Informatica®, a provider of data management solutions and recognized as a big data fabric leader by Forrester, announced Informatica Cloud Data Lake Management, a comprehensive solution for managing data lakes in either cloud or on-premise environments. Built on the Informatica Intelligent Data Lake, Informatica Cloud Data Lake Management is a comprehensive solution for quickly and easily finding, preparing, mastering, governing and protecting enterprise data in Hadoop-based data lakes to power faster and more trusted data-driven insights, on-premise or in the cloud. Everyone from CIOs, to marketing, to IT and C-level executives will benefit from having authoritative data from across the entire organization in their hands for more informed decision making.
Despite their rapidly growing popularity, data lakes are still typically managed using fragmented point solutions and labor-intensive manual processes. This makes it extremely difficult, if not impossible, for data analysts and users to fully realize a data lake’s promised business value. With organizations rapidly turning to off-premise environments for deploying Hadoop, the complexity of integrating, securing, governing and accessing the data only increases. Forrester Research commented in its recent report, The Forrester Wave™ Big Data Fabric, Q4 2016, that “Enterprises of all types and sizes are embracing big data, but the gap between business expectations and the challenges of supporting big data technology (such as Hadoop) has become the primary motivation to innovate with big data fabric…It reduces complexity and hides heterogeneity by embodying an abstracted model of the data processing pipeline that reflects business requirements rather than the complexity of the underlying systems.”
Informatica is powering the modern data democracy by making it possible to transform any big data into genuine business value, anywhere,” said Ronen Schwartz, senior vice president and general manager, Data Integration, Big Data and Cloud. “Informatica Cloud Data Lake Management eliminates the problems associated with using fragmented, limited functionality solutions for managing data lakes, while enabling customers to fully benefit from the economic advantages and the many opportunities for agility presented by the cloud.”
Available by the end of Q2 2017, the Informatica Cloud Data Lake Management solution extends the proven capabilities of the Informatica Intelligent Data Lake®, Informatica Big Data Management®, Informatica Big Data Quality, Informatica Intelligent Streaming, Informatica Enterprise Information Catalog and other industry-leading Informatica technologies to deliver the only complete, intelligent and fully cloud-ready solution for turning big data into easily accessible and trusted data assets, in the cloud or on-premise.
Since the early days of our partnership, Cloudera and Informatica have jointly led the market with best practices and tight integrations with Cloudera Navigator and Cloudera Manager, dramatically simplifying big data integration, end-to-end data governance and robust big data protection,” said Tom Pinckney, head of Business Development, Cloudera, “Informatica’s updated Cloud Data Lake Management solution enables organizations to have even greater flexibility to deploy our respective market leading functionality both on-premise and in the cloud.”
Market’s Most Comprehensive Solution for Cloud-Ready Data Lakes
Informatica Cloud Data Lake Management provides data professionals with all the critical capabilities for deploying data lakes anywhere organizations desire. The breadth and depth of this cloud functionality is unmatched in the data lake management marketplace, and includes:
- Real-time stream processing on cloud – Informatica Intelligent Streaming will support connectivity to Amazon Kinesis Firehouse and pushdown to Amazon Kinesis Streams for cloud-based stream processing.
- Data preparation on cloud – Informatica Intelligent Data Lake will be certified with Amazon Elastic MapReduce and Microsoft Azure HDInsight.
- Automated data ingestion to/from cloud – Informatica Intelligent Data Lake will support automatic import and export of data from Amazon Web Services Redshift, Amazon Aurora, Microsoft Azure SQL Database and Microsoft SQL Data Warehouse.
- Rapid deployment on cloud – Informatica Enterprise Information Catalog will now have single-click deployment on Amazon Web Services.
- Native data connectivity in the cloud – Informatica Big Data Management now connects natively to Microsoft Azure Data Lake Store when processing data on Microsoft Azure HDInsight.
Turning Big Data into More Trusted Data Assets
Informatica Cloud Data Lake Management is engineered to drive a wide range of positive outcomes for data professionals and business users. Previously elusive, these business outcomes include:
- Understanding customers in just seconds – Informatica MDM – Relate 360 now uses a graph-based processing engine to match and relate even more data to deliver a more comprehensive view of customers and other business-critical entities.
- Maximum self-service empowerment – In addition to its self-service data preparation interface, Informatica Intelligent Data Lake now empowers business analysts to enter business rules to maximize data quality without reliance on IT.
- Maximum extensibility to new data sources – Informatica Enterprise Informatica Catalog will be able to create custom metadata scanners for fast and easy extensibility to custom data sources such as legacy databases or bespoke applications.
- Maximum extensibility to new applications – Informatica Enterprise Information Catalog will have REST-based APIs to its metadata repository for easy extensibility to custom web portals, workflow-based systems and reports.
- Smarter data discovery – Informatica Enterprise Informatica Catalog will have composite domains for more automated identification and classification of business entities.
- Extreme big data integration performance – Informatica Big Data Management now supports the push-down of advanced transformations, including updates and stateful functions, to Apache Spark 2.1.0 for superior data integration performance.
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