How to Input Data in Tableau

Connecting your data is the first crucial step to creating insightful visualizations in Tableau. Before you can build stunning dashboards, you first need to bring your raw numbers into the platform. This guide will walk you through exactly how to input data in Tableau, from simple spreadsheets to cloud-based applications, so you can get to the fun part: finding and sharing powerful insights.

Understanding How Tableau Connects to Data

Tableau's power lies in its ability to connect to a vast array of data sources. It doesn't store your data inside its own system by default. Instead, it acts as a visualization layer on top of where your data already lives. Before we jump into the "how," it's helpful to understand the two main ways Tableau can interact with your data source: a Live Connection and an Extract.

Live Connection

A live connection queries your database or file directly. When you interact with a dashboard - like filtering by date or clicking on a specific category - Tableau sends a new query to the data source and fetches the updated results.

• Pros: Ideal for real-time or near-real-time data. You're always looking at the latest information without needing to manually refresh.
• Cons: Performance depends entirely on the speed of your underlying data source. Large, complex queries on a slow database can lead to slow dashboards.

Data Extract (.hyper file)

An extract is a highly compressed snapshot of your data that Tableau stores locally. It's an independent, optimized file that no longer relies on the original source for its performance.

• Pros: Can dramatically speed up your dashboards, as Tableau is querying its own optimized file instead of a potentially slow external database. It's also great for taking your data offline.
• Cons: The data is static until you schedule a refresh. It is not a "live" view of your data, it's only as current as the last time you updated the extract. You can schedule these refreshes to happen automatically.

A good rule of thumb is to start with an extract unless you have a clear need for live, up-to-the-second data. The performance boost is often worth it.

Getting Started: Tableau's "Connect to Data" Screen

When you first open Tableau Desktop, you're greeted with the start page. On the left side, you'll see a blue "Connect" pane. This is your mission control for inputting data. It's neatly organized into three categories:

• To a File: For connecting to flat files located on your computer, like Microsoft Excel sheets, CSVs, or text files.
• To a Server: For connecting to databases and cloud applications like on-premise MS SQL Server, Google Analytics, or Salesforce.
• Saved Data Sources: A library for any data connections you've pre-configured and saved for reuse.

Let's walk through how to use the most common options.

Connecting to Flat Files (Excel, CSV, and Google Sheets)

For most marketers, salespeople, and business owners, a lot of business data lives in spreadsheets. Connecting them to Tableau is straightforward and is often the first type of connection new users make.

Connecting to Microsoft Excel and CSV Files

Let’s say you have a weekly marketing report you downloaded as an Excel file. Here's how to bring it into Tableau:

1. Under the "Connect" pane, click on "Microsoft Excel". If it's a CSV, you'd click "Text File."
2. A new window will open, allowing you to browse your computer's files. Find and select your file, then click "Open."
3. You are now on the "Data Source" page. In the left-hand pane ("Sheets"), you'll see a list of all the sheets (for Excel) or files in the folder.
4. Drag the sheet you want to analyze (e.g., "Campaign Performance") into the main canvas area that says "Drag tables here."
5. Tableau will display a preview of your data in a grid at the bottom, showing your columns and rows.

One extremely useful Tableau feature for messy spreadsheets is the Data Interpreter. If your Excel file has merged cells, extra headers, or empty rows at the top, just check the "Use Data Interpreter" box. Tableau will intelligently scan the file and clean it up for analysis, often saving you a lot of manual prep work.

Connecting to Google Sheets

Connecting to a Google Sheet works very similarly but is technically a server connection since it's hosted in the cloud.

1. Under "To a Server," click on "More..." and select "Google Sheets" from the list.
2. A browser window will pop up asking for you to sign in to your Google account and grant Tableau permission to access your Google Drive files.
3. Once you authorize it, the pop-up will close, and a new dialog window in Tableau shows all the Google Sheets in your drive.
4. Select the sheet you want to analyze and click "Connect."
5. Just like with Excel, drag the specific tab you need onto the canvas to load your data.

Connecting to Servers and Cloud Applications

While spreadsheets are great, most business-critical data for sales and marketing lives in cloud databases or SaaS platforms like Salesforce, HubSpot, or Google Analytics. The connection process here is a bit different but just as manageable.

Connecting to a Database (e.g., PostgreSQL, SQL Server)

If your customer data or product sales data is stored in a database, connecting Tableau enables incredibly rich analysis. You'll likely need to get the credentials from your IT or development team.

1. In the "To a Server" section of the Connect pane, find and click on the name of your database (e.g., "PostgreSQL," "MySQL").
2. A connection dialog box appears. Here, you'll need to enter the server details. These typically include:
3. Click "Sign In."
4. Once connected, the left pane will now show a list of schemas and tables within that database. You can scroll through or search to find what you want, like an "Orders" table or a "Users" table.
5. Drag the desired table or tables to the canvas.

Connecting to Google Analytics

Pulling your website data directly from Google Analytics is a common need for any marketing team. Tableau has a native connector that simplifies this process.

1. Under "To a Server," find and click "Google Analytics."
2. Authenticate with your Google account, similar to the Google Sheets process.
3. You'll then be asked to specify the data you want to retrieve by choosing:
4. Click "Go to Worksheet" and you're ready to start building!

The Data Source Page: Your Prep Station

No matter what you connect to, you'll land on Tableau's Data Source page. This screen is more than just a preview, it's where you prepare your data before visualizing it. Here, you can:

• Join Related Data: If you drag in multiple tables from a database (e.g., Customer table and an Orders table), you can create a join by clicking on the noodle connecting them. This lets you define the relationship, telling Tableau to connect them where the CustomerID field is the same in both tables.
• Rename Fields: Double-click on any column name (like Acct_ID) to give it a friendlier name (Account ID).
• Change Data Types: Tableau is smart about guessing data types, but you can override it. Click on the icon next to a column's name (# for numbers, Abc for string, a calendar for dates) to change it if needed.
• Hide Unused Columns: Right-click on a column you don't need and select "Hide" to keep your workspace clean and improve performance.

Final Thoughts

Tableau's power to connect to everything from a local CSV file to a massive cloud data warehouse is what makes it such a flexible tool for business intelligence. Knowing the difference between a live connection and an extract, and becoming comfortable with the "Connect to Data" screen, is the foundational skill every user needs to get started on the path to creating dynamic and meaningful reports.

Learning the nuances of data connections, joins, and extracts in traditional BI tools like Tableau definitely takes time and practice. At Graphed , we felt this friction firsthand while trying to pull answers from a dozen different marketing and sales platforms. That's why we built a tool where connecting data sources like Google Analytics, Shopify, Salesforce, and Facebook Ads is as simple as a few clicks - no server names or data interpreters needed. Creating an entire dashboard is as easy as typing a question like, "Show me my ad spend vs. revenue by campaign," letting our AI turn your plain-English request into a live, interactive dashboard in seconds.