Inside Goliath: an overview of the data hub

This guide explains how the Data Hub works inside Goliath and how to use it to manage your data workflows. You’ll learn how to upload and process files, download exports, manage skip trace requests, and request custom scrapers. The goal is to keep all of your data organized, accessible, and ready to use across the platform.

What's inside the video

1. Accessing the Data Hub

• Navigate to the Data Hub section in Goliath

• Understand that this is where all uploaded or exported files are stored

2. Uploading Files

• Go to the Uploads tab

• Select the file you wish to upload (contacts, properties, signals, etc.)

• Drop the file into the designated area to start processing

3. Exporting Files

• Navigate to the Export section of the Data Hub

• Here you can find all previously exported files

• You can relabel files and view associated contacts based on filters

4. Downloading Processed Files

• On the right side of the Export section, locate the option to download processed files

• Click to download whenever convenient 

5. Managing SkipTrace Requests

• Find the SkipTrace request section for individual addresses

• Review any ongoing requests or kick off new ones

6. Accessing Custom Scrapers

• Locate the Custom Scrapers section for your account

• If on the scale plan, view your custom data pipelines

7. Requesting a Custom Scraper

• If not on the scale plan, you can request a new scraper

• Provide the following details:

  • Title of the scraper

  • URL to scrape

  • Specific locations

  • Detailed instructions (preferably a Loom video)

• Submit the scraper request for processing

Best practices, tips and tricks

A few best practices

• Use clear, descriptive names when uploading or exporting files

• Double-check file formats before uploading to avoid processing issues

• Review processed files before using them in downstream workflows

When to use the Data Hub

• Use the Data Hub for all file uploads and exports tied to contacts, properties, or signals

• Use it to manage skip tracing and custom data ingestion

• Treat it as the source of truth for imported and exported datasets

Data organization and ownership

• Keep uploads and exports clearly labeled so teams can find them easily

• Avoid duplicate uploads by checking existing files first

• Document the purpose of each custom scraper request for clarity

Recommended daily or weekly workflow

• Check the Export section regularly to retrieve processed files

• Monitor skip trace requests to ensure completion

• Review custom scraper outputs for accuracy and relevance

• Clean up or archive outdated files to keep the Data Hub organized