Informatica, the enterprise cloud data management leader, announced it has updated its Intelligent Data Platform™, powered by Informatica’s AI-powered CLAIRE™ engine. Today’s release includes the introduction of a privacy analytics dashboard for reducing the cost of compliance with laws like the California Consumer Privacy Act (CCPA) and Europe’s General Data Protection Regulation (GDPR), Data Asset Analytics (DAA) for data valuation, end-to-end support for DataOps and MLOps, and integration platform-as-a-service (iPaaS) updates that enable organizations to build more resilient and reliable integrations while providing 24/7 operations for business continuity. Updates to multi-cloud Master Data Management (MDM) allow businesses to master business-critical data to increase customer retention and loyalty, manage supply chain risk, drive digital commerce, and boost operational efficiency.
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“In today’s era of Data 4.0, and as businesses navigate an increasingly complex landscape, digital transformation must be data-led,” said Amit Walia, CEO of Informatica. “Today’s release empowers data leaders to create more value and improve operational efficiency, all while ensuring business continuity. By introducing more automation and intelligence capabilities – powered by CLAIRE – businesses can accelerate ROI, decrease risk and improve productivity across hybrid and multi-cloud environments.”
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Highlights include:
- Updates to Informatica Cloud Native Data Management Solution for Cloud Data Warehouses, Data Lakes, and Lakehouses
Updates to Informatica’s Cloud Native Data Management Solution for Cloud Data Warehouses, Data Lakes, and Lakehouses deliver high availability and upgrade management enhancements for business continuity to avoid downtime from scheduled events and upgrades without job interruption, including:
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- Support for serverless computing, intelligent pushdown processing, auto-tuning and auto-scaling, as well as a heatmap for integration jobs for optimizing performance, resources, and schedules.
- End-to-end support for DataOps and MLOps, including enhanced support for schema drift, data quality transformations and deduplication, blockchain and image transformations, data pipeline and data prep recipe recommendations, similarity-based pipeline categorization, and streaming data lineage.
- Enhanced cloud ecosystem support, including for Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), Snowflake, and Databricks.
These updates will empower organizations to build lakehouses in the cloud by merging data warehouses and data lakes into one platform, combining technologies for business analytics and decision-making with those for exploratory analytics and data science. Compared to on-premises data warehouses and data lakes, this modern approach offers more flexibility and agility at a lower cost.
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