderstanding Hive and Impala Version Differences10mUnderstanding Hue Version Differences2m

6 readings

COUNT(*) and SUM(1)5mInterpreting Aggregates: Populations and Samples10mThe least and greatest Functions5mWhy Aggregate Expressions Ignore NULL Values5m(Optional) Shortcuts for Grouping10mHow Grouping and Aggregation Can Mislead10m

2 practice exercises

Week 4 Core Quiz30mWeek 4 Honors Quiz10m

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TOP REVIEWS FROM ANALYZING BIG DATA WITH SQL

by YNMar 26, 2020

A great course to go over the basic SQL. However, this course doesn't go cover Subquery concept :(

by JCMay 4, 2020

This course helped me a great deal for a job interview as well as for all future querying with Impala and Hive

by GHApr 25, 2020

Great course. Nice assignment at the end.

Maybe you could add a couple of more assignments.

by AFDec 29, 2020

Brilliant course, one of the best I have done on Coursera! The teaching is phenomenal - thanks guys!

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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