Your employees need to make data-driven decisions, but too often, data is in silos. With a deep understanding of your organization’s needs and use cases, you can design a data architecture that empowers your teams and works across the ecosystem.
The most common data use cases and challenges? Data integration, data governance, AI governance, and data science and MLOps. Learn more about each and how a modern data architecture—like data fabric—can help shape a data-driven enterprise.
How to build your data architecture
Download the latest Forrester Wave™: Enterprise Data Fabric, Q2 2022 report
A modern data architecture ensures data is accessible to relevant data users
based on their unique workflows. Data fabric is an architectural approach that
simplifies data access in an organization and facilitates self-service data
consumption. Teams can use this architecture to automate data discovery,
governance and consumption, through integrated end-to-end data
management capabilities. Whether data engineers, data scientists or business
users are your intended audience, a data fabric delivers the data needed for
With a unified data and AI platform, the IBM® Global Chief Data Office increased its business pipeline by USD 5 billion in three years.
Luxembourg Institute of Science and Technology built a state-of-the-art platform with faster data insights to empower companies and researchers.
State Bank of India transformed its customer experience by designing an intelligent platform with faster, more secured data integration.
An abstraction layer that provides a common business understanding of the data and automation to act on insights.
A range of integration styles to extract, ingest, stream, virtualize and transform data, driven by data policies to maximize performance while minimizing storage and costs.
A marketplace that supports self-service consumption, letting users find, collaborate and access high-quality data.
End-to-end lifecycle management for composing, building, testing and deploying the various capabilities of a data fabric architecture.
Unified definition and enforcement of data policies, data governance and data stewardship for a business-ready data pipeline.
An AI-infused composable architecture built for hybrid cloud environments.
IBM was named a Leader for the 17th year in a row in the 2022 Gartner® Magic Quadrant™ for Data Integration Tools.
See why IBM is recognized as a Leader for Data Quality Solutions in the 2022 Garner Magic Quadrant for Data Quality Solutions.
Automate and enforce policies automatically across data on any cloud, with increased visibility and collaboration while reducing compliance risks.
A data fabric and data mesh can co-exist. A data fabric provides the capabilities needed to implement and take full advantage of a data mesh by automating many of the tasks required to create data products and manage the lifecycle of data products. By using the flexibility of a data fabric foundation, you can implement a data mesh, continuing to take advantage of a use case centric data architecture regardless of if your data resides on premises or in the cloud.
Read: Three ways a data fabric enables the implementation of a data mesh
Data virtualization is one of the technologies that enables a data fabric approach. Rather than physically moving the data from various on-premises and cloud sources using the standard extract, transform, load (ETL) process, a data virtualization tool connects to different data sources, integrates only the metadata required and creates a virtual data layer. This allows users to use the source data in real time.
Data continues to compound and is often too difficult for organizations to access information. This data holds unseen insights, which results in a knowledge gap.
With data virtualization capabilities in a data fabric architecture, organizations can access data at the source without moving it, helping to accelerate time to value through faster, more accurate queries.
Data management tools started with databases and evolved to data warehouses and data lakes as more complex business problems emerged. A data fabric is the next step in the evolution of these tools. With this architecture, you can continue to use the disparate data storage repositories you’ve invested in while simplifying data management. A data fabric helps you optimize your data’s potential, foster data sharing and accelerate data initiatives by automating data integration, embedding governance and facilitating self-service data consumption in a way that storage repositories don’t.