Informatica Launches Industry’s Most Comprehensive Data Engineering Solution to Address Critical Gap in Enterprise AI, Machine Learning and Analytics Initiatives

Informatica Launches Industry's Most Comprehensive Data Engineering Solution to Address Critical Gap in Enterprise AI, Machine Learning and Analytics Initiatives

Data Engineers Now Have a Comprehensive Suite of Industry-Leading Products for End-to-End Data Management in Hybrid and Multi-Cloud Environments Leveraging Serverless Compute Capabilities

Informatica, the enterprise cloud data management leader, announced the launch of the Informatica Data Engineering solution, which provides the complete suite of tools data engineers need to deliver clean, reliable, trusted, and accessible data for enterprise AI, machine learning, and analytics initiatives in hybrid cloud and multi-cloud environments.

Informatica’s Data Engineering solution supports seamless integration with Databricks, for customers looking to leverage the cloud platform with Spark, Delta Lake, and serverless support. With Informatica Data Engineering, users can easily discover datasets and ingest high volumes of data from multiple sources. The serverless capability of the solution enables customers to lower the costs of creating and maintaining data engineering pipelines at scale.

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Additionally, the Informatica Data Engineering solution includes a suite of products that provide end-to-end data management support in hybrid and multi-cloud environments.

  • Data Engineering Integration, which intelligently manages analytics and machine learning data pipelines with data ingestion and processing in a hybrid, multi-cloud environment.
  • Data Engineering Streaming, which turns volumes of streaming and IoT data into contextualized insights with recommended actions.
  • Data Engineering Quality, which allows users to govern all of their data in cloud and hybrid environments to ensure the data is trusted and relevant.
  • Data Engineering Masking, which can “de-identify” data to minimize risk exposure in applications, BI, AI, and analytics use cases.
  • Enterprise Data Catalog, which classifies and organizes data assets across any environment to ensure lineage and to maximize data value and reuse.
  • Enterprise Data Preparation, which can find, prepare, and ensure data quality for analysis and AI in a uniquely collaborative way so that data analysts and data scientists can make decisions faster.
  • Mass Ingestion, which allows users to ingest data at scale from a variety of sources, including streaming data, files, and databases using an easy-to-use five-step wizard.

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Supporting Quotes:

  • “Databricks and Informatica enable data engineers to build reliable data pipelines and process them at scale with Apache Spark and Delta Lake capabilities,” said Michael Hoff, senior vice president of Business Development and Partners at Databricks. “As a result, our joint customers can drive faster development and insights with their data for analytics and machine learning.”

  • “As today’s enterprises strive to achieve successful analytics and AI initiatives, data engineers must provide quality data to their data science and data analytics counterparts,” said Ronen Schwartz, senior vice president and general manager, Data Integration, Data Engineering, and Cloud, Informatica. “These initiatives require a comprehensive set of capabilities to support data engineers, who serve as the backbone of a data-driven organization. Informatica’s Data Engineering solution is the most comprehensive in the market and it enables data engineers to meet the requirements of their business stakeholders by empowering data analysts and data scientists with trusted, quality data they can utilize for their analytics and AI needs.”

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