What you'll learn
Use SQL for Data Analysis
Navigate the BigQuery User Interface & Key Features
Export Data in a range of formats
Range of SQL statement e.g SELECT, WHERE, ORDER BY, GROUP BY and more
Join multiple tables together with JOIN and LEFT JOIN
Range of SQL Analytics Functions e.g MIN(), MAX(), AVG(), SUM(), COUNT() and more
All hosted online. Access Google BigQuery with google account
Requirements
No prior SQL or database knowledge required!
Description
Learn how to use SQL with BigQuery quickly and effectively with this course!You'll learn how to read and write complex queries to a database using one of the most in demand skills and one of the most powerful databases: Google BigQuery.In this course you will learn:How to Navigate the BigQuery User Interface and its key featuresHow to write SQL syntax including a range of statements and functions to query your data sets.Transferable SQL Skills that can be used with any SQL database (Whether you'll be using Bigquery or another database such as MySQL or Postgresql)How to export your data for a varied range of use cases after you have completed your analysis.Learning SQL is one of the fastest ways to improve your career prospects as it is one of the most in demand tech skills and one of the most important skills as a Data Analyst.Check out the free preview videos for more information!Who this course is for:Data AnalystsData ScientistsEngineersAnyone interested in learning more about SQL, BigQuery or data analysisAs a Data Scientist with over 6 years of experience in Data Analytics, I look forward to introducing you to the world of analytics and SQL with Google BigQuery.
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 Setting up your Sandbox Account
Lecture 3 EXERCISE - Sandbox Account
Lecture 4 Add your first Dataset
Lecture 5 EXERCISE - Your First Data Set
Lecture 6 Explore Tables & Column Data Types
Lecture 7 EXERCISE - Data Types
Lecture 8 Exploring Tables
Section 2: Retrieve the data you need with the SELECT Statement
Lecture 9 SELECT with single & multiple columns
Lecture 10 EXERCISE - Selecting Single & Multiple Columns
Lecture 11 SELECT with EXCEPT
Lecture 12 EXCERCISE - SELECT with EXCEPT
Lecture 13 Query History & Saving Queries - Find your queries again
Lecture 14 EXERCISE - Query History & Saving Queries
Section 3: Filter the data you need with the WHERE Statement
Lecture 15 WHERE statement with Integers
Lecture 16 EXERCISE - Where statement with integers
Lecture 17 ORDER BY to order your results
Lecture 18 EXERCISE - ORDER BY
Lecture 19 WHERE statement with Dates
Lecture 20 EXERCISE - WHERE statement with Dates
Lecture 21 WHERE statement with boolean values (True/False)
Lecture 22 EXERCISE - WHERE with boolean values
Lecture 23 AND - to combine your filters
Lecture 24 EXERCISE - using AND
Lecture 25 OR - to combine your filters
Lecture 26 EXERCISE - OR
Lecture 27 BETWEEN - to combine your filters
Lecture 28 EXERCISE - BETWEEN
Lecture 29 IN - to filter on multiple values
Lecture 30 EXERCISE - IN
Lecture 31 WHERE statement with strings (text)
Lecture 32 EXERCISE - WHERE with text
Lecture 33 LIKE - filter for strings
Lecture 34 EXERCISE - LIKE
Lecture 35 WHERE statement with strings - handling case sensitivity
Lecture 36 NULL
Lecture 37 NOT - filter
Lecture 38 WHERE - Summary
Section 4: Calculate more metrics with Aggregate Analytical Functions
Lecture 39 COUNT() - to count number or rows or values
Lecture 40 COUNT() with DISTINCT
Lecture 41 SUM() AND AVG() - To calculate the sum and average
Lecture 42 MIN() and MAX()
Lecture 43 VAR() & STD_DEV()
Section 5: GROUP BY
Lecture 44 GROUP BY statement
Lecture 45 GROUP BY & ORDER BY
Lecture 46 GROUP BY multiple columns
Lecture 47 GROUP BY & ORDER BY 1,2,3
Lecture 48 HAVING & GROUP BY
Section 6: JOIN tables together
Lecture 49 JOINING tables
Lecture 50 Aliasing Tables
Lecture 51 LEFT JOIN
Section 7: Create new Columns with Single Line Functions
Lecture 52 IF() Function
Lecture 53 CASE function
Section 8: EXPORT your data
Lecture 54 Exporting to Google Drive or .csv
Lecture 55 Export to Google Data Studio
Data Analysis,Data Scientist,Engineer,Anyone who wants to learn SQL or Data Analysis!


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