Complete Sql Bootcamp For Data Science, Analytics, Marketing

Master SQL for Job Interview Preparation, Data Analysis, Big Data, and Business Intelligence

What you'll learn
Understand what a relational database is
How to install SQL on Mac, Linux, or Windows
How to create a table
How to import data into a table
How to query a database table using SQL
How to insert into, update, and delete from a table
Speed things up using indexes
Join tables together to merge data
Aggregate data using count, sum, and average
Determine where in the sales funnel customers are being lost
Chart your year over year revenue
Group and sort sales by location
Use SQL on Spark
Install Spark
Create a Spark cluster on AWS EC2
Requirements
You should you how to open a terminal / command line shell. All the examples will be done here.
Description
It is becoming ever more important that companies make data-driven decisions.With big data and data science on the rise, we have more data than we know what to do with.One of the basic languages of data analytics is SQL, which is used for many popular databases including MySQL, Postgres, SQLite, Microsoft SQL Server, Oracle, and even big data solutions like Hive and Cassandra.I’m going to let you in on a little secret. Most high-level marketers and product managers at big tech companies know how to manipulate data to gain important insights. No longer do you have to wait around the entire day for some software engineer to answer your questions - now you can find the answers directly, by yourself, using SQL!In this course, The Complete SQL Bootcamp for Data Science, Analytics, and Marketing, we'll start from the basics - installing SQL onto your Mac, Linux, or Windows machine and explaining what a relational database is. Next, we'll look at basic tasks like creating tables and loading data into those tables. We will look at a wide variety of SQL commands and I will show you how to speed things up using indexes.Once you know all the SQL commands we will start doing advanced examples - answering questions marketers and business people often have, like where are customers dropping off in our sales funnel? And which of our locations has the highest revenue?In the last section, we'll do Advanced SQL queries on Spark, the big data framework that is the successor to MapReduce and also runs on top of Hadoop. I will teach you how to install Spark, create a cluster very quickly on Amazon EC2, and run SQL queries, allowing you to apply everything you learned up until this point in a big data environment.Do you want to know how to optimize your sales funnel using SQL, look at the seasonal trends in your industry, and run a SQL query on Hadoop? Then join me now in my new class on SQL! Dominate data analytics, data science, and big data!TIPS (for getting through the course):Watch it at 2x to learn twice as fast!Take handwritten notes. This will drastically increase your ability to retain the information.Ask lots of questions on the discussion board. The more the better!Write code yourself, don't just sit there and look at my code.

Overview

Section 1: Why you should stop depending on engineers and learn SQL

Lecture 1 Introduction and Outline

Lecture 2 How to Succeed in this Course

Section 2: Survey of SQL databases and Installation of SQLite

Lecture 3 Overview of SQL databases

Lecture 4 Installing SQLite on Mac, Linux, and Windows

Lecture 5 Visual Walkthrough of Windows Installation

Section 3: What is a relational database? Basic commands

Lecture 6 What’s a relational database?

Lecture 7 How to load the data used in this class

Lecture 8 Basic commands

Lecture 9 Querying a table

Lecture 10 Creating a table

Lecture 11 Importing Data on Windows

Lecture 12 Modifying a table’s structure

Lecture 13 Suggestion Box

Section 4: Indexes and speed comparison

Lecture 14 Speeding things up with indexes

Lecture 15 Index Example in the Console

Section 5: Modifying a table's data

Lecture 16 Insert / Update / Delete

Lecture 17 What is CRUD?

Section 6: Joining tables

Lecture 18 Joining or Merging tables together

Lecture 19 Joins in the console

Section 7: Aggregating, grouping, and sorting. Real marketing queries.

Lecture 20 Count, Distinct, Sum, Min, Max, Avg

Lecture 21 Group by, Sort, Limit

Lecture 22 Funnels, YOY revenue, and Sales by Location

Section 8: Advanced: SQL on Spark (Optional)

Lecture 23 Spark SQL

Lecture 24 Create your own Spark cluster on Amazon EC2

Section 9: Further Knowledge, Practice and Exercises

Lecture 25 How to load the extra dataset (tab-separated tables)

Lecture 26 The "IN" Keyword

Lecture 27 The "BETWEEN" Keyword

Lecture 28 Interview Question-Style Exercises

Section 10: Appendix / FAQ

Lecture 29 How to Succeed in this Course (Long Version)

Lecture 30 BONUS

This course is for not only marketers but anyone who wants to be able to answer data-related questions on their own,Students who want a different approach to learning SQL,Professionals who are exposed to data but can't yet leverage its power,Developers who build web-applications but don't yet know how to use a database backend,Product managers who want to make data-driven decisions