How to Import Data into Tableau

Bringing your data into Tableau is the first essential step to creating powerful visualizations and uncovering insights. This article will guide you through the various ways to connect your data, from simple spreadsheets on your computer to complex databases residing on a server.

Understanding Tableau's Data Connection Types

Tableau is designed to connect to an incredibly wide range of data sources. Before jumping into the steps, it's helpful to understand the two primary ways Tableau can interact with your data: a Live Connection or an Extract.

• Live Connection: This method queries your source data directly. Every time you filter your dashboard or interact with a chart, Tableau sends a query to the original database. This is great for data that changes constantly and needs to be monitored in real-time. The downside is that dashboard performance depends entirely on the speed and efficiency of the source database.
• Extract (.hyper file): This method takes a snapshot of your data and pulls it into Tableau's own high-performance data engine. This makes your dashboards incredibly fast because Tableau isn't waiting on an external database to respond. You can schedule these extracts to refresh automatically (e.g., every hour or once a day) to keep your data up-to-date. This is the most common and recommended approach for complex dashboards or when the source database is slow.

You can choose your connection type on the Data Source page after you've connected to your data. For now, let's focus on getting it connected in the first place.

Connecting to File-Based Data Sources

For many analysts, the journey begins with a simple file. These are often the easiest data sources to connect to and are perfect for learning the fundamentals of Tableau without needing server credentials or database knowledge.

Connecting to an Excel or CSV File

Spreadsheets are the bread and butter of business data analysis. Connecting to an Excel workbook or a plain text CSV file is straightforward.

1. Select the Connector: Open Tableau Desktop. On the start page, you’ll see a "Connect" pane on the left side. Under the "To a File" section, click on "Microsoft Excel" for .xls or .xlsx files or "Text file" for .csv or .txt files.
2. Locate Your File: A file browser window will pop up. Navigate to the folder where your file is saved, select it, and click "Open."
3. Go to the Data Source Page: Tableau will automatically take you to the Data Source page. On the left, you'll see a list of all the sheets (for Excel) or files (if you connected to a folder of text files) available.
4. Drag Your Data to the Canvas: Drag the sheet or table you want to analyze from the left pane and drop it onto the area that says "Drag tables here."
5. Review Your Data: A preview of your data will appear in a grid at the bottom of the screen. This is your chance to make sure everything looks right. Tableau is usually very good at automatically detecting data types (like numbers, dates, and text), but it’s always a good idea to double-check the little icons above each column header.

Connecting to a PDF File

Have you ever needed to grab a table from a PDF report? Tableau can save you from the tedious process of copying and pasting by connecting to PDFs directly.

1. Select the PDF Connector: In the "Connect" pane under "To a File," select "PDF File."
2. Open the PDF: Find the PDF document you want to analyze and open it.
3. Choose Your Tables: Tableau will scan the entire document for tables. A dialog box will appear showing you the tables it found, listed by page number. You can select a single table or multiple tables to import.
4. Add to the Canvas: Drag your selected table(s) to the canvas to start working with the data just as you would with any other source.

Connecting to Server-Based Data Sources

If your data lives in a formal database, you'll connect through the "To a Server" section. The process is similar for most relational databases like MySQL, PostgreSQL, Microsoft SQL Server, or Oracle.

Connecting to a SQL Database (MySQL Example)

Here’s how you would connect to a MySQL database. The required fields will be slightly different for other databases, but the core steps remain the same.

1. Select Your Server Type: From the "Connect" pane, click the "More..." link under "To a Server" to see the full list of connectors. Find and click on "MySQL."
2. Enter Connection Details: A dialog box will appear asking for server credentials. You will need this information from your database administrator:
3. Sign In: Once all the details are filled in, click "Sign In."
4. Select Your Tables: On the Data Source page, you'll see a dropdown menu to select the database (if you didn't specify one earlier). The tables within that database will be listed in the left pane. You can now drag the tables to the canvas to begin joining them together.

Connecting to Cloud Data Sources

With so much data now stored in cloud applications, Tableau has built-in connectors for dozens of popular platforms like Google Analytics, Salesforce, and Google Sheets.

Connecting to Google Sheets

Google Sheets is a popular choice for collaborative datasets and is incredibly easy to import into Tableau.

1. Select the Google Sheets Connector: In the "Connect" pane under "To a Server," click on "Google Sheets."
2. Authenticate Your Account: A web browser window will open prompting you to sign in to your Google account. Enter your credentials and grant Tableau permission to access your Google Drive files.
3. Choose Your Sheet: After authenticating, Tableau will display a list of all the Google Sheets in your drive. Select the one you want to work with and click "Connect."
4. Prepare Your Data: You'll land on the Data Source page, where you'll see all of the individual worksheets within your Google Sheet listed on the left. Drag the specific worksheet you need to the canvas to get started.

Prepping Your Data on the Data Source Page

Connecting your data is just the beginning. The Data Source page is where you can clean, shape, and combine your data before you start building charts. This foundational work is critical for accurate analysis.

Creating Relationships and Joins

When you drag more than one table to the canvas, Tableau prompts you to define a relationship between them. This commonly involves linking the tables using a common field, like an Order ID that exists in both your Orders table and your Returns table. Tableau's relationship model (the famous "noodle") is generally more flexible than traditional joins, but you can also open the classic join interface if you need more specific control over join types (inner, left, right, full outer).

Cleaning Up with the Data Interpreter

Sometimes, spreadsheet files aren't perfectly formatted for analysis. They might have extra header rows, footers, or sub-totals. Look for the "Use Data Interpreter" checkbox on the left pane. When checked, Tableau's algorithm scans the file for common formatting issues and cleans them up automatically, which can save you a ton of manual work.

Pivoting Data from Wide to Tall

Your data might be arranged in a "wide" format (e.g., separate columns for Jan, Feb, Mar sales). For analysis in Tableau, a "tall" format is often better (a 'Month' column and a 'Sales' column). To fix this:

• In the data grid, select the columns you want to pivot (e.g., hold Ctrl or Cmd and click on Jan, Feb, Mar).
• Click the small dropdown arrow that appears on one of the selected column headers.
• Choose "Pivot."

Your multiple columns will be transformed into two new columns: "Pivot Field Names" and "Pivot Field Values," which you can rename to 'Month' and 'Sales'.

Final Thoughts

Connecting data in Tableau is a flexible and powerful front end to the analysis process. Whether you’re working with a simple CSV or connecting to a live cloud database, the steps allow you to get set up quickly, while the tools on the Data Source page give you the power to properly prepare your data for visualization.

Manually setting up these connections and transformations for every data source is a fundamental skill, but it often becomes the biggest time sink in the analysis workflow. We designed Graphed to automate that entire first step. Rather than connecting sources individually and building dashboards from scratch, you can connect platforms like Google Analytics, Shopify, and Salesforce once, then simply describe what you want to see. This turns hours of setup and reporting busywork into a few seconds of asking plain-English questions.