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Create Datasets by Combining Catalog Items in Ataccama ONE Desktop

Learn how to create datasets by combining catalog items in Ataccama ONE Desktop to improve data governance, data quality, and analytics.

· · 3 min read

In today’s data-driven enterprise, the ability to create meaningful datasets from existing data catalog items is one of the most powerful capabilities available to data engineers and data stewards. Ataccama ONE Desktop provides a robust, intuitive environment to discover, combine, and govern your data assets — all within a unified data management platform.

Whether you’re building a dataset for self-service analytics, reporting, regulatory compliance, or enterprise initiatives, understanding how to combine catalog items in Ataccama ONE Desktop is a foundational skill that accelerates data governance, metadata management, and data quality management workflows.

What Is Ataccama ONE Desktop?

Ataccama ONE Desktop is the standalone, locally installed version of Ataccama ONE, an enterprise data governance, master data management (MDM), and data quality management platform. It enables data professionals to:

  • Discover and catalog data assets across multiple sources using a centralized data catalog
  • Profile and cleanse data using built-in data quality rules
  • Create and manage datasets by combining multiple catalog items
  • Govern data through data lineage, metadata management, and compliance tracking

By bringing together data discovery, governance, and quality capabilities, Ataccama helps organizations build trusted and reusable data products.

Creating a Dataset by Combining Catalog Items in Ataccama ONE Desktop

Step 1 : Launch Ataccama ONE Desktop and Navigate to the Data Catalog

Open Ataccama ONE Desktop and access the data catalog, where all available data assets are organized and searchable. The data catalog serves as the foundation for discovering and managing enterprise data resources.

Step 2: Browse and identify Catalog items to Combine

Use the catalog search and filtering capabilities to locate relevant catalog items, datasets, and business-critical data assets. Review metadata, ownership information, and data lineage details to ensure you are selecting trusted data sources.

Step 3: Create a New Dataset

Create a new dataset within Ataccama ONE Desktop. This allows you to consolidate information from multiple catalog items into a single, governed dataset designed for analytics, reporting, or business operations.

Step 4:Add Catalog Items to the Dataset

Select and add the required catalog items to your dataset. Combining multiple data assets helps create a unified view of information while maintaining consistency and governance standards.

Step 5:Configure Joins and Attribute Mappings

Configure joins and attribute mappings between the selected catalog items. Proper mapping improves data quality, ensures data consistency, and supports effective data integration across systems.

Step 6:Save and Publish the Dataset

Save and publish the dataset so it becomes available for broader use across the organization. Published datasets support self-service analytics, operational reporting, and enterprise decision-making while adhering to data governance policies.

Step 7:Run the Dataset and Review Results

Execute the dataset and review the results to verify accuracy, completeness, and quality. Use profiling and validation features available in Ataccama ONE Desktop to ensure the dataset meets organizational standards for data quality management.

Conclusion:

Unlock the Power of Your Data Catalog with Ataccama ONE Desktop

Creating datasets by combining catalog items in Ataccama ONE Desktop is a game-changing capability for organizations focused on data governance, data quality management, and self-service analytics. By following the steps outlined in this guide—from data catalog discovery to dataset publication—you can build trusted, governed, and reusable data assets that support your entire enterprise data ecosystem.

Ataccama ONE Desktop’s integration of the data catalog, data quality management engine, metadata management framework, and data lineage capabilities ensures every dataset is more than just a collection of information. Each dataset becomes a governed, documented, and trustworthy data product that supports compliance, operational efficiency, and data-driven decision-making.

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