Collect, access, and maintain quality, actionable data for business and data science
Data management is the practice of collecting, accessing, maintaining, and driving value from data in an agile, secure, and cost-effective manner. Key components of a data management strategy include data governance, processing, security, and storage.
Discover how to integrate IBM Envizi with Planning Analytics AddOn for ESG forecasting, target setting, scenario modeling, and achieving sustainability goals.
This article provides details on the features and use cases of the IBM watsonx product suite to show how users can manage the full AI lifecycle when integrating all parts of the watsonx portfolio together.
Learn efficient Redis data deletion strategies using Lua scripting and external processing to optimize performance, reduce latency, and manage memory efficiently.
Learn how the Arrow Flight service provided by IBM Cloud Pak for Data can be used to read and write data sets from within a Spark Java application that is deployed in IBM Analytics Engine. Arrow Flight provides a common interface for Spark applications to interact with a variety of different data sources.
Fybrik is a cloud native platform to unify data access, governance and orchestration, enabling business agility while securing enterprise data. By providing access and use of data only via the platform, Fybrik brings together access, performance and governance for data, greatly reducing risk of data loss.
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