Companies often try to break down silos by copying disparate data for analysis into central data stores, such as data marts, data warehouses and data lakes. This is costly and prone to error when most manage an average of 400 unique data sources for business intelligence.¹ With data virtualization, you can access data at the source without moving data, accelerating time to value with faster and more accurate queries.
Data virtualization tools break down siloes and query multiple sources to manage and govern data.
Make data available with real-time, self-service access for business users and citizen data scientists.
Cut migration and duplication costs. Democratize data access and improve data governance and security.
Query across various databases and big data repositories for centralized access control and governance.
Build a 360-degree view of customer data to unlock deeper insights for personalized customer engagement.
Easily deliver trusted data and accelerate innovation by connecting the right data to the right people.
Learn how businesses can simplify data governance to create a trusted business-ready data foundation.
Data virtualization use cases
Access disparate data with a universal query engine
With IBM Watson Query you can use a single distributed query engine across multiple data sources. Watson Query combines with data virtualization to query across clouds, databases, data lakes, warehouses, and streaming data without copying or data movement. You gain faster access to the data you need most.
Build a trusted data foundation with a data fabric solution
Connect the right data to the right people at the right time with an intelligent data fabric. This architectural approach simplifies access to various data types across hybrid, multicloud environments with data governance, security and compliance. With data virtualization from IBM, you can increase data accuracy with near real-time and self-service access to trusted, quality data at the source.
Breaking down data silos and accelerating queries
With tools like IBM Cloud Pak for Data, data virtualization helps our clients build, run and manage an integrated view of their data services faster and with fewer resources than traditional warehousing and extract, transform, load (ETL) approaches.
