Data Asset Inventory (DAI)

What is a Data Asset Inventory (DAI)?

A data asset inventory (DAI) is a structured catalog that finds, lists and details all of an organization’s data, aiding compliance and data security. This includes internal and external data, its location, sensitivity and importance, along with descriptive metadata. 

To be successful, a data asset inventory has to be:

1. Comprehensive: including all relevant structured/unstructured data, whether stored on-premise or in the cloud — across structured and unstructured; cloud and on-prem
2. Accurate and complete
3. Consistent: acting as a single source of truth for privacy, security, and governance

It includes information such as:

• The location of data
• Security measures protecting specific data
• Who can access data
• Where data was obtained and who owns it
• How data flows between systems in the organization

A data asset inventory is a key component of an organization’s data asset management and overall data management strategies. The GDPR requires that organizations deploy a data asset inventory to achieve compliance.

What are the benefits of a Data Asset Inventory (DAI)?

A data asset inventory delivers both reactive benefits (such as compliance/risk management) and proactive advantages (including supporting digital transformation and increased data consumption). Overall it allows organizations to:

1. Better understand and protect sensitive information
2. Meet regulatory/compliance requirements, such as around the GDPR
3. Improve risk management around data
4. Make better informed decisions through comprehensive insights into available data
5. Optimize resources, including reducing data duplication and outdated information
6. Improve data governance
7. Improve data quality and understand gaps/needs in organizational data
8. Increase operational efficiency by providing a single version of the truth around data
9. Enable the training of AI models more successfully through quality data 

How do you create a Data Asset Inventory (DAI)?

• Begin the process by carrying out a deep data discovery of all organizational data, starting with the most critical/heavily used sources
• Assess the sensitivity of each data asset along with data relationships, identities, inferred data, metadata and associated data
• Look to answer the questions of how the data asset is used, what it includes, and who owns it
• Use this to assess risk and required security protections
• Make the information in the data asset inventory available via your data catalog, providing a searchable, accessible platform across your data assets

These processes can be carried out manually, or through specialist automated software tools.

What is the difference between a Data Asset Inventory, Data Asset Management and a Data Catalog?

There can be confusion between the relative roles of the data asset inventory, data asset management and a data catalog within the data stack. Each has a specific function and brings its own value to wider data management.

Data Asset Inventory

A data asset inventory lists and details the type and location of each data asset in an organization. It primarily serves as a source for compliance and risk management, providing a high level overview of all data. It includes the technical metadata for each data asset.

Data Catalog

A data catalog is the next step above a data asset inventory, organizing the contents of the data asset inventory in a centralized platform with the aim of aiding search, discovery, management and the greater usage of data. While still aimed at technical users, it is more user-friendly and searchable to help with data discovery. Alongside technical metadata, it also includes business, operational and social metadata, as well as information around data lineage and data quality.

Data Asset Management

Data asset management is the overall process of organizing, managing and optimizing data assets to drive business value. A data asset inventory is one of the first steps in successful data asset management, while a data catalog is a more searchable and usable, higher level solution. Both a data asset inventory and a data catalog are part of the data asset management stack.