Welcome back to the Data Insights specialization. I'm Evan and I'll be your guide on your big data journey. In this course, we'll cover how to connect and bring in a new datasets into BigQuery, and I can join them all together to create a proper data analytics warehouse. We'll first cover what different types of data BigQuery can connect to and ingest. Which range from things like CSV files, or files at Google Cloud Storage to more nuanced concepts like querying a Google Spreadsheet directly, or ingesting things like JSON, or AVRO formats. Now no topic on data storage would be complete without talking about a few of the unique ways you can partition your datasets and other flexible storage options for you to explore. Then we'll move on to the core differences between BigQuery permanent and temporary tables, as well as logical view creation, and when you should use each of those three in your reporting applications. Lastly, we'll close out the course with a few data visualization options and best practices. So you can present and share your insights and interactive dashboards, for your own audiences. Let's get started first with how you can set up and use BigQuery to store your new datasets.