Data integration tools and solutions are a group of technical and business processes designed to combine data from disparate sources into meaningful and valuable data sets. Tools such as ETL, data replication and data virtualization offer data integration solutions that extract large volumes of data from source systems and load it to an enterprise data warehouse or cloud source.
IBM offers scalable, multicloud data integration solutions which can be used stand-alone or as managed services on IBM Cloud®. Leverage IBM solutions such as IBM Cloud Pak® for Data platform to make the most of your siloed data and accelerate your AI journey.
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Gain enterprise scale and security with a data integration platform running on Red Hat® OpenShift®.
Accelerate delivery and reduce TCO with AI-powered automation of tasks.
Leverage container technology to run data integration across hybrid and multicloud environments.
A leader in ETL, IBM® DataStage® is a highly scalable data integration tool for designing, developing and running jobs that move and transform data on premises and in the cloud.
With a modern container-based architecture on Red Hat OpenShift, IBM DataStage for IBM Cloud Pak for Data combines this industry-leading data integration with DataOps, governance and analytics on a single data and AI platform. Deliver trusted data at scale across hybrid or multicloud environments.
Advance end-to-end data integration to cleanse, monitor, transform and deliver trusted data.
Understand, cleanse, transform, monitor and deliver trustworthy and context-rich information.
Data integration is used when organizations need to combine and analyze static data, while application integration is best for when you need to interact with data that is changing in real time. This blog outlines key differences and how IBM solutions can make your data more accessible and functional.
From data integration to data quality, the services within IBM DataStage have the machine learning-powered features enterprises need to power their data integration journey. Read this blog and jumpstart your data integration journey.
See how IBM has been named a leader in the Magic Quadrant for Data Integration for over a decade.
Learn why data integration is critical to deliver real-time access to large volumes of data for AI.
Join this webinar to learn five steps to reduce costs, increase scale and add flexibility.