Learn SQL for Data Analysis with Google Big Query
Learn SQL for Data Analysis with Google Big Query, available at $54.99, has an average rating of 4.51, with 55 lectures, based on 3137 reviews, and has 10540 subscribers.
You will learn about 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 This course is ideal for individuals who are Data Analysis or Data Scientist or Engineer or Anyone who wants to learn SQL or Data Analysis! It is particularly useful for Data Analysis or Data Scientist or Engineer or Anyone who wants to learn SQL or Data Analysis!.
Enroll now: Learn SQL for Data Analysis with Google Big Query
Summary
Title: Learn SQL for Data Analysis with Google Big Query
Price: $54.99
Average Rating: 4.51
Number of Lectures: 55
Number of Published Lectures: 55
Number of Curriculum Items: 55
Number of Published Curriculum Objects: 55
Original Price: $69.99
Quality Status: approved
Status: Live
What You Will 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
Who Should Attend
- Data Analysis
- Data Scientist
- Engineer
- Anyone who wants to learn SQL or Data Analysis!
Target Audiences
- Data Analysis
- Data Scientist
- Engineer
- Anyone who wants to learn SQL or Data Analysis!
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:
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How to Navigate the BigQuery User Interface and its key features
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How to write SQL syntax including a range of statements and functions to query your data sets.
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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)
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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:
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Data Analysts
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Data Scientists
-
Engineers
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Anyone interested in learning more about SQL, BigQuery or data analysis
As 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.
Course Curriculum
Chapter 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
Chapter 2: Retrieve the data you need with the SELECT Statement
Lecture 1: SELECT with single & multiple columns
Lecture 2: EXERCISE – Selecting Single & Multiple Columns
Lecture 3: SELECT with EXCEPT
Lecture 4: EXCERCISE – SELECT with EXCEPT
Lecture 5: Query History & Saving Queries – Find your queries again
Lecture 6: EXERCISE – Query History & Saving Queries
Chapter 3: Filter the data you need with the WHERE Statement
Lecture 1: WHERE statement with Integers
Lecture 2: EXERCISE – Where statement with integers
Lecture 3: ORDER BY to order your results
Lecture 4: EXERCISE – ORDER BY
Lecture 5: WHERE statement with Dates
Lecture 6: EXERCISE – WHERE statement with Dates
Lecture 7: WHERE statement with boolean values (True/False)
Lecture 8: EXERCISE – WHERE with boolean values
Lecture 9: AND – to combine your filters
Lecture 10: EXERCISE – using AND
Lecture 11: OR – to combine your filters
Lecture 12: EXERCISE – OR
Lecture 13: BETWEEN – to combine your filters
Lecture 14: EXERCISE – BETWEEN
Lecture 15: IN – to filter on multiple values
Lecture 16: EXERCISE – IN
Lecture 17: WHERE statement with strings (text)
Lecture 18: EXERCISE – WHERE with text
Lecture 19: LIKE – filter for strings
Lecture 20: EXERCISE – LIKE
Lecture 21: WHERE statement with strings – handling case sensitivity
Lecture 22: NULL
Lecture 23: NOT – filter
Lecture 24: WHERE – Summary
Chapter 4: Calculate more metrics with Aggregate Analytical Functions
Lecture 1: COUNT() – to count number or rows or values
Lecture 2: COUNT() with DISTINCT
Lecture 3: SUM() AND AVG() – To calculate the sum and average
Lecture 4: MIN() and MAX()
Lecture 5: VAR() & STD_DEV()
Chapter 5: GROUP BY
Lecture 1: GROUP BY statement
Lecture 2: GROUP BY & ORDER BY
Lecture 3: GROUP BY multiple columns
Lecture 4: GROUP BY & ORDER BY 1,2,3
Lecture 5: HAVING & GROUP BY
Chapter 6: JOIN tables together
Lecture 1: JOINING tables
Lecture 2: Aliasing Tables
Lecture 3: LEFT JOIN
Chapter 7: Create new Columns with Single Line Functions
Lecture 1: IF() Function
Lecture 2: CASE function
Chapter 8: EXPORT your data
Lecture 1: Exporting to Google Drive or .csv
Lecture 2: Export to Google Data Studio
Instructors
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Annabel Lyle
Data Analyst – Data Studio & Google Analytics
Rating Distribution
- 1 stars: 31 votes
- 2 stars: 48 votes
- 3 stars: 417 votes
- 4 stars: 1180 votes
- 5 stars: 1461 votes
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