Bites of the Backend

Welcome to Our New Series: Alteryx Developer Tools

You’ve cleaned, joined, parsed, and prepped your way through Alteryx’s Core tools. You’ve earned your snack breaks with the classics like Filter, Join, and Summarize. But now? It’s time to peek behind the curtain.

Welcome to the Alteryx Developer Tools series—your new backstage pass to the less-traveled paths of the platform. These tools aren’t about UI polish or drag-and-drop ease; they’re built for users who want to tinker, extend, and manipulate data at a deeper level.

To kick things off, we’re diving into one of the most mysterious and misunderstood data types in Alteryx: the Blob. And what better place to start than with the Blob Input, Blob Convert, and Blob Output tools?

First, What’s a Blob?

The term “Blob” stands for Binary Large Object. It’s a flexible, all-purpose container for non-text data—think images, PDFs, zipped files, Word docs, or anything else that doesn't fit nicely into a string or numeric field.

Blob data is stored and passed through workflows in its native binary format. This makes it incredibly powerful but also… invisible. You can’t just peek inside a Blob field in the Browse tool and expect to see readable content.

Why Work With Blobs in Alteryx?

So why bother with Blobs at all? Here are a few compelling use cases:

• Reading or archiving attachments, like PDFs or images.

• Embedding documents into reports or databases.

• Extracting metadata from media files.

• Manipulating binary formats like ZIP, Excel binaries, or raw sensor logs.

• Building more advanced or interactive macros.

Step 1: Blob Input – Bringing Binary In

📦 What it Does:

The Blob Input tool reads external binary files and brings them into your workflow as Blob fields.

🧰 Configuration:

• Directory Path: Points to the folder with your Blob files.

• File Name or Pattern: Filters which files to bring in (e.g., *.jpg, *.pdf).

• File Name Field: Stores the name alongside the Blob, so you don’t lose track.

• Include Subdirectories: Handy if your files are deeply nested.

💡 Common Use Cases:

• Bringing in scanned documents for automated handling.

• Loading images for further classification or metadata tagging.

• Reading zipped content (for unpacking later using scripts or macros).

⚠️ Tips:

• Be careful with large binary files—they can inflate memory usage quickly.

• Use with File Browse interfaces if building apps that allow uploads.

🔄 Step 2: Blob Convert – Binary Shape-Shifter

📦 What it Does:

The Blob Convert tool transforms Blob fields to and from strings, numbers, or file paths. It’s the gateway to working with Blobs, not just storing or passing them.

🧰 Configuration:

💡 Common Use Cases:

• Convert a CSV stored in a database Blob field into a usable table.

• Decode text logs zipped into a Blob.

• Create PDFs dynamically, then encode them back into Blob for emailing or storage.

⚠️ Considerations:

• Encoding and character set matter! Use UTF-8 for text when possible.

• Be mindful of delimiters when converting to/from multi-line strings.

💾 Step 3: Blob Output – Writing It All Back

📦 What it Does:

Blob Output lets you save a Blob field back out into a binary file—be it a restored image, report, zipped archive, or otherwise.

🧰 Configuration:

• Output Directory: Where the file gets written.

• File Name Field: Dynamically determines the output file name.

• Overwrite Options: Choose whether to overwrite or append.

• Create Directory If It Doesn’t Exist: Helpful in automation.

💡 Common Use Cases:

• Save processed PDFs or attachments back to disk

• Export Excel or image files created during the workflow

• Dynamically generate and save files based on record data

⚠️ Considerations

• File Overwrites: Be careful when using dynamic filenames—if two records generate the same name, one may overwrite the other unless handled with care.

• File Path Construction: Ensure your output path is valid and doesn’t contain illegal characters or missing folders (use Create Directory If It Doesn’t Exist when needed).

• Large File Writes: Writing many large Blobs in one go can be resource-intensive. Batch your writes or break them into chunks for stability.

• Network Drives: Writing to shared or network drives may slow performance or introduce access errors—test your output locations in production settings.

• Silent Failures: If a file fails to write (e.g., due to permissions), the tool may not always throw an error—add logging or checks downstream if this matters.

🧠 A Full Blob Use Case: Document Pipeline

Let’s look at a common example: processing scanned invoices stored as PDFs in a shared drive.

1. Blob Input loads all scanned files.

2. Blob Convert turns them into text (if using OCR tools).

3. Text Parsing & RegEx extract invoice metadata (dates, totals, vendor names).

4. Reporting Tools repackage the data into PDFs or Excel.

5. Blob Convert (again) to turn the outputs back into binary.

6. Blob Output writes them to organized folders (e.g., by vendor or date).

🪟 How Does This Compare to Excel?

In Excel, binary files are usually handled outside the spreadsheet entirely. While you can embed documents or images, there’s no native support for:

• Parsing or dynamically transforming binary content.

• Batch processing of file content.

• Storing files in memory as variables or fields.

With Alteryx Blob tools, you can automate document-heavy workflows, even at scale—something Excel simply can’t do without extensive VBA or third-party scripts.

📌 Best Practices When Using Blob Tools

✅ Do:

• Add file identifiers alongside the Blob fields to maintain traceability.

• Use small batches to test performance.

• Monitor memory usage with large files.

• Combine with scripting tools (Python/R) for advanced manipulation.

❌ Don’t:

• Expect to browse Blob content visually—use convert or export first.

• Mix Blob fields into tools that expect strings or numbers.

• Forget cleanup—temp folders can fill quickly in shared environments.

📈 Advanced Blob Tricks

Looking to push the envelope?

• Use Python Tool to decode image content (e.g., extract EXIF data from photos).

• Combine with RegEx to parse HTML stored as Blob.

• Store entire documents inside macros for portable data apps.

• Use Blob Convert and Base64 encoding to email attachments in a Report.

🧠 What’s Coming Next in the Developer Tools Series?

We’ll soon dive into:

• The Download Tool and working with APIs.

• Using Run Command for shell access.

• Exploring Macro Input/Output Anchors.

• Using Dynamic Replace with templates and expressions.

Developer tools might seem intimidating at first—but just like espresso beans, they’re concentrated power. Once you get used to the flavor, you won’t want to go back.

🍫 One Last Bite: Chocolate-Covered Espresso Beans

They’re compact, intense, and not for the faint of heart—just like Blob data. But they give you a boost that carries you through complex workflows with a new edge. Perfect for long builds and deep dives into developer land.

Happy snacking and analyzing!