This page provides you with instructions on how to extract data from Amazon S3 CSV and analyze it in Google Data Studio. (If the mechanics of extracting data from Amazon S3 CSV seem too complex or difficult to maintain, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)
What is Amazon S3?
Amazon S3 (Simple Storage Service) provides cloud-based object storage through a web service interface. You can use S3 to store and retrieve any amount of data, at any time, from anywhere on the web. S3 objects, which may be structured in any way, are stored in resources called buckets. One common use is to store files in comma-separated values (CSV) format, in which each record consists of multiple values separated by commas.
What is Google Data Studio?
Google Data Studio is a simple dashboard and reporting tool. It's free and easy to use, but it lacks the sophisticated features of higher-end reporting software. Many of the connectors it supports are for Google products, but third parties have written partner connectors to a wide variety of data sources. Its drag-and-drop report editor lets users create about 15 types of charts.
Getting CSV data out of S3
AWS has both a REST API and command-line utilities that you can use to get at resources stored in the platform. To retrieve objects you need to know the object and host names, as well as your AWS authorization information.
Preparing CSV data
If you don't already have a data structure in which to store the data you retrieve, you'll have to create a schema for your data tables. Then, for each value in each table, you'll need to identify a predefined datatype (INTEGER, DATETIME, etc.) and build a table that can receive them.
Loading data into Google Data Studio
Google Data Studio uses what it calls "connectors" to gain access to data. Data Studio comes bundled with 17 connectors, mostly to pull in data from other Google products. It also supports connectors to MySQL and PostgreSQL databases, and offers 200 connectors to other data sources built and supported by partners.
Using data in Google Data Studio
Google Data Studio provides a graphical canvas onto which users drag and drop datasets. Users can set dimensions and metrics, specify sorting and filtering, and tailor the way reports and charts are displayed.
From Amazon S3 CSV to your data warehouse: An easier solution
As mentioned earlier, the best practice for analyzing Amazon S3 CSV data in Google Data Studio is to store that data inside a data warehousing platform alongside data from your other databases and third-party sources. You can find instructions for doing these extractions for leading warehouses on our sister sites Amazon S3 CSV to Redshift, Amazon S3 CSV to BigQuery, Amazon S3 CSV to Azure SQL Data Warehouse, Amazon S3 CSV to PostgreSQL, Amazon S3 CSV to Panoply, and Amazon S3 CSV to Snowflake.
Easier yet, however, is using a solution that does all that work for you. Products like Stitch were built to move data automatically, making it easy to integrate Amazon S3 CSV with Google Data Studio. With just a few clicks, Stitch starts extracting your Amazon S3 CSV data, structuring it in a way that's optimized for analysis, and inserting that data into a data warehouse that can be easily accessed and analyzed by Google Data Studio.