How to Make a Time Series Plot in Tableau with AI

A time series plot is one of the most fundamental yet powerful tools in data analysis, showing you how a specific metric changes over a period of time. Creating one in Tableau can help you spot trends, understand seasonal patterns, and communicate performance at a glance. This guide will walk you through building a time series plot in Tableau, step by step, and then show you how to layer in AI-powered features like forecasting to make your analysis even more insightful.

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What Exactly is a Time Series Plot?

In simple terms, a time series plot (or time series graph) is just a line chart that has a time-based value on the horizontal axis (the x-axis) and a measured value on the vertical axis (the y-axis).

This sounds technical, but you see them everywhere. Think about:

• Tracking your company's monthly revenue over the last three years.
• Visualizing daily website traffic to see the impact of a new marketing campaign.
• Monitoring weekly new user sign-ups to understand growth.

The goal is to move beyond static numbers and see the story of your data unfold over time. Is your revenue cyclical, peaking during the holidays? Did that one blog post cause a noticeable spike in traffic last Tuesday? A time series plot makes these patterns immediately obvious.

The Classic Way: Building a Time Series Plot in Tableau, Step-by-Step

Let's get straight to building one. For this example, we’ll use a common scenario: visualizing monthly sales. All you need is Tableau and a simple dataset with at least one date column and one numeric column (like sales, users, or sessions).

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Step 1: Connect to Your Data Source

First, open Tableau and connect to your data. Whether it's in an Excel file, a Google Sheet, or a database, the process is similar. In the "Connect" pane on the left, choose the appropriate connector and select your file or server.

For this walkthrough, we’ll assume you’re using a simple spreadsheet with two columns: Order Date and Sales.

Once connected, Tableau will take you to the Data Source screen. If everything looks good, click on a worksheet tab (e.g., "Sheet 1") at the bottom of the window to go to the main workspace.

Step 2: Understand Continuous vs. Discrete Dates (Green vs. Blue Pills)

This is the single most important concept for time series plots in Tableau, and it's a common stumbling block for beginners.

In the "Data" pane on the left, you'll see your fields. Date fields have a small calendar icon. When you drag a date field into your view, Tableau can treat it in two ways:

• Discrete (Blue): This treats date parts as distinct categories. For YEAR(Order Date), it would show 2021, 2022, and 2023 as separate, individual labels, much like you'd categorize products. Discrete pills are blue.
• Continuous (Green): This treats the date as a continuous axis from a start point to an end point. This is what you want for a time series line chart. Continuous pills are green.

The easiest way to remember is: Green for go, blue is for buckets. To see trends over time, you want your chart to "go" along an axis, so you need a green pill.

Step 3: Build the Basic View

Now for the fun part. This is just a simple drag-and-drop process.

1. Drag your date field (e.g., Order Date) from the Data pane and drop it onto the Columns shelf at the top of the workspace. By default, Tableau will likely make it a blue, discrete YEAR.
2. We need a continuous axis. Right-click the YEAR(Order Date) pill in the Columns shelf. In the bottom section of the context menu, you’ll see options for a continuous axis. Choose the granularity you want — let’s pick Month (the second one from the top, which will appear as "Month / Year"). The pill will turn green.
3. Next, drag your numeric measure (e.g., Sales) and drop it onto the Rows shelf.

Instantly, Tableau generates a line chart. You’ve just created a time series plot! You can see your sales data plotted month-over-month along a continuous timeline.

Step 4: Refine and Format Your Chart

The default chart is functional, but you can make it clearer and more professional with a few tweaks.

• Adjust the Mark Type: In the "Marks" card to the left of your worksheet view, you can change the chart type. Ensure it’s set to "Line." You could also select "Area" for a filled-in-area chart, which can be visually striking.
• Add Color and Context: Got a "Category" field? Drag it onto the "Color" button in the Marks card. Tableau will now create a separate line for each category, allowing you to compare their performance over time.
• Enhance Tooltips: Hover over any point on the line. Tableau shows a tooltip with the date and sales amount. You can customize this by clicking on the "Tooltip" button in the Marks card to add more information or rephrase the text for clarity.

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Level Up: Bringing AI into Your Time Series Analysis

Building the plot is the first step. The real magic happens when you use technology to pull deeper insights from it. Tableau has several built-in features that lean on AI and statistical modeling to take your analysis further, without you needing to be a data scientist.

1. Adding a Forecast in Two Clicks

Once you have your time series plot, what if you could project future performance based on past trends? Tableau’s forecasting feature does exactly that.

1. Go to the Analytics pane (it’s a tab next to the "Data" pane on the left side of the workspace).
2. Under "Model," you'll see the Forecast option. Simply click and drag it onto your chart.
3. Drop it in the "Add a Forecast" box that appears. That's it.

Tableau will automatically extend your timeline into the future. It will show a continuation of your line chart, representing the predicted values, and a shaded area around it. This shaded area is the prediction interval — the range within which Tableau is confident the actual values will fall. You can right-click the forecast to configure it, adjusting its length or changing the statistical model it uses.

2. Asking Questions with "Ask Data"

Sometimes, you just want a quick answer without having to drag and drop anything. Tableau’s "Ask Data" feature allows you to type a question in plain English and get a visualization in return.

You can directly type something like: "Monthly sales for the last two years as a line chart."

Tableau's natural language processing (NLP) model interprets your request, identifies the relevant fields ("Sales," "Order Date"), and generates the time series plot for you. It’s a great way to quickly explore data and is an excellent example of how AI can lower the barrier to getting answers.

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3. Explaining Patterns with "Explain Data"

Have you ever looked at a strange spike or dip in your time series chart and wondered, "What caused that?"

With "Explain Data," you can find out. Right-click on a specific data point (a "mark") in your chart and select the lightbulb icon that says "Explain Data." Tableau will run statistical models in the background to automatically identify potential drivers behind that value. For a sales spike, it might find that a high number of orders for a particular product category from a specific region was the primary explanation.

Common Time Series Plot Pitfalls & Pro Tips

As you build more of these charts, you might run into a few common issues. Here’s how to handle them.

• Handling Gaps in Your Data: If you have months with no sales, your line chart might have breaks. To fix this, right-click your green date pill on the Columns shelf and select "Show Missing Values." Tableau will fill in the timeline, making the gap more obvious.
• Choosing the Right Granularity: Looking at daily data can sometimes be too noisy, while yearly data might hide important seasonal trends. Don't be afraid to change your date granularity. Just right-click the green date pill and switch between Day, Week, Month, and Quarter to find the view that tells the clearest story.
• Don’t Confuse a Moving Average for a Trend: You can add a moving average from the Analytics pane to smooth out a noisy line chart. This is great for seeing the general direction of your data, but remember it’s a calculated smoothing, not the raw trend itself.

Final Thoughts

Learning to build a time series plot in Tableau is a foundational skill for anyone working with data. It moves you from looking at static reports to dynamically exploring trends, and by using features like forecasting and Explain Data, you can start uncovering insights that would be difficult to spot on your own.

While Tableau’s built-in AI tools are powerful, they still operate within a complex interface that takes time to master. At Graphed, we’ve built our entire platform around conversation. Instead of dragging and dropping pills or finding menus, you can connect your data sources — like Google Analytics, Shopify, and Salesforce — and simply ask in plain English: “Show me my revenue versus ad spend for the last six months." We instantly create a real-time, shareable dashboard for you. It allows you to skip the steep learning curve and get straight to the insights you need to grow your business. You can try Graphed for free.