Marketing Analytics Dashboard in QuickSight

Build an interactive marketing dashboard with Amazon QuickSight.

Introduction

60 Second Summary

Every marketing team collects web traffic data, social media metrics, and engagement numbers. The challenge is turning that flood of raw data into clear visuals that reveal what's actually driving results.jgfkhgfhfjd

In this project, you will build a Marketing Analytics Dashboard in Amazon QuickSight. You will load sample marketing data, prepare it by removing noisy fields and fixing blank values, then create interactive visuals and publish everything as a shareable dashboard.

What You'll Build

Imagine opening a live dashboard where a color-coded line chart tracks visitor trends month by month, a scatter plot maps desktop versus mobile engagement, and adjusting one date filter updates every chart simultaneously.

By the end of this project, you'll have:

A line chart with custom colors tracking monthly Return visitors and New visitors SEO trends, sitting alongside a scatter plot that reveals the relationship between desktop and mobile engagement.
A prepared dataset that filters out noisy cumulative columns and automatically labels blank events as "Unknown," ensuring every visual you build starts from clean data.
A published Marketing Dashboard with a cross-visual date filter and generative AI features enabled, ready to share with your team.
Secret Mission: Add a bar chart breaking down page views by event type using your custom calculated field.

Are there any prerequisites?

You need an AWS account with console access. This project uses Amazon QuickSight's 30-day free trial, so there are no costs to complete it.

Before We Start

Before we dive in, let's lock in what you're about to build and why it matters.

You're going to take raw marketing data, clean it up, and turn it into a published, interactive dashboard in Amazon QuickSight. By the end you'll have hands-on experience with the full pipeline: data loading, preparation, visualization, and publishing.

Set Up Amazon QuickSight

To build your Marketing Analytics Dashboard, you first need access to Amazon QuickSight. QuickSight is AWS's cloud-native business intelligence service for creating interactive visualizations and dashboards.

In this step, you'll sign up for QuickSight's 30-day free trial directly from the AWS Management Console. The free trial gives you full Author access for 30 days with no charges.

In this step, get ready to:

Sign in to the AWS Management Console and find QuickSight.
Complete the QuickSight signup with your account name, email, SPICE region, and authentication method.
Confirm the QuickSight homepage loads with your 30-day free trial active.

Find QuickSight in the AWS Management Console

Open your browser and sign in to the AWS Management Console.
In the search bar at the top of the console, type Quick.
Choose QuickSight from the search results. You can also find it under the Analytics section in the left navigation.

The QuickSight signup page loads, displaying your AWS account number for verification.

Complete the QuickSight signup

The signup page walks you through a few configuration details to create your QuickSight account. Each choice determines how your account is set up and where your data is stored.

For QuickSight account name, enter a unique name for your account (for example, yourname-quicksight).
For Notification email address, enter your email address. This is where QuickSight sends service and usage notifications.
For the AWS Region, choose the region closest to you. This sets where your SPICE data is stored.
For Authentication method, select the recommended option: Password-based or Single-Sign On.
Review your choices and choose Create account.

What is SPICE?

SPICE stands for Super-fast, Parallel, In-memory Calculation Engine. It stores your prepared data in memory so QuickSight can query it quickly without hitting your original data source every time.

The AWS Region you selected determines where your SPICE data is physically stored. Your free trial includes SPICE capacity.

Account creation takes a moment. Once it completes, you'll see a confirmation screen.

Choose Go to Quick to open the QuickSight homepage.

Before you continue, what do you expect to see on the QuickSight homepage?

The QuickSight start page loads with a left navigation menu showing Analyses, Dashboards, Data, and other options. Your 30-day free trial is now active.

Not seeing the QuickSight homepage?

If account creation seems stuck, wait a minute and refresh the page. Account provisioning can take up to a minute.
If you see a permissions error, your AWS IAM user may not have the required permissions to create a QuickSight account. Check that your IAM user has the necessary QuickSight signup permissions.
If the account name was rejected, try a different name. QuickSight account names must be globally unique.

Help me troubleshoot my QuickSight account creation. I completed the signup form but I'm not seeing the QuickSight homepage.

Your QuickSight account is live and your 30-day free trial is running. Next up, you'll load sample marketing data and create your first visualization.

Load Sample Data and Create Your First Visual

Your QuickSight account is set up and the 30-day free trial is running. Now it's time to get real data on screen.

QuickSight ships with built-in sample datasets that mirror real-world marketing analytics. In this step, you'll load that data, let QuickSight's AutoGraph feature pick the best chart type for you, and spot a data quality problem lurking in the raw dataset.

In this step, get ready to:

Load the Web and Social Media Analytics sample dataset.
Build a line chart using AutoGraph.
Spot blank values hiding in the Events field.

Load the Web and Social Media Analytics sample dataset

QuickSight includes sample datasets you can use right away. The one you need is called Web and Social Media Analytics, and it contains marketing data like visitor counts, mailing list signups, and social media metrics.

In the left navigation menu, choose Analyses.
Look for the Web and Social Media Analytics sample dataset on the Analyses page.

✔️ I see the Web and Social Media Analytics dataset

Choose Web and Social Media Analytics.
Select Use in Analysis.

QuickSight opens a new analysis with the sample data loaded and ready to visualize.

ⓧ I don't see any sample data

Some QuickSight accounts don't pre-load sample datasets. You can upload the data manually instead.

Download the sample data file from the QuickSight sample data documentation. Look for the web-and-social-analytics.csv.zip download link on that page.
Unzip the downloaded file to get web-and-social-analytics.csv.
Return to QuickSight and choose Data from the left navigation menu.
Choose New, then Dataset.
Choose Upload file.
Select the web-and-social-analytics.csv file from your computer.
Choose Next on the Confirm file upload settings screen.
Choose Visualize on the Data source details screen.

QuickSight opens a new analysis with your uploaded data. You can skip straight to the next substep.

You should now see the analysis editor with a Fields list pane showing all available columns from the dataset.

Don't see the Fields list pane?

If the Fields list pane is not visible, look for a small expand arrow or toggle icon on the left side of the analysis editor. Choosing it reveals the full list of available fields.

help me find the Fields list pane in my QuickSight analysis

Build your first visual with AutoGraph

AutoGraph automatically picks the best chart type based on the fields you select. You choose the data columns and AutoGraph handles the rest.

In the Fields list pane, choose the Date field.
Then choose Mailing list adds.

AutoGraph automatically creates a line chart showing mailing list additions over time. You now have a working visualization built from real marketing data.

What is AutoGraph?

AutoGraph is QuickSight's default visualization mode. It analyzes the data types of the fields you select and picks the chart type that fits best.

For a date field paired with a numeric field, it chooses a line chart. If you selected two categorical fields instead, it might pick a bar chart or pivot table. You can always override AutoGraph by choosing a specific visual type manually.

🙋‍♀️ Don't see a line chart?

Make sure you selected Date first, then Mailing list adds. The selection order affects how AutoGraph assigns fields to axes.

help me fix my AutoGraph line chart in QuickSight

Spot data quality issues in the Events field

Your line chart looks clean because the Date and Mailing list adds columns have solid data. Not every field in this dataset is that reliable.

Before you visualize the next field, take a guess. What do you think will happen when you chart the Events column? Will it show a clean breakdown of event types?

Choose Insert, then Add visual on the application bar to create a new blank visual.
Choose the Events field from the Fields list pane.

Look at the visual that appears. Some data points show up as blank or empty entries. These are not zeroes. They are missing values in the raw dataset where the Events field was never filled in.

Why do blank values matter?

Blank entries skew every chart, aggregation, and filter built on that field. A bar chart counting events by type would include a mystery blank category with no label.

Any dashboard built on this raw data would mislead the people reading it. Fixing these gaps at the data level is essential before building real visuals.

You have a working analysis with your first chart and a clear picture of where the raw data falls short. Next up, you'll clean and transform the dataset so every visual tells an accurate story.

Prepare Your Dataset for Clean Analysis

In the last step, you saw what happens when you build visuals from raw data. The Events field had blank values that pollute your charts, and cumulative columns like Twitter followers cumulative add noise without useful insight.

Amazon QuickSight has data preparation tools that fix these issues at the dataset level. Every analysis built from a prepared dataset automatically inherits the clean fields. In this step, you'll strip out the noisy columns, rename a confusing field, and create a calculated field that replaces those blank Events values with something meaningful.

In this step, get ready to:

Exclude noisy cumulative fields from the dataset.
Rename a field for clarity and add a calculated field to replace blank Events values.
Save the prepared dataset for use in future analyses.

Exclude noisy fields from the dataset

The raw dataset includes running totals for Twitter followers and mailing list size. These cumulative columns can skew averages and distort trend lines because they only go up over time. Removing them keeps your visuals focused on the metrics that actually fluctuate.

Choose Data in the left navigation pane.
Choose Datasets.
Find the Web and Social Media Analytics dataset and choose it.
Choose Edit/Preview data to open the data preparation page.

You should see the full dataset preview with all the raw fields listed in the Fields pane on the left.

In the Dataset Name field at the top, replace the default name with Marketing Sample.
In the Fields pane, find the Twitter followers cumulative field.
Choose the three-dot menu next to it and choose Exclude field.
Repeat for the Mailing list cumulative field. Choose its three-dot menu and choose Exclude field.

Both fields should disappear from the Fields pane. Your dataset now has two fewer columns of noise.

Select multiple fields at once

You can hold Command (macOS) or Ctrl (Windows) to select multiple fields at once before excluding them.

🙋‍♀️ Can't find the three-dot menu?

Hover directly over the field name in the Fields pane. The three-dot icon appears on hover to the right of the field name.

If you don't see the Fields pane at all, make sure you're on the data preparation page (opened by choosing Edit/Preview data), not the dataset summary page.

Help me find the field exclusion option in QuickSight's data preparation page.

Rename the Website Pageviews field

Field names flow directly into chart labels. A name like Website Pageviews is readable, but Website page views is cleaner on an axis label.

In the dataset preview pane, scroll to the Website Pageviews field.
Choose the pencil icon next to the field name to edit it.
In the Edit field page, change the Name to Website page views.
Choose Apply.

The field name updates in the Fields pane and in the dataset preview header. Every visual that uses this field will now display the cleaner label.

Add a calculated field to fix blank Events

In Step 2, you saw blank entries when you tried to visualize the Events field. Those blanks are empty strings in the raw data. A calculated field can check each value and replace empty strings with the word Unknown so every event has a visible category in your charts.

Scroll to the top of the Fields pane.
Choose Add calculated field.
In the Add name field, enter populated_event.

In the Functions pane on the right, double-click the ifelse function.
Expand the Field list dropdown and double-click the Events field.
Complete the formula in the editor so it reads exactly like this:

ifelse(strlen({Events})=0, 'Unknown', {Events})

What does this formula do?

This formula checks every row in the Events column. strlen({Events})=0 tests whether the Events value is an empty string (zero characters long).

If it is empty, ifelse replaces it with Unknown. If it already has a value, the original value passes through unchanged.

Choose Save to save the calculated field.
Choose Save again to save the entire dataset.

Seeing a formula error?

Make sure the curly braces around {Events} are present in both places. QuickSight uses curly braces to reference field names inside formulas.

Check that the single quotes around 'Unknown' are straight quotes, not curly/smart quotes. Some text editors auto-correct quotes, which breaks the formula.

Help me debug my calculated field formula in QuickSight.

Before you check the Fields pane, think about what you expect to see. How many changes did you make to this dataset, and where should each one appear?

Look at the Fields pane now. The Marketing Sample dataset should show the two cumulative fields gone, Website Pageviews renamed to Website page views, and a new populated_event calculated field at the top of the list.

Your dataset is clean and ready for serious analysis. Next up, you'll build a proper multi-visual analysis with a line chart and scatter plot that tell different parts of the marketing story.

Build a Multi-Visual Analysis

Your Marketing Sample dataset is prepped and ready. Excluded fields, a renamed column, and a calculated field mean every visual you build from here starts with clean data.

A single chart can only tell one part of the marketing story. In this step, you'll create a new Amazon QuickSight analysis with two visual types that reveal different patterns in the data.

In this step, get ready to:

Create a new analysis from the Marketing Sample dataset.
Build a line chart showing Return visitors over time using AutoGraph.
Add a scatter plot comparing desktop and mobile unique visitors.

Create a new analysis and build a line chart

An analysis is your working canvas in QuickSight. You'll connect it to the Marketing Sample dataset and let QuickSight's AutoGraph feature automatically pick the best chart type for the fields you select.

Choose Analyses from the left navigation menu.
Choose Create analysis.
Select the Marketing Sample dataset.
Choose Use in Analysis.

A New sheet pop-up appears with two options: Interactive sheet and Pixel perfect report.

Choose Interactive sheet.
Choose Add.

Your analysis canvas opens with a blank visual and the Fields list pane on the left showing every field from your prepared dataset.

In the Fields list pane, choose the Date field.
Choose the Return visitors field.

A line chart appears on the canvas showing Return visitors plotted over time. You did not pick the chart type. AutoGraph chose it automatically based on the fields you selected.

What is AutoGraph?

AutoGraph is selected by default in every new visual. It looks at the data types of the fields you choose and automatically picks the visual type that fits best.

A date field plus a numeric field? AutoGraph picks a line chart. Two numeric fields? It picks a scatter plot. You can always override the choice by selecting a different visual type manually.

🙋‍♀️ Don't see a line chart?

Make sure you selected the Marketing Sample dataset when creating the analysis, not the original Web and Social Media Analytics dataset.
Confirm that Date and Return visitors are both highlighted in the Fields list pane. Clicking a field once selects it. Clicking again deselects it.
help me figure out why my line chart isn't showing up in QuickSight

Add a scatter plot visual

The line chart shows visitor trends over time. A scatter plot will reveal something different: the relationship between desktop and mobile engagement on any given date.

Choose Insert on the application bar.
Choose Add visual.

A new blank visual appears on the canvas. This time, you'll pick the chart type yourself instead of letting AutoGraph decide.

In the Visual types pane, choose the scatter plot icon.
From the Fields list pane, choose Desktop Uniques to populate the X axis field well.
Choose Mobile Uniques to populate the Y axis field well.
Choose Date to populate the Group/Color field well.

What are field wells?

Field wells are the drop zones at the top of each visual that control what data appears and how it is mapped. Each visual type has its own set of wells.

For a scatter plot, the X axis and Y axis wells set which numeric fields are compared. The Group/Color well adds a third dimension by coloring each data point based on a field. Here, coloring by Date lets you spot whether the desktop-to-mobile relationship shifts over time.

Before you review your analysis, think about what you expect to see. How many visuals should be on the canvas, and what data does each one show?

Your analysis should now contain two visuals. The line chart shows Return visitors plotted by Date. The scatter plot shows Desktop Uniques on the X axis, Mobile Uniques on the Y axis, with each point colored by Date.

Scatter plot looks empty or wrong?

Check the field wells at the top of the scatter plot visual. Desktop Uniques should be in X axis, Mobile Uniques in Y axis, and Date in Group/Color.
Make sure you selected the scatter plot visual (click on it) before choosing fields. If the line chart was still selected, the fields would be added to the line chart instead.
help me fix my scatter plot in QuickSight

Two visuals, two different stories from the same dataset. Next up, you'll customize colors, adjust date granularity, add a cross-visual filter, and publish the whole thing as a shareable dashboard.

Customize Your Visuals and Publish Your Dashboard

Your analysis has two visuals telling different parts of the marketing story. One tracks return visitor trends over time, and the other maps the relationship between desktop and mobile engagement.

These charts work, but they can tell a stronger story. Customizing colors, adjusting date granularity, and adding cross-visual filters turns separate charts into a cohesive dashboard that others can explore.

In this step, get ready to:

Customize the line chart with a second measure, custom color, and monthly granularity.
Apply a cross-visual date filter that updates every chart simultaneously.
Publish the finished analysis as a shareable Marketing Dashboard.

Add a second measure and customize your line chart

Your line chart currently shows a single measure. Adding a second measure lets you compare trends side by side on the same axis.

Select the line chart visual by clicking on it.
In the Fields list pane, choose New visitors SEO to add it as a second measure.

The chart updates with a second line tracking New visitors SEO alongside Return visitors.

Choose the end of the Return visitors line on the chart.
Choose Color Return visitors.
Select the red icon from the color selector.

The Return visitors line is now red, making it easy to distinguish from New visitors SEO at a glance.

Choose the Date field in the X axis field well.
Choose Aggregate.
Choose Month.

Your line chart now shows both measures aggregated by month instead of by day. Monthly granularity smooths out daily noise and reveals clearer trends.

What does changing aggregation do?

Date aggregation controls how QuickSight groups data points on the X axis. Switching from Day to Month collapses all data within each calendar month into a single point.

This is useful when daily data is noisy and you want to spot seasonal or monthly patterns instead.

Resize both visuals by dragging the resize handle in the lower right corner of each visual.
Drag the scatter plot next to the line chart so they sit side by side.

Both visuals are now arranged side by side, giving you a clean two-panel view of your marketing data.

Visuals not sitting side by side?

Make sure you are dragging the move handle at the top of the visual, not the resize handle at the bottom right. The move handle repositions the visual on the canvas.

If both visuals are too wide to fit next to each other, resize each one to roughly half the canvas width first, then drag one alongside the other.

Help me arrange my QuickSight visuals side by side.

Apply a cross-visual date filter

A filter on a single visual only affects that one chart. A cross-visual filter updates every visual in your analysis at once, keeping all your charts in sync.

Select the scatter plot visual by clicking on it.
Choose Insert on the application bar.
Choose Add Filter.
Choose the Date field to filter on.

A new Date filter appears in the Filter pane on the left.

Select the new filter to expand it.
In the Edit filter pane, for Condition, choose the After comparison type.
Choose Date to open the date picker.
Pick 2014 for the year.
Pick January for the month.
Pick 1 on the calendar.
Choose Apply.

The scatter plot now filters to show only data after January 1, 2014. The line chart still shows the full date range because the filter currently applies to a single visual.

In the Filter pane, choose the Date filter again to expand its scope options.
Choose Single visual and change it to All visuals of this dataset.

Both visuals now filter to show only data after January 1, 2014. The line chart and scatter plot update simultaneously.

Why filter to all visuals?

A single-visual filter is useful when you want one chart zoomed into a date range while others show the full picture. A cross-visual filter keeps every chart in sync, which is essential for a dashboard where viewers expect all visuals to tell the same time-bound story.

🙋‍♀️ Filter not applying to both visuals?

Make sure you changed the filter scope from Single visual to All visuals of this dataset. If the scope still shows Single visual, click the scope dropdown and select the correct option.

Help me apply a cross-visual filter in QuickSight.

Publish your analysis as a dashboard

Publishing converts your analysis into a read-only dashboard that you can share with other QuickSight users. The dashboard preserves your filters, layout, and visual configuration.

Choose Publish from the application bar.
Choose Publish dashboard.
Choose Publish as a new dashboard.
For Dashboard name, enter Marketing Dashboard.

Under Select sheets, choose All sheets.
Under Generative capabilities, enable Allow executive summary.
Enable Allow Data Q&A.
Choose Publish.

What are the generative capabilities?

Allow executive summary uses generative AI to build a written summary of each sheet in the dashboard. Allow Data Q&A enables Amazon Q in QuickSight, which lets dashboard viewers ask natural-language questions about the data.

Both features are available during your free trial at no extra cost.

On the Share dashboard page that opens, choose the X icon to close it.

Share later if needed

You can always share the dashboard later by opening it and choosing Share at the upper right. For now, closing the share page is all you need.

Before you check the published dashboard, what do you expect to see? Think about which visuals should appear and how the date filter should affect the data.

Your Marketing Dashboard is now published. The line chart shows Return visitors in red and New visitors SEO aggregated by month. The scatter plot shows Desktop Uniques vs Mobile Uniques. Both visuals are filtered to data after January 2014 and arranged side by side.

Dashboard not showing your visuals?

Make sure you chose All sheets under Select sheets before publishing. If you only published a specific sheet, the dashboard may be missing visuals from other sheets.

If the filter is not applied, return to the analysis by choosing Analyses in the left navigation, open your analysis, confirm the Date filter scope is set to All visuals of this dataset, and re-publish.

Help me troubleshoot my published QuickSight dashboard.

Secret mission

Add an Event Breakdown Bar Chart

Your dashboard shows visitor trends and device patterns, but it does not reveal what types of events drive engagement. In this mission, you will add a vertical bar chart using the populated_event calculated field you built during data preparation. The result proves your data cleanup paid off and completes the dashboard with a third visual type.

Clean Up Your Resources

This project runs entirely within Amazon QuickSight's 30-day free trial. During the trial, you will not be charged. After 30 days, you will be billed at the Author rate of $24 per user per month.

Cost warning

If you do not unsubscribe from QuickSight before your 30-day free trial ends, you will be automatically billed $24/user/month for Author access. The $250/month infrastructure fee only applies if you have Pro users or active Topics/Dashboard Q&A enabled.

Set a calendar reminder for 30 days from today to revisit this page and decide whether to keep or delete your QuickSight account.

Resources you used:

Amazon QuickSight account (30-day free trial, then $24/user/month for Author access).
Marketing Sample dataset (stored in SPICE, uses free trial SPICE capacity).
Marketing Dashboard (stored within QuickSight, includes all analyses and visuals).

Decide whether to keep your resources running, pause them to come back later, or delete them entirely.

Keep everything running

No action needed. Choose this if you are still actively building or exploring QuickSight during your free trial.

Your QuickSight free trial lasts 30 days from the date you signed up.
During the trial, you will not be charged for Author access or SPICE storage.
Your Marketing Dashboard, Marketing Sample dataset, and analysis will remain available in your QuickSight account.
After 30 days, you will be billed at $24/user/month for Author access unless you unsubscribe.

Pause - I'll come back to this later

There is no pause option for QuickSight. The free trial runs for 30 days from the date you signed up, regardless of usage.

Your resources (dashboard, dataset, analysis) stay intact for the full 30-day trial period.
If you return within 30 days, everything will be exactly as you left it.
If you do not plan to return before the trial ends, follow the Delete tab instructions to avoid charges.

Delete - I don't want to use this again

Remove your QuickSight account entirely to avoid charges after the trial. This permanently deletes all QuickSight resources. Your AWS account itself is not affected.

In QuickSight, choose your profile icon on the application bar, then choose Manage Quick.
Choose Account settings, then choose Manage to open the Account termination page.
Confirm you are viewing the correct QuickSight account by checking the account name displayed.
Toggle off Account termination protection. This enables the Delete account section.
Enter the confirmation word shown on your screen to finalize deletion.

This action is permanent

Deleting your QuickSight subscription permanently destroys all data across all AWS regions. This includes your Marketing Dashboard, Marketing Sample dataset, all analyses, and all QuickSight users. This action cannot be undone.

💡 Direct link alternative

You can also reach the Account termination page directly by visiting this URL while signed in to AWS:

https://us-east-1.quicksight.aws.amazon.com/sn/console/unsubscribe

This link works regardless of which AWS Region you selected during setup.

Nice Work!

Nice work! You just built and published a live Marketing Analytics Dashboard in Amazon QuickSight, taking raw sample data through the full pipeline from ingestion to shareable, interactive dashboard.

You've learned how to:

Prepared a dataset for clean analysis by excluding noisy fields, renaming columns, and building a calculated field with QuickSight's formula language.
Built a multi-visual analysis with a line chart and scatter plot, then customized colors, date granularity, layout, and applied a cross-visual date filter so every chart updates simultaneously.
Published the analysis as a shareable Marketing Dashboard with generative AI capabilities enabled.
Secret Mission: Added an event breakdown bar chart using the populated_event calculated field and re-published the dashboard.

Ready to quiz yourself?