Using SQL for Data Science

The role of a data scientist is to turn raw data into  actionable insights. Much of the world's raw data—from electronic medical records to customer e-commerce  transaction histories—lives  in organized collections of tables called relational databases.  Therefore, to be an effective data scientist, you must know how to wrangle and extract data from these databases using a language  called SQL (pronounced ess-que-ell, or sequel).

As data collection has increased exponentially, so has the need for people skilled at using and interacting with data; to be able to think critically, and provide insights to make better decisions and optimise their businesses. This is where the data scientist comes in.  According to Glassdoor, being a data scientist is the best job in America; with a median base salary of $110,000 and thousands of job openings at a time. The skills necessary to be a good data scientist include being able to retrieve and work with data, and to do that you need to be well versed in SQL, the standard language for communicating with database systems.

This course is designed to give you a primer in the fundamentals of SQL and working with data so that you can begin analyzing it for data science purposes. You will begin to ask the right questions and come up with good answers to deliver valuable insights for your organization. This course starts with the basics and assumes you  have  little or no  knowledge or skills in SQL. 

 What you will learn includes:

• Downloading and installing Oracle Database
• Downloading and installing TOAD
• Download and installing SQL Developer
• Connecting to Oracle database
• Querying data from single and multiple columns
• Removing duplicate records from query output
• Filtering records with WHERE clause
• Using various operators with the WHERE clause
• Limiting data
• Using aggregate functions
• Sorting and Grouping data
• Extracting data from multiple tables