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Virtualizing data with Watson Query

Virtualizing data with Watson Query

Use Watson Query to create a virtual table to segment or combine data from one or more tables. Watson Query connects multiple data sources into a single self-balancing collection of data sources or databases.

 

The Watson Query service is a part of the data fabric.

Overview

Required service
Watson Query.

You must create and deploy a service instance of Watson Query in Cloud Pak for Data as a Service to virtualize your data. For more information, see Provision a service instance for Watson Query.

After you provision your service instance, you can set up your Watson Query instance. For more information, see Getting started with Cloud Pak for Data as a Service and Quick start: Virtualize data.

Related service
IBM Knowledge Catalog.

If you want to publish your virtual data to a governed catalog, you must install IBM Knowledge Catalog. For more information, see Getting started with curating and governing data.

Data formats
Watson Query works with connections to many types of data sources and formats. For more information, see Connecting to data sources in Watson Query.
Data size
Data size limits are defined by each data source. For more information, see Supported data sources in Watson Query.
Credentials
Watson Query uses your IBM® Cloud credentials to connect to the service. You must have certain Watson Query roles to perform certain tasks. For more information, see Connecting and authenticating to the Watson Query service.
Limitations
See Limitations and known issues in Watson Query.

Watch the following video for an overview of Watson Query.

This video provides a visual method as an alternative to the written documentation.

Learn more

For more information about these tasks, see the following resources.

Generative AI search and answer
These answers are generated by a large language model in watsonx.ai based on content from the product documentation. Learn more