Learn SQL for Data Analysis with Google Big Query
- 2 hours on-demand video
- 16 articles
- Full lifetime access
- Access on mobile and TV
- Certificate of Completion
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- 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
- No prior SQL or database knowledge required!
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 features
How 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:
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.
- Data Analysis
- Data Scientist
- Anyone who wants to learn SQL or Data Analysis!
You now know how to :
1. Access Query History - Phew! This means that you'll never lose a query again. BigQuery keeps track of every query that you have run in the interface so that you can run it again
2. Save Queries - You can choose to 'save query' and name your query something memorable - so that you can always go back to the 'Saved Queries' tab and find the ones that are important to you.
3. Share Saved Queries with others - If you want others to also be able to run your queries - click 'link sharing ON' and then copy the url. This will allow whoever you share it with to also run and save your query.
If you haven't already:
Find a historical query in 'query history' and select 'run in editor'
Save a query and then find it again under 'Saved Queries'
Turn link- sharing on for this saved query, and copy & paste the url into a new tab in your browser to see what the experience will be like for the person you share the link with.
You now know how to :
1. Use the WHERE clause to filter on dates
You have to specify the date in the format of 'year-month-date'
for example '2019-01-01' if it was 1st January 2019
2. You can use the same operators as we looked at for integers on dates
install_date >= '2018-01-01'
Filter out bike stations that were installed before 1st April 2018. How many were there?
Filter out any bike stations that were not installed on exactly 31st October 2018 (Halloween)
and then maybe have a look at the ones that were installed on Halloween ?
If you get stuck along the way remember you can always post in the Q&A forum!