SQL Mastery For Data Science

Name: SQL Mastery For Data Science
Rating: 4.2 (14 reviews)

Up Your Skills with SQL Tips and Tricks for Data Science

Created bySkill Savy

Last updated 2/2024

English

English [Auto],

What you'll learn

SQL for Data Science
Learn practical applications of SQL queries for data analysis
How to join tables and calculate rolling averages
How to use window functions, aggregate and filter data
Learn how to retrieve data
Much more

Course content

2 sections • 15 lectures • 58m total length

Introduction1:32
Learn to retrieve data with SQL Server and the Adventure Works 2014 warehouse, then use aggregation, joins, filters, ranking, window functions, and six-week rolling averages for analytics questions.
Course Files0:32
Explore exercise files with well-commented code that reinforces SQL concepts, and follow along without files, then consult online docs to learn how to use the functions.

Retrieve data using SQL4:18
Retrieve data from databases using SQL, a universal language with a standard syntax. Learn to select columns, use aliases, limit results, and perform basic data manipulation.
Joining Tables5:44
Learn to join tables in SQL to combine datasets, perform lookups, and enable year over year comparisons by using inner and left joins with aliases.
Filter Data5:33
Filter data effectively by using where, date ranges, between, in, and like conditions to focus analysis, speed up queries, and craft precise results.
Aggregate data6:29
Learn to aggregate data with built-in functions like min, max, average, sum, and count, plus standard deviation, variance, and rank, using group by and having clause to add context.
Window functions1:54
Explore SQL window functions using partitions and over clause with ordering to control aggregation, reference previous rows, and compute group, country, and region averages and year-to-date values in one query.
Subqueries4:16
Discover how subqueries embed inner queries in outer queries to aggregate data and create rolling averages. Learn to use subqueries to filter results, compare with joins, and apply exists clause.
Rolling calculations4:48
Explore rolling calculations using window functions to compute moving averages and year to date totals, with examples of weekly sales, running totals, and partitioning by year.
Analyze employee data4:18
Analyze how to compute daily and monthly active employees from start and end dates using a date dimension, handling null end dates, and building trends in SQL Server.
Date and time functions5:11
Explore date and time functions to manipulate and aggregate daily data into monthly insights, compute date differences, filter by periods, and identify the most recent data for timely analytics.
Common table expressions5:55
Explore common table expressions to build self-referencing queries, navigate employee hierarchies, perform lookups, and create aggregates of aggregates using with clauses for faster analysis.
Year-over-year calculations3:26
Master year-over-year analysis by comparing the same month across years and removing seasonality; learn to compute the growth percent using a common table expression.
Finding ranks4:09
Learn to rank SQL results using rank, dense_rank, row_number, and percent_rank with partition by and over, to identify top products by year and subcategory.
Course Feedback0:01

Requirements

Free downloads SQL Server and AdventureWorks

Description

Gain the career-building SQL skills you need with this course. Through hands-on learning you’ll load, extract, and manipulate data from relational databases. Study at your own pace and grow your SQL skills.

In this course, we'll go over the most common data science and analytics questions that you'll receive, such as how to find the top products per category, how to find active employee counts by month, how to calculate rolling average of sales and much more.

We'll start by showing you how to retrieve data from a database using SQL Server and AdventureWorks, then show you how to aggregate, join, and filter your results to create context for your analysis.

We'll also get into answering more complex questions with ranking, moving averages, and window functions.

Learn how to retrieve data, join tables, calculate rolling averages and rankings, work with dates and times, use window functions, aggregate and filter data, and much more.

SQL is one of the most requested skills in Data Science. This course is great for anyone looking to build their skills and take it to the next level.

Learn to use Structured Query Language (SQL) to extract and analyze data stored in databases. You’ll first learn to extract data, join tables together, and perform aggregations. Then you’ll learn to do more complex analysis and manipulations using subqueries, and window functions.

By the end of the course, you’ll be able to write efficient SQL queries to successfully handle a variety of data analysis tasks.

Who this course is for:

Programmers, Developers, DevOps, Data miners

SQL Mastery For Data Science

What you'll learn

Explore related topics

Course content

Introduction2 lectures • 2min

SQL Tips & Tricks13 lectures • 56min

Requirements

Description

Who this course is for: