How to Export Data to Excel

Moving your data out of its original application and into a fresh Excel sheet is one of the most common tasks in business. This guide lays out the step-by-step methods for exporting data from popular sources, tips for keeping your data clean, and how to troubleshoot common issues along the way.

Why Export Data to Excel Anyway?

With so many sophisticated business intelligence and reporting tools available, why do so many people still rely on exporting data to Excel? The reality is that Excel remains an incredibly powerful and flexible tool for a few key reasons.

• Total Control and Flexibility: Once the data is in Excel, it's yours to command. You can build custom formulas, create financial models, run what-if scenarios, and organize information in a way that makes sense for your specific needs, free from the constraints of another platform’s reporting features.
• Familiarity and Accessibility: Nearly everyone with a business-focused role has some experience with Excel. There's no steep learning curve for basic tasks, making it a go-to tool for quick analysis or one-off reports without needing specialized training.
• Offline Analysis: You don’t need an internet connection to work with your data in Excel. Once you've exported your file, you can analyze your information from anywhere - on a plane, during a commute, or in a meeting room with spotty Wi-Fi.
• Easy Sharing: Sending an Excel file is simple and universally understood. You can share your findings with colleagues, clients, or stakeholders, confident that they can open and interact with the data you’ve prepared.

Understanding Common Data Export Formats

When you click "Export," you'll often be asked to choose a file format. While there are many types, a few appear far more often than others. Understanding them will help you pick the right one for the job.

CSV (.csv - Comma-Separated Values)

The CSV is the universal donor of the data world. It's a plain text file where data is organized in rows, with each value in a row separated (or "delimited") by a comma. Almost every application that handles data can export to and import from a CSV file.

• When to use it: Use a CSV for maximum compatibility when moving data between different applications that might not speak the same language. It's also ideal for large datasets because the file sizes are small.
• The downside: CSVs don’t save any formatting. Charts, formulas, font colors, and cell widths are all lost. It’s pure, raw data.

Excel Workbook (.xlsx / .xls)

This is Excel's native format. An XLSX file keeps all Excel-specific features intact, including formulas, charts, PivotTables, formatting, and macros. The older .xls format is still around but has limitations on rows and columns compared to the modern .xlsx format.

• When to use it: Choose this option when the source application offers it and you want a ready-made report with formatting preserved.
• The downside: It's a less universal format. While many programs can open Excel files, it's not as universally compatible as a simple CSV.

TSV (.tsv - Tab-Separated Values)

A TSV is almost identical to a CSV file. The only difference is that it uses a tab character instead of a comma to separate values. This can be useful when your data itself contains commas (like in a description field), which can confuse a CSV importer.

• When to use it: If you're exporting data with a lot of free-form text entry that might include commas, a TSV can prevent the data from being split into incorrect columns when you open it.
• The downside: Less common than CSV, so you may not see it as an option as often.

How to Export Data into Excel from Common Sources

Now, let's get into the practical, step-by-step instructions for getting data out of various platforms and into your spreadsheet.

Method 1: Exporting From SaaS Platforms (Shopify, Salesforce, HubSpot)

Most modern web-based applications have made exporting data a straightforward process. While the exact button labels may vary, the general workflow is remarkably consistent.

General Steps:

1. Navigate to the appropriate section of the application. This is typically labeled "Reports," "Analytics," "Data," or the name of the specific data you need (e.g., "Orders," "Contacts").
2. Create a new report or filter an existing view to show only the data you need. This is a crucial step - avoid exporting your entire database when you only need information from the last 30 days.
3. Look for an "Export," "Download," or icon of a downward-pointing arrow. This button is often located in the top-right corner of the report or data table.
4. Select your desired file format. CSV is almost always available and is a safe choice. If XLSX is an option, it may save you a little formatting work later on.
5. Click the final export button. The file will either download immediately or the system will email you a link to download it once it's ready, which is common for very large datasets.

Example with Shopify: To export your orders, you'd go to your Shopify Admin > "Orders" > Click "Export" in the top right > Choose which orders to export (e.g., this month's orders) and select "CSV format" > Click "Export orders." You'll receive an email with the download link.

Method 2: Exporting From a Webpage Table

Sometimes the data you need is sitting in a plain HTML table on a website, like a list of public company financials or sports statistics. Here are a couple of ways to grab it.

The Quick and Dirty: Copy & Paste

For simple tables, this is the fastest method. Just select the data on the webpage with your mouse, copy it (Ctrl + C), go to Excel, select a single cell, and paste (Ctrl + V). Excel is usually pretty good at interpreting the table structure, but this can sometimes result in messy formatting you have to clean up manually.

The Pro Method: Using Excel's "Get Data from Web" Feature

This is an incredibly powerful, built-in feature of Excel that's perfect for cleanly importing structured data from a website.

1. Open a new Excel workbook.
2. Go to the Data tab on the Ribbon.
3. In the "Get & Transform Data" group, click on From Web.
4. A dialog box will appear. Paste the full URL of the webpage containing the table you want to import and click OK.
5. Excel will analyze the page and display a Navigator window. On the left, it will show a list of all the tables it found on the page.
6. Click on each table name to see a preview on the right. Once you find the correct one, select it.
7. Click the Load button at the bottom. Excel will neatly import the data from the webpage directly into a formatted table in your new worksheet. The best part? You can easily refresh this data later if the website updates!

Method 3: Exporting From a Database

If you're a bit more technical and need to pull data directly from a business database like SQL Server, MySQL, or PostgreSQL, Excel can connect directly, saving you from having to ask a developer for a CSV file.

1. In Excel, go to the Data tab.
2. Click Get Data > From Database. Select the type of database you're connecting to (e.g., "From SQL Server Database").
3. Enter the server details and credential information. You might need to get this information from your IT department or technical team lead.
4. Once connected, you'll see the Navigator window again, similar to the "From Web" prompt. You can select entire tables or write a custom SQL query to pull exactly the data you need (e.g., SELECT * FROM Customers WHERE Country = 'Canada').
5. After previewing the data, click Load to import it into your worksheet. This creates a direct connection that you can refresh at any time to get the latest data.

Tips for a Clean and Successful Export and Import Process

Getting the data out is only half the battle. Here are a few best practices to ensure the file you work with is clean, accurate, and easy to use.

1. Filter Before You Export

Don't export more data than you need. A massive file with hundreds of thousands of rows will make Excel slow and sluggish. Use the filters in your source application to narrow down the dataset to the specific time period, category, or customer segment you're actually analyzing. This results in smaller file sizes and a much more focused analysis.

2. Understand the "Text to Columns" Tool

Sometimes when you open a CSV file, all the data gets crammed into Column A instead of neatly separating. This happens when Excel fails to recognize the delimiter (the character separating the data points).

• To fix this, select all the data in Column A.
• Go to the Data tab and click Text to Columns.
• In the wizard that pops up, choose "Delimited" and click "Next."
• Check the box for the correct delimiter - it's usually a Comma, but it might be a Tab or Semicolon. You'll see a preview of your data correctly splitting into columns.
• Click "Finish," and your data will be properly organized.

3. Fix Numbers That Excel Thinks Are Text

A classic Excel frustration. You export financial data, but you can't sum the revenue column because Excel sees the numbers as text. You can often spot this by a small green triangle in the corner of the cell.

To fix this, select the entire column, click the little error icon that appears, and choose "Convert to Number." If that doesn’t work, you can use a helper column with the formula =VALUE(A2) to force the conversion, then copy and paste the values back over the original column.

4. Always "Save As..." an Excel Workbook

After you open a fresh CSV file and begin working - adding formulas, formatting, or charts - your very first step should be to save it as an Excel Workbook (.xlsx). If you simply click "Save," Excel will try to save it as a CSV again, which will strip out all of your hard work. Go to File > Save As and choose "Excel Workbook (.xlsx)" from the dropdown menu.

Final Thoughts

Mastering the art of exporting data into Excel opens up a world of custom analysis and reporting that pre-built dashboards can't always provide. Understanding the common file types and knowing how to use Excel's powerful import tools will save you an incredible amount of time and help you get clean, reliable data to work with every time.

That manual process of downloading CSVs and wrangling them in spreadsheets, week after week, is exactly the kind of repetitive work we aimed to eliminate. We built Graphed to connect directly to all your data sources - like Shopify, Google Analytics, Salesforce, or Facebook Ads - in one click. Instead of exporting and importing, you can simply ask questions in plain English like, "show me my Shopify sales by marketing campaign for last month," and get a live, interactive dashboard instantly, freeing you up to act on insights instead of just gathering data.