Data Vault Calculator for Hubs, Links, and Satellites

How to Use Our Data Vault Calculator

Provide estimates based on your source system analysis to generate a high-level project scope. Accuracy improves with the quality of your inputs.

1. Source System & Volume Inputs

This section describes the data you are starting with.

• Number of Source Systems: Enter the total number of distinct source systems (e.g., CRM, ERP, Billing) you plan to integrate.

• Average Business Keys per Source: Estimate the average number of core business concepts (which will become Hubs) you expect to extract from each source system. Examples include Customer, Product, Order, etc.

• Average Relationships per Source: Estimate the average number of natural business relationships (which will become Links) in each source.

• Average Descriptive Tables per Source: Estimate the average number of tables that contain contextual or descriptive attributes (which will become Satellites).

• Average Source Rows (in Millions): Enter the average number of rows in a typical source table, in millions. For example, for 2,500,000 rows, enter “2.5”.

• Historical Load Factor: A multiplier for historical data. Enter “1” for a current-state load. For five years of history where the data volume was similar each year, you might enter “5”.

2. Data Structure Inputs

This section defines the average shape of your data.

• Average Attributes per Satellite: Enter the average number of descriptive columns you expect in each Satellite table.

• Average Data Type Size (Bytes): This is the average size in bytes for a single field. A mix of text, numbers, and dates often averages around 25-50 bytes. Adjust based on your data profile.

Understanding Your Results: From Estimates to a Project Plan

The calculator provides key metrics to help you scope your Data Vault project. These numbers represent the foundational Raw Vault, which is the auditable, untransformed repository of your integrated data.

Results Breakdown

These results provide a data-driven baseline for your project plan. You can use the Total Loading Patterns to estimate development timelines and the Estimated Storage to provision your data warehouse environment, whether on-premise or in the cloud.

Frequently Asked Questions

What are the core components of a Data Vault 2.0 model?

Data Vault 2.0 is built on three primary table types that work together to create a flexible and scalable data model.

• Hubs (The Business Keys): A Hub contains a list of unique business keys. Think of them as the nouns of your business: Customer ID, Product SKU, Invoice Number. They contain very little information beyond the key itself, a load timestamp, and the data source.

• Links (The Relationships): A Link establishes a relationship between two or more Hubs. They are the verbs of your business, representing transactions or associations. For example, a Link could connect a Customer Hub and a Product Hub to represent a purchase.

• Satellites (The Descriptive Context): A Satellite contains all the descriptive attributes about a Hub or a Link and tracks changes to that data over time. A Customer Hub might have a Satellite with the customer’s name, address, and credit score. If the customer’s address changes, a new record is added to the Satellite, providing a full historical view.

Data Vault vs. Kimball: When should I choose Data Vault?

Choosing a modeling methodology is a major architectural decision. The choice depends on your organization’s specific needs.

Choose Data Vault if: Your organization has many complex data sources, needs a highly auditable and scalable core, and expects business requirements to change frequently. Choose Kimball if: Your sources are stable, your reporting requirements are well-defined, and speed-to-report for business users is the top priority.

What is the difference between a Raw Vault and a Business Vault?

The Raw Vault is the first layer built from the source systems. Its purpose is to integrate the data and store it in its rawest form, preserving a complete, auditable history. No business rules or transformations are applied here. This calculator estimates the size of your Raw Vault.

The Business Vault is an optional layer built on top of the Raw Vault. It contains derived tables where business rules, calculations, and transformations are applied to create data that is ready for consumption. For example, a “360-degree customer view” would be built in the Business Vault by combining data from multiple Raw Vault Satellites.

How accurate are these estimates?

This calculator is a scoping and estimation tool, not a precise forecasting engine. Its accuracy is directly proportional to the quality of your initial analysis and inputs. It’s designed to give you a “t-shirt size” estimate (Small, Medium, Large, XL) for your project during the initial planning and discovery phases. Use these numbers to guide architectural discussions, not to purchase specific hardware or finalize budgets.

How do I identify Hubs, Links, and Satellites from my source data?

• Look for Business Keys: Scan your source data for things that uniquely identify a core business concept. These are your Hubs. Examples: CustomerID in a CRM, EmployeeID in an HR system, SKU in an inventory system.

• Identify Natural Relationships: Look for tables or processes that bring business keys together. A sales order line item that has both a CustomerID and a ProductID represents a relationship. This becomes a Link.

• Find the Context: Any attributes that describe a business key or a relationship become Satellites. For a CustomerID Hub, the fields FirstName, LastName, Address, and CreateDate would go into a Customer Satellite.

Does this calculator account for the Business Vault?

No. This tool focuses exclusively on estimating the Raw Vault. The size and complexity of a Business Vault are entirely dependent on your organization’s specific business rules and reporting needs, which vary too much to be estimated by a generic calculator.

What is a “loading pattern” in the context of Data Vault?

A key benefit of Data Vault 2.0 is the use of standardized, repeatable templates for loading data. Every Hub table is loaded using the same pattern, every Link uses another, and every Satellite uses a third. This calculator’s “Total ETL/ELT Loading Patterns” estimate is simply the number of tables you’ll need to build, as each one corresponds to one of these standardized jobs. This templated approach dramatically speeds up development compared to writing custom logic for every table.

Does the storage estimate include compression and indexing?

No. The storage estimate is a raw calculation based on data types and row counts. Modern cloud data warehouses (like Snowflake, BigQuery, Redshift) have excellent, automatic compression that can reduce this footprint by 3-10x. The estimate also does not include the overhead for indexes, which you might create to improve query performance. You should treat the calculated number as a pre-compression, pre-indexing baseline.

What are the main benefits of using the Data Vault 2.0 methodology?

Organizations choose Data Vault 2.0 for four key reasons:

1. Agility & Flexibility: New data sources can be added easily without disrupting the existing model, which is crucial in a constantly changing business environment.

2. Scalability: The model is designed for massive parallelism, allowing it to scale to petabytes of data by loading tables independently and simultaneously.

3. Auditability & Traceability: The Raw Vault provides a pristine, unaltered copy of source data with full historical tracking, making it easy to trace any piece of data back to its origin.

4. Automation: The use of standardized patterns and templates allows for a high degree of automation in the data ingestion and modeling process, reducing development time and errors.

Other Tools You Might Find Useful

After estimating the scope of your Data Vault, you may need to plan for other aspects of your data platform.

• To convert your storage estimate into different units, use our [Data Storage Converter].

• To estimate potential cloud warehousing costs, check with specific vendors or use a generic Cloud Data Warehouse Cost Calculator.

• To see how long it might take to upload your historical data, use our Upload Time Calculator.