These methodologies are enabling organizations to unify their data, gain deeper insights, and activate data in real time to drive business growth and innovation
Real-time capabilities: Advanced data clouds offer sub-second real-time data ingestion, analysis, and activation. This enables real-time AI recommendations, analytics, and automation.
AI/ML integration: Leading data clouds have built-in AI and machine learning capabilities to derive insights from data. This includes support for processing unstructured data like audio and video content.
Flexible and open architecture: Data clouds are built on open protocols and standard interfaces for easier integration. They offer flexible integration with various data sources, analytics tools, and applications.
Enhanced security and governance:
-Improved policy-based governance to control sensitive data sharing.
-Features like AI tagging/classification of data and secure connectivity options.
Scalability and performance:
-Ability to process massive volumes of data (quadrillions of records).
-On-demand provisioning of compute and storage resources.
Industry-specific solutions: Tailored data cloud capabilities for industries like retail, healthcare, logistics, and financial services.
Ecosystem expansion:
-A growing ecosystem of pre-built connectors to integrate various data sources and applications.
-Improved analytics and insights: Advanced analytics capabilities to gain deeper customer insights.
-Support for real-time and predictive analytics.
-Focus on business outcomes: Emphasis on driving tangible business value like improved profitability, cost savings, and risk management.
These methodologies are enabling organizations to unify their data, gain deeper insights, and activate data in real time to drive business growth and innovation
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