“The current state of the world has disrupted business as usual and is driving a true paradigm shift to Data 4.0,” said Amit Walia, CEO of Informatica. “The need for digital transformation has accelerated. Today, we must redefine previous assumptions and enter a world that is cloud native and metadata-driven, supported by intelligent automations and trusted insights, at operational scale. I believe that Data 4.0 is the soul of digital transformation – and that scale, automation and trust can only be achieved with AI and machine learning capabilities.”
Today’s innovations across Informatica’s product portfolio equip businesses with the industry’s most advanced intelligence and automation capabilities, enabling them to achieve Data 4.0 transformation. Fuelled by AI and data, enterprises will be able to rapidly scale, navigating complexity with adaptability, resiliency, agility, flexibility, and responsiveness.
Informatica’s modern, cloud-native, microservices-based, API-driven, and AI-powered Intelligent Data Platform helps unlock the significant untapped value of new data for enterprises by intelligently automating intensive, manual work that leaves room for errors; making data more accessible to enable self-service analytics; and delivering the visibility, flexibility and scalability needed to make critical decisions rapidly while mitigating risk.
These announcements strengthen Informatica’s ability to help organisations accelerate data-driven transformation and become next-generation intelligent enterprises. Highlights include:
Intelligent Data Platform
- Delivers the industry’s most advanced AI/machine learning-powered intelligence and automation capabilities for end-to-end enterprise cloud data management including data cataloging, ingestion, integration, quality, mastering, governance, protection, and deployment.
- Extends the industry’s only intelligent, enterprise-class catalog of catalogs with new innovations in automated data value capture, automated end-to-end lineage, and metadata management, enabling metadata-driven intelligence and automation for all business use cases.
- Automates data value calculation and identifies levers for data asset appreciation, such as data quality and enrichments within an overall data valuation framework.
- Delivers comprehensive data asset analytics with pre-packaged and extensible reports such as data event history and dashboards for instant visibility of data asset usage, inventory, enrichment, collaboration, and data value including real-time key metrics and trend charts along with built-in filters.
- Gain full visibility and quickly get to the root of data analytics errors with automated data lineage stitching from all data sources across the enterprise, as well as automated lineage derivation from the code used to modify, transform, and combine data, and automated change notifications.
- Deliver deeper, smarter insights for business with automated domain discovery for self-service analytics.
- Provides out-of-the-box liability and risk assessment models, such as for regulatory compliance and sensitive data location-related risks.
- Provides a foundational metadata knowledge graph for a holistic view of data relationships.
Cloud Data Warehouse and Data Lakes
- Automate cloud mass ingestion for files, databases (including change data capture), and streaming with intelligent schema drift functionality.
- Reuse existing workloads in the cloud with minimal disruption, thanks to detailed lineage and impact analysis, and prioritise datasets and workloads for migration through a comprehensive understanding of the data landscape.
- Ensure trustworthy data in cloud data warehouse and data lake solutions through cloud data quality and metadata management together with cloud data integration and cloud application integration on a modern, microservices-based, cloud-native platform with serverless computing.
- Accelerate AI and machine learning projects with improved data visibility for agile data prep, analysis, and model development.
- Automate end-to-end data management with AI/machine learning-powered automation to build and tune data integration jobs and detect anomalies.
- Operationalize data pipelines and machine learning in the cloud with DataOps and MLOps for continuous integration (CI) and continuous deployment (CD).
- Save costs and improve performance of running data management workloads using intelligent pushdown processing with a serverless run time engine.
Data Governance & Privacy
- Quickly “shop” for and access enterprise data using a data marketplace digital storefront, with order management and governed provisioning capabilities to ensure timely approval and delivery of data.
- Democratise data by collaboratively defining data quality policies and rules. Discover data and automatically execute where rules should be applied, ensuring trusted data is protected and delivered to data consumers and applications.
- Accelerate data governance projects with new automated capabilities to infer data quality measurement, using natural language processing (NLP) to automatically build Informatica Data Quality rules from business rule definitions.
- Improve compliance transparency with the ability to track protection status, access, proliferation, and risk exposure of sensitive data, leveraging scenario-based planning to apply appropriate protections and detect and mitigate anomalous data access.
- Automate building of data subject registry by correlating relationships between individual subjects’ personal data across structured and unstructured sources to facilitate data subject rights and other privacy compliance activities.
- Automate data governance activities with intelligent data discovery, classification, and documentation of key data elements. Scale business context with glossary linkage physical datasets.
- Automate change notifications to enable proactive management of changes based on impact derived from end-to-end lineage.
- Accelerate and strengthen digital commerce, minimize supply chain risk, increase customer loyalty, and improve finance and operational processes with greater data visibility across customers, suppliers, products, and financials.
- Ensure all master data is clean, complete, and consistent to get an end-to-end 360-degree view across the entire business and understand the relationships between master data domains and the business context.
- Quickly adapt to changing business conditions by leveraging a shared foundation of consistent and trusted master data and relationships across the enterprise for a complete view into business.
- Connect master data to transaction and interaction data to fuel analytics and data science initiatives to answer complex questions and uncover hidden insights.
- Reduce IT workloads while making it easier to find, manage, and curate data to build a 360-degree view of all business-critical data, with intelligent file structure discovery that automates domain mapping recommendations.
- Automate the creation of a complete, trusted, and actionable view of all master data by leveraging industry-leading contextual matching technology powered by AI and machine learning.
- Visualise relationships, taxonomies, and hierarchies at scale using a graph technology to gain rich and insightful views for faster, more accurate decision making.
- Increase operational efficiency by replacing manual processes such as data onboarding, synchronisation, and reporting through intelligence and automation.