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SnapLogic Reduces Cloud Integration Time to Market and Costs

By   /  August 28, 2017  /  No Comments

The press release stated that, “SnapLogic, the leader in self-service application and data integration, today announced delivery of its Summer 2017 (4.10) release of the SnapLogic Enterprise Integration Cloud. The release includes a series of platform enhancements to help customers automate, manage, and monitor their integration processes. The Summer 2017 release also features new and enhanced Snaps for improved connectivity and performance with Microsoft Azure SQL Database, Microsoft Dynamics 365, SAP, Teradata, Hadoop HDFS, Confluent, JSON Web Token, Parquet, and RabbitMQ.”

As well as, “SnapLogic also announced new features and strong adoption for Iris, its industry-first artificial intelligence technology for enterprise integration. The first AI-powered feature, SnapLogic Integration Assistant, was released to customers in May and is already driving impressive usage with nearly 50 percent of all Snaps used in the platform being recommended by Integration Assistant versus being manually selected. Now, in addition to expert step-by-step guidance for building data pipelines, Iris also applies machine learning to optimize pipeline performance — making recommendations for pipeline configuration and operation based on real-world performance insights.”

It quoted Vaikom Krishnan that, “’We’re excited to continue delivering innovation every quarter that reduces the time and cost of enterprise integration,” said Vaikom Krishnan, senior vice president of engineering at SnapLogic. “This new release includes several customer-requested enhancements for large-scale integration projects, as well as continued Snap enhancements to connect more data, more applications, and more things.’”

Read more here.

About the author

Charles Roe is the Digital Content Manager at DATAVERSITY. He is responsible for both the article and blogging programs, as well as the DATAVERSITY Training Center. He has been a professional freelance writer and copy editor for more 15 years, and has been writing for the Data Management industry since 2009. Charles has written on a range of industry topics in numerous articles, white papers, and research reports including Data Governance, Big Data, NoSQL technologies, Data Science, Cognitive Computing, Business Intelligence & Analytics, Information Architecture, Data Modeling, Executive Management, Metadata Management, and a host of others. Charles is backed with advanced degrees in English, History, and a Cambridge degree in Language Instruction. He worked for almost 20 years as an instructor of English, History, Culture, and Writing at the college level in the USA, Europe, and Turkey. He writes creatively in his spare time.

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