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

Ian Cook
Top Instructor

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)

Shareable Certificate

Earn a Certificate upon completion

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Start instantly and learn at your own schedule.

Course 2 of 3 in the

Modern Big Data Analysis with SQL Specialization

Flexible deadlines

Reset deadlines in accordance to your schedule.

Beginner Level

Approx. 18 hours to complete

English

Subtitles: Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Vietnamese, Korean, German, Russian, Turkish, English, Spanish

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 HiveApache ImpalaData AnalysisBig DataSQL

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 2 of 3 in the

Modern Big Data Analysis with SQL Specialization

Flexible deadlines

Reset deadlines in accordance to your schedule.

Beginner Level

Approx. 18 hours to complete

English

Subtitles: Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Vietnamese, Korean, German, Russian, Turkish, English, Spanish

Instructor

Instructor rating

4.93/5 (49 Ratings)

Ian Cook
Top Instructor

Staff Curriculum Developer

Cloudera

16,927 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.

Syllabus - What you will learn from this course

Content Rating94%(1,040 ratings)

Week

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 Course4m

Review and Preparation4m

Using the Hue Query Editors7m

Running SQL Utility Statements6m

Running SQL SELECT Statements5m

Understanding Different SQL Interfaces4m

Overview of Beeline and Impala Shell2m

Using Beeline8m

Using Impala Shell3m

5 readings

Instructions for Downloading and Installing the Exercise Environment30m

Troubleshooting the VM5m

(Optional) What about Spark SQL?10m

Expectations for Learners10m

(Optional) Using Other SQL Engines10m

2 practice exercises

Week 1 Core Quiz30m

Week 1 Honors Quiz5m

Week

Week 2

3 hours to complete

SQL SELECT Essentials

3 hours to complete

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

16 videos

Introduction2m

SQL SELECT Building Blocks2m

Introduction to the SELECT List7m

Expressions and Operators7m

Data Types6m

Column Aliases5m

Built-In Functions7m

Data Type Conversion5m

The DISTINCT Keyword5m

Introduction to the FROM Clause3m

Identifiers7m

Formatting SELECT Statements4m

Using Beeline in Non-Interactive Mode5m

Using Impala Shell in Non-Interactive Mode4m

Formatting the Output of Beeline and Impala Shell4m

Saving Hive and Impala Query Results to a File5m

4 readings

Order of Operations5m

Division and Modulo Operators15m

Common String Functions15m

Case (In)Sensitivity in SQL10m

2 practice exercises

Week 2 Core Quiz30m

Week 2 Honors Quiz5m

Week

Week 3

3 hours to complete

Filtering Data

3 hours to complete

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

14 videos

Introduction1m

About the Datasets4m

Introduction to the WHERE Clause2m

Using Expressions in the WHERE Clause9m

Comparison Operators9m

Data Types and Precision4m

Logical Operators7m

Other Relational Operators4m

Understanding Missing Values8m

Handling Missing Values6m

Conditional Functions9m

Using Variables with Beeline and Impala Shell7m

Calling Beeline and Impala Shell from Scripts6m

Querying Hive and Impala in Scripts and Applications2m

6 readings

Data Reference5m

(Optional) Unicode Characters10m

Working with Literal Strings15m

Missing Values with Logical Operators10m

Missing Values in String Columns5m

(Optional Exercise) Change VM Desktop Color30m

2 practice exercises

Week 3 Core Quiz30m

Week 3 Honors Quiz5m

Week

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

Introduction1m

Introduction to Aggregation2m

Common Aggregate Functions2m

Using Aggregate Functions in the SELECT Statement8m

Introduction to the GROUP BY Clause6m

Choosing an Aggregate Function and Grouping Column4m

Grouping Expressions6m

Grouping and Aggregation, Together and Separately5m

NULL Values in Grouping and Aggregation4m

The COUNT Function7m

Tips for Applying Grouping and Aggregation7m

Filtering on Aggregates2m

The HAVING Clause8m

Understanding Hive and Impala Version Differences10m

Understanding Hue Version Differences2m

6 readings

COUNT(*) and SUM(1)5m

Interpreting Aggregates: Populations and Samples10m

The least and greatest Functions5m

Why Aggregate Expressions Ignore NULL Values5m

(Optional) Shortcuts for Grouping10m

How Grouping and Aggregation Can Mislead10m

2 practice exercises

Week 4 Core Quiz30m

Week 4 Honors Quiz10m

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, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.
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.

Analyzing Big Data with SQL