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Apache Spark (TM) SQL for Data Analysts

Approx. 14 hours to complete

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Course Summary

In this course, you will learn how to use Apache Spark SQL to analyze data and gain insights from it. You will also learn how to use Spark SQL to manipulate data and prepare it for analysis.

Key Learning Points

Learn how to use Spark SQL to analyze data
Gain insights from data using Spark SQL
Manipulate data and prepare it for analysis

Job Positions & Salaries of people who have taken this course might have

- USA: $75,000 - $130,000
- India: ₹4,00,000 - ₹10,00,000
- Spain: €25,000 - €50,000
- USA: $75,000 - $130,000
- India: ₹4,00,000 - ₹10,00,000
- Spain: €25,000 - €50,000
- USA: $100,000 - $150,000
- India: ₹7,00,000 - ₹20,00,000
- Spain: €30,000 - €60,000
- USA: $75,000 - $130,000
- India: ₹4,00,000 - ₹10,00,000
- Spain: €25,000 - €50,000
- USA: $100,000 - $150,000
- India: ₹7,00,000 - ₹20,00,000
- Spain: €30,000 - €60,000
- USA: $90,000 - $140,000
- India: ₹6,00,000 - ₹15,00,000
- Spain: €25,000 - €55,000

Learning Outcomes

Understand the basics of Apache Spark SQL
Learn how to manipulate and prepare data using Spark SQL
Gain insights from data analysis using Spark SQL

Prerequisites or good to have knowledge before taking this course

Basic knowledge of SQL
Familiarity with programming concepts

Course Difficulty Level

Intermediate

Course Format

Online
Self-paced

Similar Courses

Big Data Essentials: HDFS, MapReduce and Spark RDD
Data Analysis with Python

Related Education Paths

Notable People in This Field

Creator of Apache Spark
Creator of Alluxio

Related Books

Description

Apache Spark is one of the most widely used technologies in big data analytics. In this course, you will learn how to leverage your existing SQL skills to start working with Spark immediately. You will also learn how to work with Delta Lake, a highly performant, open-source storage layer that brings reliability to data lakes. By the end of this course, you will be able to use Spark SQL and Delta Lake to ingest, transform, and query data to extract valuable insights that can be shared with your team.

Knowledge

Ingest, transform, and query data to extract valuable insights.
Leverage existing SQL skills to start working with Apache Spark.

Outline

Welcome to Apache Spark SQL for Data Analysts
Course goals
Before you begin
End of module knowledge check

Spark makes big data easy
Introduction to module 2
What is big data?
Common struggles with big data
Big Data Needs
Apache Spark Intro
Spark SQL
Module 2 Concept Review

Using Spark SQL on Databricks
Introduction to Module 3
Signing up for Databricks Community Edition
Preparing your workspace
Working with notebooks
Using course materials
Basic queries with Spark SQL reading introduction
Data Visualization on Databricks reading introduction
Data visualization tools
Exploratory Data Analysis lab introduction
Course Materials
Basic Queries reading activity
Data Visualization reading activity
Your turn! Exploratory Data Analysis lab
Module 3 Concept Review
3.3 Exploratory Data Analysis Quiz

Spark Under the Hood
Introduction to module 4
Understanding optimizations
The physical cluster
The SparkUI and SQL tab
Optimizing query logic
Impact of Caching
Optimizing with selective data loading
Module 4 Concept Review

Complex Queries
Introduction to module 5
What is nested data?
Introduction to managing nested data
Introduction to Manipulating Data
Introduction to Data Munging
Managing Nested Data reading activity
Manipulating Data reading activity
5.3 Data Munging Lab
Module 5 Concept Review
Lab 5.3 Quiz

Applied Spark SQL
Introduction to module 6
Complex data - common strategies
About higher-order functions
Higher-order functions introduction
Introducing Aggregating and Summarizing Data
Partitioning Tables Introduction
Sharing Insights Lab Introduction
Higher Order Functions reading activity
Aggregating and Summarizing Data reading activity
Partitioning Tables
Sharing Insights
Module 6 concept review
Lab 6.4 Quiz

Data Storage and Optimization
Introduction to module 7
A quick refresher
Introducing a new data management paradigm
Introduction to the lesson
What is Delta Lake
Data Warehouses
Data Lakes
Data Lakes vs Data Warehouses
The Lakehouse

Delta Lake with Spark SQL
Introduction to the module
Intro to Using Delta reading
Managing Records in a Delta table
Delta Engine Optimization Introduction
Delta Lake Lab Introduction
8.1 Using Delta
8.2 Managing records
8.3 Optimizing Delta
Delta Lab
8.4 Delta Lab

SQL Coding Challenges
SQL coding challenges
Final Exam

Summary of User Reviews

Discover Apache Spark SQL for Data Analysts with Coursera. This course has received high praise from its users for its comprehensive and practical approach to teaching data analysis. Many users appreciate the well-structured course material that is easy to follow and understand.

Key Aspect Users Liked About This Course

The course material is well-structured and easy to follow.

Pros from User Reviews

The course content is comprehensive and practical.
The instructors are knowledgeable and engaging.
The course provides hands-on experience with real-world datasets.
The course is well-structured and easy to follow.
The course provides a solid foundation for further study in data analysis.

Cons from User Reviews

Some users felt that the course moved too quickly through certain topics.
Some users found the course material to be too basic.
Some users experienced technical difficulties with the course platform.
Some users felt that the assessments were too difficult or not relevant to the course material.
Some users would have liked more opportunities for interaction with instructors and other students.