Uses cases where data virtualization could be valuable!
Data virtualization is a technology that provides a unified view of data from disparate sources without physically moving or replicating the data. It creates a virtual layer that sits on top of the underlying data sources and abstracts away the complexity of managing and accessing the data.
Data virtualization has several valuable use cases across different industries and business functions:
Other reasons why companies use data virtualization include:
To reduce the cost and complexity of data management
To improve the performance of data analytics queries
To enable real-time analytics
To improve data governance
To facilitate data migration
Here are some specific examples of how data virtualization can be used in different industries:
Retail: Retailers can use data virtualization to integrate data from their CRM system, e-commerce platform, and point-of-sale system to create a single view of their customers. This can help them to understand their customers' buying habits, target them with personalized offers, and improve customer loyalty. | Financial services: Financial services companies can use data virtualization to integrate data from their core banking system, trading system, and risk management system to create a single view of their customers and their portfolios. This can help them to reduce risk, improve fraud detection, and make better investment decisions. |
Healthcare: Healthcare providers can use data virtualization to integrate data from their patient records system, electronic health records system, and billing system to create a single view of their patients. This can help them to improve patient care, reduce costs, and comply with regulations. | Walmart - Created a virtualized view of item, supply chain, and store data to enable real-time inventory visibility across stores and online. Reason: Speed time to insight by consolidating data without replication and the agility to analyze new data sources easily. |
Cisco - Uses data virtualization to merge device, network, and customer data into a unified view for technical support and operations. Reason: Decouple reporting and analytics from source systems. | BMW - Virtualizes sensor data from vehicles to power analytics and serve insights faster. Reason: Single source of truth for consistent results. |
Morgan Stanley - Consolidates trading data in a virtualized platform to enable risk analytics and regulatory reporting. | Cigna - Virtualized claims data from sources across the organization to enable self-service analytics for business users. |
Sash Barige
Nov/5/2022
References:
Forrester: Data Virtualization: The Path to a Unified View of Data
Gartner: Data Virtualization: A Critical Enabler for Digital Transformation
Denodo: Top 3 Data Virtualization Use Cases for Data Warehousing
Informatica: Data Virtualization for Data Warehousing
HIMSS: Data Virtualization for Healthcare Data Management
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