Preparing and integrating data

You can use Cloud Pak for Data to integrate data across multiple clouds to refine data, transform data, virtualize data, manage data, and privatize data.

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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.
Refining data with Data Refinery
Use Data Refinery to cleanse and shape tabular data with a graphical flow editor. You can also use interactive templates to code operations, functions, and logical operators. When you cleanse data, you fix or remove data that is incorrect, incomplete, improperly formatted, or duplicated. When you shape data, you customize it by filtering, sorting, combining or removing columns, and performing operations.
Creating synthetic data
Use the graphical flow editor tool Synthetic to generate synthetic tabular data based on production data or a custom data schema using visual flows and modeling algorithms.
Curating data for quality
Import metadata, enrich data assets with additional metadata, and assess data quality.
Managing data quality
Measure, monitor, and maintain the quality of your data to ensure the data meets your expectations and standards for specific use cases.
Transforming data with DataStage
Use DataStage to move and transform data between operational, transactional, and analytical target systems. Develop flows using prebuilt transformation functions and parallel processing capabilities to transform data and integrate it with many systems throughout your organization.
Managing master data
Use IBM Match 360 with Watson to consolidate data from the disparate sources that fuel your business to establish a single, trusted, 360-degree view of your customers.
Masking data
Use Data Privacy to extract protected data that can be used by data scientists, business analysts and testers. Data is protected with advanced data masking options to comply with data privacy regulations and the usefulness of the data is maintained.
Replicating data
Use Data Replication to integrate and synchronize data. Data Replication provides near-real-time data delivery with low impact to sources.
Managing feature groups
Create a feature group to preserve a set of columns of a data asset along with associated metadata for use with Watson™ Machine Learning models. Publish feature groups to IBM® Knowledge Catalog so that it can be used as a feature store. Feature groups in IBM Knowledge Catalog can be searched and reused by others without them needing access to your project.