Marketing Analytics Dashboard

Introduction

30 Second Summary

Every marketing team collects data from websites, social media, and email campaigns. Turning that raw data into clear visuals is what helps you spot trends, prove what's working, and make better decisions.

In this project, you will build a marketing analytics dashboard using Amazon QuickSight. You will upload sample data, create multiple chart types, add interactive filters, and publish a shareable dashboard.

What You'll Build

A multi-visual marketing dashboard in Amazon QuickSight that visualizes web and social media data with interactive date filters.

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

• A prepared dataset with excluded fields, renamed columns, and a calculated field in Amazon QuickSight.
• An analysis containing a line chart, bar chart, and KPI visual showing marketing metrics over time.
• A published, shareable dashboard with interactive date filters that viewers can use to explore the data.
• Secret Mission: Add an ML-powered forecast to your line chart that predicts future mailing list growth.

Are there any prerequisites?

You need an existing AWS account with admin-level access. The project uses Amazon QuickSight's 30-day free trial, which you will set up in Step 1.

Before We Start

Before We Start...

Sign Up for Amazon QuickSight

Amazon QuickSight is a fully managed business intelligence service built into AWS. It runs entirely in the browser, so there is nothing to install on your computer.

In this step, you will create your QuickSight account through the AWS Management Console and download the sample marketing data file you will visualize throughout this project.

In this step, get ready to:

• Create an Amazon QuickSight account within your existing AWS setup.
• Download and unzip the sample marketing data file.

Create your Amazon QuickSight account

QuickSight requires a separate signup within your AWS account. This activates the service and provisions your SPICE storage (the in-memory engine that powers fast dashboard queries).

• Sign in to the AWS Management Console at console.aws.amazon.com.
• In the search bar at the top of the console, type QuickSight and select Amazon QuickSight from the results.
• Click Sign up for QuickSight.

What is SPICE?

SPICE stands for Super-fast, Parallel, In-memory Calculation Engine. It caches your data so dashboards load instantly without querying the source every time.

During signup, you select an AWS Region for SPICE storage. Pick the Region closest to you for the best performance.

The signup wizard asks for a few details. Fill in each field one at a time:

• Enter a unique name in the QuickSight account name field. This must be globally unique across all AWS accounts.
• Enter your email address in the Notification email address field.
• Select your preferred AWS Region for SPICE capacity. Choose the Region closest to your location.
• Under authentication method, select Password-based or Single Sign-On. This is the recommended option for individual accounts.
• Review your selections and click Create account.

Why Password-based or Single Sign-On?

This authentication method lets you sign in using your existing AWS credentials. It is the simplest option for individual learners and small teams. The other options (IAM Identity Center, Active Directory) are designed for larger organizations with centralized identity management.

Account creation takes a moment. Once it finishes, you will see a success screen.

• Click Go to Amazon QuickSight to open the QuickSight console.
• Verify you see the QuickSight homepage with the left navigation menu showing options like Analyses, Dashboards, and Data.

Don't see the QuickSight signup page?

Make sure you are signed in with an account that has admin-level access (IAM admin or root). If you see an access denied error, check your IAM permissions. Your account needs the quicksight:Subscribe permission at minimum.

If the button says Open QuickSight instead of Sign up, your account already has QuickSight enabled. Click it to proceed directly to the console.

Help me troubleshoot my QuickSight signup issue.

Your 30-day free trial

QuickSight includes a 30-day free trial for up to 25 users. You will not be charged during this project as long as you cancel before the trial ends. The Before You Go section at the end of this project shows you how.

Download the sample data file

You need a CSV file containing web and social media marketing data. AWS provides this as a sample dataset you can download directly from their documentation.

• Open the AWS QuickSight sample data page in a new browser tab.
• Find the Web and social media analytics data (marketing) link and click it to download web-and-social-analytics.csv.zip.
• Locate the downloaded ZIP file on your computer (usually in your Downloads folder).
• Unzip the file. On macOS, double-click the ZIP. On Windows, right-click and select Extract All.
• Confirm you have a file named web-and-social-analytics.csv ready on your computer.

Save it somewhere easy to find

Move the unzipped CSV file to your Desktop or a dedicated project folder. You will need to locate it again in the next step when you upload it to QuickSight.

Can't find the download link?

The sample data page lists several datasets. Look for the one labeled Web and social media analytics data (marketing). If the page layout has changed, try searching the page for "web-and-social" using Cmd+F (macOS) or Ctrl+F (Windows).

Help me find and download the QuickSight sample data file.

Your QuickSight account is ready and your data file is waiting on your computer. Next up, you will upload this CSV into QuickSight and prepare it for visualization.

Upload and Prepare the Dataset

Your QuickSight account is ready to go. Now it's time to bring in data and shape it for analysis.

Raw data rarely arrives in perfect form. In this step, you'll upload the sample marketing CSV, remove unnecessary fields, and create a calculated field that handles missing values cleanly.

In this step, get ready to:

• Upload the sample CSV file and create a dataset in QuickSight.
• Exclude unnecessary fields and rename a column for clarity.
• Add a calculated field that fills in missing event data.

Upload the CSV and create a dataset

QuickSight needs a dataset before you can build any visuals. You'll upload the CSV file you downloaded earlier, and QuickSight will import it into SPICE (its in-memory calculation engine) for fast querying.

• Click Data in the left navigation menu.
• Click New Dataset in the top right corner.
• Choose Upload a file.
• Select the web-and-social-analytics.csv file from your computer.
• Click Next to confirm the file upload settings.
• Click Visualize to import the data into SPICE and open it in an analysis.

QuickSight opens a new analysis with a blank canvas. You'll build visuals on this canvas in the next step.

What just happened?

QuickSight imported your CSV into SPICE and created a dataset. It also auto-created an analysis (a workspace where you build visuals) connected to that dataset.

SPICE caches your data in memory so visuals load quickly, even as your datasets grow larger.

File upload not working?

Make sure you unzipped the downloaded file first. QuickSight needs the .csv file, not the .zip archive.

If you see a permissions error, confirm your QuickSight account finished setting up in Step 1.

Help me troubleshoot my QuickSight file upload

Edit the dataset and clean up fields

The raw dataset has fields you won't need for this dashboard. Excluding them keeps your field list manageable and your visuals focused.

• Click the QuickSight logo or Data in the left navigation to return to the main menu.
• Click Data in the left navigation.
• Find the Web and Social Media Analytics dataset and click on it.
• Click Edit dataset.

The dataset editor opens with a preview of your data and a Fields pane on the left.

• Click the dataset name at the top of the page and rename it to Marketing Sample.
• In the Fields pane, find Twitter followers cumulative.
• Click the three-dot menu next to it and choose Exclude field.
• Find Mailing list cumulative and exclude it the same way.
• In the Dataset preview pane, find the Website Pageviews column header.
• Click the pencil/edit icon next to the field name and rename it to Website page views.

Why exclude and rename fields?

Excluding fields removes them from your analysis without deleting the underlying data. This keeps the field list short and focused on the metrics you actually need.

Renaming "Website Pageviews" to "Website page views" improves readability when the field name appears in your visual labels and axes.

Add a calculated field for missing events

Some rows in the dataset have an empty "Events" field. A calculated field lets you replace those blanks with a meaningful label so your visuals display "Unknown" instead of nothing.

• Click Add calculated field at the top of the Fields pane.
• In the Name field, enter populated_event.
• In the formula editor, paste this formula:

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

What does this formula do?

The ifelse function checks a condition. If the Events field has zero characters (is empty), it returns "Unknown". Otherwise, it keeps the original value.

This ensures every row has a meaningful event label when you build visuals later.

• Click Save in the calculated field editor.
• Click Save at the top of the dataset editor to save all your changes.

You should see populated_event listed in the Fields pane alongside your other fields. The dataset name at the top should read "Marketing Sample".

Seeing a validation error on the formula?

Check that the field name {Events} matches exactly what appears in your Fields pane. Field names are case-sensitive.

Make sure you have the curly braces around the field name. Verify there are no extra spaces inside the strlen() function.

Help me fix my QuickSight calculated field formula

Your dataset is cleaned, renamed, and ready for action. Next up, you'll use this prepared data to create your first visuals and start building the dashboard.

Create Your First Visuals

Your dataset is prepped and ready to tell a story. Now it's time to turn those rows of numbers into visuals that reveal trends at a glance.

In this step, you'll build three different visual types in your analysis: a line chart for time-series trends, a bar chart for channel comparison, and a KPI visual for a headline metric.

In this step, get ready to:

• Create a line chart showing mailing list adds over time.
• Add a vertical bar chart comparing monthly SEO visitors.
• Add a KPI visual displaying total website page views.

Open your analysis and create a line chart

An analysis is the workspace where you build and arrange visuals. When you uploaded your dataset in the previous step, QuickSight auto-created one for you.

• From the QuickSight homepage, click Analyses in the left navigation menu.
• Find the analysis that was auto-created with your dataset and click on it to open it.
• In the Data pane on the left, click the Date field.
• Then click the Mailing list adds field.

QuickSight uses AutoGraph to automatically select the best visual type for your selected fields. You should see a line chart appear showing mailing list adds over time.

What is AutoGraph?

AutoGraph analyzes the data types you select (dates, numbers, categories) and picks the most compatible visual type automatically. Since you selected a date field and a numeric field, it chose a line chart to show trends over time.

Don't see your analysis listed?

If no analysis appears under Analyses, you can create one manually. Click New analysis, select your Marketing Sample dataset, and click Use in analysis.

Help me find or create my analysis in QuickSight.

Add a vertical bar chart

Your line chart shows one metric over time. Now you'll add a second visual to compare a different metric by month.

• Click Add in the top menu bar.
• Select Add visual.
• A new blank visual appears on your sheet. In the Visual types pane at the bottom left, select the vertical bar chart type.
• Drag Date from the Data pane to the X axis field well.
• Drag New visitors SEO from the Data pane to the Value field well.
• In the X axis field well, click the three-dot menu next to Date.
• Choose Aggregate, then select Month.

Your bar chart now shows monthly SEO visitor counts. Each bar represents one month of data instead of individual days.

Why aggregate by month?

Daily data in a bar chart creates hundreds of tiny bars that are hard to read. Aggregating by month groups the data into meaningful time buckets so you can spot trends at a glance.

Don't see the three-dot menu in the field well?

Make sure the bar chart visual is selected (click on it first). The field wells appear at the bottom of the visual pane only when a visual is actively selected.

Help me find the aggregation settings for my bar chart.

Add a KPI visual

A KPI visual displays a single headline number. This is useful for showing totals or key metrics that stakeholders want to see immediately.

• Click Add in the top menu bar.
• Select Add visual.
• In the Visual types pane, select the KPI visual type.
• Drag Website page views from the Data pane to the Value field well.

You should see a large number appear representing the total website page views across your entire dataset.

What is a KPI visual?

KPI stands for Key Performance Indicator. In QuickSight, a KPI visual shows a single aggregated number prominently. It's designed to give executives and stakeholders a quick read on the metrics that matter most.

Your analysis now has three visuals covering different angles of the marketing data. Next up, you'll customize these visuals with color changes, date granularity adjustments, and a better layout.

Customize Your Visuals

Your analysis now has three visuals showing different marketing metrics. The default settings work, but customizing them makes patterns easier to spot and the dashboard more readable for stakeholders.

In this step, you will adjust the date granularity on your line chart, add a second metric with a distinct color, and rearrange the layout so the most important number sits at the top.

In this step, get ready to:

• Change the line chart's date granularity from daily to monthly.
• Add a second metric to the line chart and change its color.
• Resize and rearrange your visuals into a clean layout.

Change the line chart date granularity to monthly

Your line chart currently shows mailing list adds by day. Daily data points create a noisy, hard-to-read chart. Switching to monthly aggregation reveals the bigger trends.

• Click on the line chart visual to select it.
• Look at the Field wells section at the top of the visual.
• Click the Date field in the X axis field well.
• Click the three-dot menu that appears.
• Select Aggregate, then choose Month.

The chart updates to show mailing list adds grouped by month instead of by day. You should see a much smoother line with fewer data points.

What is date granularity?

Date granularity controls how time-based data gets grouped. Daily granularity shows every individual day as its own data point. Monthly granularity sums all the days within each month into a single point.

Choosing the right granularity depends on your audience. Executives want monthly trends. Operations teams might need daily detail.

Don't see the Aggregate option?

Make sure you are clicking the Date field inside the X axis field well, not the field in the Data pane on the left. The three-dot menu with Aggregate only appears from the field well.

help me find the Aggregate option for my Date field in QuickSight

Add a second metric and change its color

A single line tells one story. Adding a second metric to the same chart lets you compare trends side by side.

• Click on the line chart to make sure it is selected.
• In the Data pane on the left, find the Return visitors field.
• Drag Return visitors into the Value field well at the top of the visual.

The line chart now displays two lines. One represents mailing list adds and the other represents return visitors.

• Click on the Return visitors line in the chart.
• Click the color swatch that appears.
• Select red from the color picker to differentiate it from the first metric.

You should now see two clearly distinct lines. The mailing list adds line stays its default color and the return visitors line is red.

Why change the color?

When a chart has multiple metrics, distinct colors make it immediately clear which line represents which data. Viewers should never have to squint at a legend to tell two metrics apart.

Can't click the Return visitors line?

If the two lines overlap, try clicking on a section of the chart where the lines are visually separated. You can also look for the metric name in the legend below the chart and click there instead.

help me change the line color in my QuickSight chart

Resize and rearrange your visuals

Layout matters for dashboards. The most important metric should grab attention first, with supporting charts arranged logically below.

• Click and drag the KPI visual to the top of the sheet.
• Resize the KPI visual by dragging its edge handles so it spans the width of the sheet but stays short in height.
• Drag the line chart below the KPI visual, positioning it on the left side.
• Drag the bar chart to sit beside the line chart on the right side.
• Resize both charts by dragging their edges so they sit side by side and fill the width below the KPI.

Your layout should now show the KPI number prominently at the top, with the line chart and bar chart arranged side by side underneath.

Snap to grid

QuickSight snaps visuals to a grid as you drag them. Use this to align edges cleanly. If a visual jumps to an unexpected position, drag it slowly and watch for the blue guide lines.

Visuals overlapping or not aligning?

If your visuals overlap, try making the KPI shorter first to free up space. Then resize the two charts so their combined width fits the sheet. Drag slowly to let the grid snapping guides appear.

help me arrange my QuickSight visuals

Your analysis now has a polished layout with customized visuals. Next up, you will add interactive date filters so viewers can explore different time ranges on their own.

Add Interactive Filters

Your visuals are customized and arranged. Right now, they show all data from the entire dataset, which spans several years.

Stakeholders often want to focus on a specific time period. Filters let you narrow the data without creating separate visuals for each date range. Even better, you can add an on-sheet control so viewers can adjust the date range themselves.

In this step, get ready to:

• Create a date filter on the Date field.
• Expand the filter scope to all visuals in your analysis.
• Add an on-sheet filter control for interactive date exploration.

Create a date filter

A filter restricts which rows of data appear in your visuals. You will create one that hides all data before a certain date.

• Click on any visual in your analysis to select it.
• In the left panel, click Filter to open the Filters pane.
• Click the plus icon (+) at the top of the Filters pane.
• Select the Date field from the list.
• A new Date filter appears in the Filters pane. Click it to expand the filter settings.
• Set the Filter type dropdown to After.
• Set the start date to January 1, 2014.
• Click Apply.

Your selected visual updates to show only data from after January 1, 2014. The other visuals have not changed yet.

What does this filter do?

The "After" filter type tells Amazon QuickSight to hide all rows where the Date field is on or before January 1, 2014. Only data after that date appears in the visual.

This is useful for trimming early data that might be incomplete or irrelevant to your analysis.

Don't see the filter take effect?

Make sure you clicked Apply after setting the date. The filter does not update the visual until you apply it.

Also confirm you selected a visual before opening the Filters pane. If no visual is selected, the filter may not attach correctly.

Help me troubleshoot my QuickSight date filter that isn't working.

Expand the filter scope to all visuals

By default, a new filter only applies to the single visual you had selected. Your dashboard has three visuals that all use the same dataset, so they should all respect the same date range.

• In the Filters pane, make sure your Date filter is expanded (click it if it is collapsed).
• Find the scope setting that currently says Single visual.
• Change it to All visuals of this dataset.

All three visuals now update to reflect the same date range. Your line chart, bar chart, and KPI visual all show data from after January 1, 2014.

Why apply the filter to all visuals?

Consistent date ranges across visuals prevent confusion. If your line chart shows 2014 onward but your KPI shows all-time totals, the numbers will not match up and viewers may draw incorrect conclusions.

Only one visual updated?

Double-check that you selected All visuals of this dataset and not Some visuals. The "Some visuals" option requires you to manually select which visuals to include.

My QuickSight filter only applies to one visual instead of all three. How do I fix the scope?

Add an on-sheet filter control

Right now, changing the date range requires opening the Filters pane. A filter control places a date picker widget directly on the sheet so viewers can adjust the range without digging into settings.

• In the Filters pane, find your Date filter.
• Click the three-dot menu icon next to the Date filter.
• Choose Add to sheet.

A date picker control appears on your analysis sheet. This is the interactive widget that dashboard viewers will use to change the date range.

• Drag the date picker control to the top of your sheet, above all three visuals.
• Try clicking the control and selecting a different date to confirm the filter updates all visuals.

When you change the date in the control, all three visuals immediately update to reflect the new range.

Why add a filter control to the sheet?

When you publish this analysis as a dashboard, viewers cannot open the Filters pane. The on-sheet control is the only way for them to interact with the date filter.

Placing it at the top of the sheet makes it the first thing viewers see. This signals that the dashboard is interactive and invites exploration.

Don't see the filter control on your sheet?

The control may appear behind or below your existing visuals. Scroll down to see if it was placed at the bottom of the sheet, then drag it to the top.

If you do not see Add to sheet in the three-dot menu, make sure you are clicking the menu on the filter itself in the Filters pane, not on a visual.

Help me find and position my filter control in QuickSight.

Your analysis is now fully interactive. Next up, you will publish it as a dashboard so stakeholders can explore the data on their own.

Publish Your Dashboard

Your analysis is packed with insights, but right now only you can see it. To share your work with stakeholders, you need to publish it as a dashboard.

A dashboard is a read-only version of your analysis that preserves all your visuals, filters, and formatting. In this step, you will publish your analysis and confirm it is accessible to viewers.

In this step, get ready to:

• Publish your analysis as a new dashboard named "Marketing Dashboard".
• View the published dashboard from the Dashboards section.

Publish the analysis as a new dashboard

Publishing converts your analysis into a shareable, read-only view. Your data stays live, so the dashboard always reflects the latest information in your dataset.

• In your analysis, click Publish in the top menu bar.
• Choose Publish dashboard.
• Select Publish as new dashboard.
• Enter Marketing Dashboard as the dashboard name.
• Under Select sheets, keep All sheets selected.
• Click Publish.

What is a dashboard vs an analysis?

An analysis is your workspace where you build, edit, and experiment with visuals. A dashboard is a read-only snapshot of that analysis designed for viewers.

Dashboards preserve your filters, controls, and layout. Viewers can interact with filter controls but cannot edit the visuals themselves.

View the published dashboard

After publishing, QuickSight opens a sharing page. You can skip sharing for now and go straight to viewing your dashboard.

• On the Share dashboard page that appears, click the X to close it.
• Click Dashboards in the left navigation menu.
• Find Marketing Dashboard in the list and click it to open the dashboard.

You should see all three of your visuals displayed with the date filter control at the top. This is exactly what a stakeholder would see when they open your dashboard.

Test the filter control

Try changing the date range using the filter control at the top of your dashboard. All three visuals should update together to reflect the new date range you select.

Don't see your dashboard listed?

Make sure you clicked Dashboards in the left navigation, not Analyses. Dashboards and analyses are listed in separate sections.

If you accidentally closed the publish dialog before clicking Publish, go back to your analysis and try the publish flow again from the top menu.

Why can't I find my published dashboard?

Secret mission

Add ML-Powered Forecasting

Your dashboard shows what happened in the past. But what about the future? Use QuickSight's built-in machine learning to predict future mailing list growth and explore what-if scenarios.

Clean Up Your Resources

Clean Up Your Resources

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

This project uses the Amazon QuickSight 30-day free trial. After the trial ends, you will be billed per user per month (starting at $3/month for Reader access).

Cost warning

Your QuickSight free trial lasts 30 days from signup. If you do not cancel before it ends, your account will convert to a paid subscription. If you are done experimenting, choose the Delete tab below to cancel your QuickSight account and avoid charges.

Resources you used:

• Amazon QuickSight account (30-day free trial, then billed per user per month).
• Marketing Sample dataset (stored in SPICE, included in free trial capacity).
• Marketing Dashboard (no additional cost beyond the QuickSight subscription).

Keep everything running

No action needed. Choose this if you are still actively exploring QuickSight within your 30-day free trial.

• Your dataset, analysis, and dashboard remain available in the QuickSight console.
• Remember to cancel before the trial ends if you do not plan to continue using QuickSight.

Pause - I'll come back to this later

Delete the dashboard and dataset to free up SPICE capacity, but keep your QuickSight account active for future use within the trial period.

• In the QuickSight console, click Dashboards in the left navigation.
• Select Marketing Dashboard and delete it.
• Click Datasets in the left navigation.
• Select the Marketing Sample dataset and delete it.
• Your QuickSight account remains active. Remember to cancel before the 30-day trial ends if you do not want to be charged.

Delete - I don't want to use this again

Remove all project resources and cancel your QuickSight account entirely to avoid any future charges.

• In the QuickSight console, click the person icon in the top right corner.
• Select Manage QuickSight.
• Go to Account settings.
• Click Delete account and confirm the deletion.
• This removes your QuickSight subscription, all datasets, analyses, and dashboards permanently.

That's a Wrap!

That's a Wrap!

Nice work. You just built a full marketing analytics dashboard from scratch in Amazon QuickSight.

You've learned how to:

• Uploaded and prepared a marketing dataset with field exclusions, renaming, and a calculated field in Amazon QuickSight.
• Built a multi-visual analysis with a line chart, bar chart, and KPI visual to explore marketing trends over time.
• Published an interactive dashboard with date filters and on-sheet controls that stakeholders can use to explore data themselves.
• Added ML-powered forecasting with what-if scenario analysis to predict future mailing list growth.

Ready to quiz yourself?