Quicksight Tutorial: A Step-by-Step Guide to Data Analysis and Visualization

Quicksight is a fast and powerful business intelligence service that allows you to easily connect to a variety of data sources, including Amazon Redshift, Amazon S3, and Amazon RDS.

With Quicksight, you can create a data set by dragging and dropping fields from a data source into a data set, and then use that data set to create visualizations.

In this tutorial, we'll walk you through the process of creating a data set and visualization in Quicksight, step by step.

To get started, make sure you have an Amazon Web Services (AWS) account and have enabled Quicksight in the AWS Management Console.

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Amazon QuickSight is a cloud-based Business Intelligence tool that's a part of the Amazon Web Services (AWS) universe.

To get started with QuickSight, you can take an online course that covers its basics, including how to use its different functions and connect it to various data sources within and outside of AWS.

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The course will also cover how to prepare your data, create analyses, and share your project results with others.

QuickSight is a highly scalable and flexible data analysis tool, making it a great option for those who want to quickly analyze their data.

You can start by clicking the "New Analysis" button in the QuickSight dashboard and defining what kind of data to import.

Some of the topics covered in the course include how to use QuickSight and its different functions, understand the workflow of QuickSight, and connect QuickSight to different data sources.

You'll also learn how to prepare your data in QuickSight, for example by adding filters and calculated fields, and how to easily create your analysis by building multiple visuals.

The course is designed for those who have never worked with QuickSight before, but it's also suitable for those who have worked with other Business Intelligence tools and want to take a look at new tools.

Here are some key benefits of using QuickSight:

By taking the course and learning the basics of QuickSight, you'll be able to quickly analyze your data and make informed decisions.

Connecting to your data warehouse from QuickSight is the first step to creating visualizations. Log in to QuickSight and choose your data source, which can be an RDS instance or Redshift cluster.

If your data isn't listed, click Connect to another data source or upload a file, and choose Redshift. You'll need to enter your Panoply credentials.

Choose the schema you want to work with, and a table within that schema, then click Select. You can also import the data to SPICE, QuickSight's in-memory optimized calculation engine, for better performance.

To add more tables to your visualization, go to the main QuickSight page and click New data set. This allows you to pick your database and select the next schema and table you want to work with.

You can also use the data preparation page to join tables for more complex visualizations. However, if you're familiar with SQL, you may find this process cumbersome.

Fortunately, QuickSight provides a better alternative for SQL users. From the main QuickSight screen, click New analysis, then New data set, and choose your data source. This time, instead of picking a schema and table, click Use custom SQL.

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To start creating an analysis from scratch, download a dataset into the QuickSight context, such as the sample Superstore dataset available for free.

You can choose from a list of available datasets, but since you're going to use your own dataset, click on the New data set button to proceed.

To create an overview from your dataset, press Visualise, and a new analysis will open up without any graphics.

Rename the analysis as needed and go ahead with the visual development.

To make your first picture, pick the visual form bar from the panel and drag and drop the State and Sales panels to the Y-axis and Value boxes respectively from the field list panel.

Choose the visual form as Line and drag and drop the Date of Order and Sales respectively to the X-axis and Value tab.

Such analyses are automatically saved by default, which means you don't need to specifically save them.

This function can be toggled by selecting Autosave on or off as necessary.

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Analyzing Data is a breeze in QuickSight. You can create an analysis from scratch by downloading a dataset, such as the sample Superstore dataset.

To start, you'll need to download a dataset into the QuickSight context. This can be done by choosing from a list of available datasets or uploading your own. In this case, we're using the Superstore dataset, which can be downloaded for free.

To create an overview of your dataset, press the Visualise button. A new analysis will open up, and you can rename it as needed. From there, you can start building your visualizations, such as a bar chart to see sales made on a state-by-state basis.

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To analyze data effectively, you can choose between using tables or direct queries. Using a full table linked to a large database may take longer to load and will use a greater capacity of SPICE.

You can choose to connect to a database like Athena, which is a great option for many users. To do this, you'll need to name and create your data source.

If you choose to use a full table, you'll have access to the full table in your analysis, but it may take longer to load and use more capacity. This is because it's pulling in all the data from the database, which can be a lot.

Using custom SQL to query your database directly is another option. This can be a good choice if you only need to access specific data.

Filters are a powerful tool in data analysis, allowing you to exclude or include certain data from your visual.

To access filters, navigate to the left side of your screen underneath the "Visualize" tab. From there, select the visual you want to filter and click "Create one...".

You can filter with a measure or dimension, and the workflow will guide you through completing the filter, including aggregations, operators, values, and null responses.

Customizing visuals in QuickSight is a breeze, and you can do it in a few key ways. One way is by selecting the arrow dropdown in the top right of a visual.

QuickSight offers some basic formatting tools, such as axis labels, data labels, legend options, groups and colors, and title. You can access these options by selecting the arrow dropdown in the top right of a visual.

Changing the colors of a visual may require you to select a data point on the graph and change that specific color. For certain visuals, this is a necessary step to get the look you want.

Sharing your Quicksight analysis with others is a breeze. Click on the Share icon on the menu bar and select Publish dashboard.

To make your dashboard visible to specific users, provide individual email addresses or select all users under the account.

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Sharing the analyses allows you to publish it and share it with other users. You can share the analysis by developing a read-only version, also known as a dashboard.

To publish the analysis as a dashboard, click on the Share icon on the menu bar and select Publish dashboard. Give the dashboard a relevant name and click on Publish dashboard.

You can choose which users should have access to the dashboard by providing individual email addresses or selecting all users under the account. Once the dashboard is ready, it will be visible to all the users under the account used.

QuickSight is a great choice when your data is stored in an AWS cloud system or integrated with QuickSight. It's simpler, faster, and easier to use than competitors like Tableau and Microsoft BI.

Tableau takes longer to learn due to its complexity, but it offers a wide range of ways to manipulate and visualize data.

From my experience, connecting systems and loading data sets with Tableau is more tedious than with QuickSight.