From the course: ETL in Python and SQL
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Loading data into relational databases
From the course: ETL in Python and SQL
Loading data into relational databases
- [Instructor] Now that we know the difference between Databases, Data Warehouse, Data Lakes, and Data Lakehouses, we will load our transform data from our Jupyter Notebook to our H Plus Sports Data Warehouse. In this lesson, we will be creating a PostgresSQL database on ElephantSQL, a hosting service that provides a browser tool for SQL queries where you can create, read, updates and delete data directly from your web browser. This will serve as our H Plus Sport Data Warehouse. To create your Postgres Database Instance, you can follow along as we go to www.elephantsql.com/plans.html. Here you can sign up and create a free TINY TURTLE Shared Instance. Let's try that. We would name an instance appropriately. For our instance here, we call it H Plus Sports. And tag it as data_warehouse. Next space would be to select to our Region. Great. We will just go with the default for each of these, and finally we can review our instance. Default and we can create our instance. Great. Now that…
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Contents
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Introduction to data warehouses and data lakes5m 1s
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Loading data into relational databases8m 1s
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Data quality checks and validation with SQL3m 27s
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Challenge: Transform the data and remove duplicates and nulls40s
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Solution: Transform the data and remove duplicates and nulls2m 37s
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