Data is at the center of every HubSpot Hub, yet most organizations still struggle to align information across tools and teams. Different apps store different definitions of the same metric, creating friction between reporting, automation, and strategy.
HubSpot Data Hub helps fix that by giving companies one place to connect, clean, and structure data across their systems. Within Data Hub, Data Studio lets users build Datasets, reusable data layers that define how information is organized and used in reports, workflows, and Segments.
This article explains how Datasets work, how they connect with third-party sources, and why they’re essential for creating consistent, connected data in HubSpot.
In HubSpot, a dataset is a reusable collection of structured data. It allows teams to combine data from multiple HubSpot objects or connected sources into a single, organized view that can be used across the platform.
Rather than duplicating or rebuilding data every time you create a report, segment, or workflow, a dataset acts as a defined data layer that references your CRM records and any connected external sources. It also lets you combine data that can’t be joined elsewhere in HubSpot, such as metrics from multiple objects or external systems, giving you a more complete view of performance across tools.
Datasets are designed to make working with data easier for non-technical users. They eliminate the need to manually export, merge, and clean spreadsheets, offering a centralized, AI-assisted interface for preparing and analyzing your data inside HubSpot.
How HubSpot Datasets Work
When you build a dataset in Data Studio, you combine key data elements from HubSpot and external sources into one unified structure that can be reused across your portal.
Each dataset includes these components:
These elements let you combine HubSpot data with external systems such as Snowflake, Shopify, or QuickBooks, giving you a complete, connected picture of your customers and operations.
Once published, a dataset becomes available throughout HubSpot for use with building reports, workflows, and Segments. For example, you can build a workflow that automatically alerts account managers when high-value customers log multiple support tickets or when a subscription value changes in your subscription management platform.
By standardizing data definitions and calculations, datasets help GTM teams align on the same metrics. Rather than relying on inconsistent spreadsheets or disconnected reports, every team works from the same trusted data source inside HubSpot.
Most organizations store data across multiple platforms, including CRMs and accounting tools, as well as data warehouses like Snowflake and spreadsheets in Google Sheets. Data Studio makes it simple to bring all of this information together.
When you create a Dataset, you can join data from different sources using shared identifiers. For instance, you might join contact records in HubSpot with customer usage data in Snowflake or Shopify purchase history.
To ensure clean and accurate joins:
Clean joins allow you to bring your most important data into HubSpot without duplication or data loss, ensuring you have a single, reliable view of each customer.
HubSpot’s Data Sync framework allows more than 100 third-party apps to connect directly with Data Studio. This helps teams blend data from marketing, sales, finance, and support tools into a single Dataset.
Common integration categories include:
Certain integrations, such as Shopify, QuickBooks Online, Stripe, Xero, and Snowflake, are marked as compatible with Data Studio in Data Hub. These enable near-real-time syncing, so your datasets always reflect up-to-date information across your business.
Data Studio includes built-in AI functionality to help you create and maintain datasets more easily. These AI tools can:
These tools remove much of the manual effort from data management and help ensure your datasets remain clean and usable across reports, workflows, and segments.
Creating a Dataset in HubSpot is a straightforward process designed to help teams blend and clean their data without needing technical expertise.
Here’s how to build a Dataset in HubSpot:
By turning complex data blending into a guided, low-code experience, HubSpot makes data operations more accessible.
Each of these use cases highlights how Datasets create consistency and context across multiple business processes, not just analytics.
Here are some best practices to keep your Datasets clean, efficient, and reliable:
By maintaining clear governance and structure, your Datasets remain dependable across every team that uses them.
When using HubSpot Data Studio, it’s essential to know that building and syncing external data connections may require HubSpot credits. Credits are part of HubSpot’s usage-based billing system and are consumed when you import, process, or sync data from third-party applications into your CRM.
You can monitor your organization’s credit usage in your HubSpot account settings under Billing & Usage. Keeping an eye on this helps you plan how often your data syncs and avoid unnecessary overages.
Understanding how credits work ensures that your team can use Data Studio efficiently without unexpected billing surprises. It’s especially valuable for companies connecting large data warehouses or high-frequency syncs from multiple apps.
A Dataset in HubSpot is a reusable data layer built in Data Studio, part of Data Hub. It combines information from HubSpot and external systems to create accurate, consistent data for use across the platform.
Datasets organize information through joins, filters, and calculated fields. They help standardize metrics and simplify how teams work with shared data.
Data Studio integrates with more than 100 third-party apps, including Snowflake, Shopify, QuickBooks Online, Stripe, and Xero, giving teams broader visibility into customer and revenue data.
Datasets break down data silos, reduce manual data management, and help teams work confidently with trusted information inside HubSpot.
Datasets give data-focused teams new ways to organize, combine, and analyze information from across systems. While not every HubSpot user will need them, Datasets are especially valuable for organizations that depend on precise reporting, multi-source data, or advanced automation.
New features like Data Agent and Breeze Assistant make it easier to manage and interact with that data directly inside HubSpot. Breeze Assistant helps users query and interpret their CRM data through natural language, while Data Agent improves data quality by automatically enriching and validating records. Together, these tools help teams get more value from the information they already have.
As HubSpot continues to expand its AI and data capabilities, Datasets will serve as an important bridge between HubSpot’s Smart CRM and the broader data landscape, allowing GTM teams to work smarter with cleaner, connected data.
Need help implementing HubSpot Datasets or connecting your data in Data Studio? Contact the Pros.
