Category: Data Integration

Category: Data Integration
Informatica World 2016: Digital Disruption Demands Data Centricity

Data Powers Business Informatica World 2016, being held in Moscone West, San Francisco on May 23 -26, is the launching pad for Informatica’s “Next-Gen Data Architecture.” The conference theme is “Data Powers Business”, a response to the evolving data-centric landscape in which data intelligence and customer experience are driving business and technology decisions. At IW … Continue reading “Informatica World 2016: Digital Disruption Demands Data Centricity”

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What differentiates Informatica’s Intelligent Data Lake platform?

Three reasons why you should be impressed with Informatica’s Intelligent Data Lake platform:  Cohesiveness, Cohesiveness, and Cohesiveness! Informatica raises the bar While other leading Data Integration vendors advertise a broad portfolio of products that might include Master Data Management, Self-service Data Preparation and Big Data Integration, Informatica raises the bar by combining the power of … Continue reading “What differentiates Informatica’s Intelligent Data Lake platform?”

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Comparing Patterns of Big Data Integration

Previously, I introduced five key patterns of big data integration. Here, we review those patterns, then dive into the pros and cons of each. Five key big data integration patterns With increased reliance on Hadoop and Spark for data management, processing and analytics, data integration strategies should evolve to exploit big data platforms in support … Continue reading “Comparing Patterns of Big Data Integration”

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Syncsort Establishes a New Milestone in Exploiting Mainframe Data with Hadoop

Syncsort is a key player in mainframe data access and integration. The company’s DMX-h product enables ingestion of historical, mainframe data into Hadoop, thereby capitalizing on the power of Hadoop for processing and analyzing mainframe data in combination with other relevant data. Syncsort has taken a significant leap forward with its latest release of DMX-h … Continue reading “Syncsort Establishes a New Milestone in Exploiting Mainframe Data with Hadoop”

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Five Patterns of Big Data Integration

As reliance on Hadoop and Spark grows for data management, processing and analytics, data integration strategies should evolve to exploit big data platforms in support of digital business, Internet of Things (IoT) and analytics use cases. While Hadoop is used for batch data processing , Spark supports low-latency processing. Integration leaders should understand the various … Continue reading “Five Patterns of Big Data Integration”

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