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Webtrends, a leading provider of data, analytics and personalization solutions, today announced the availability of its new Infinity Data Connector™. Built on the Webtrends Infinity™ big data platform, the solution allows brands to collect and feed rich, visitor-level analytics data from websites, mobile apps and connected devices into on premise or cloud-based customer warehouses and big data initiatives.
“Even as big data has become the crown jewel of business intelligence, organizations still struggle to unify disparate customer data silos,” said Webtrends CEO Joe Davis.
According to Optimize Customer Experiences With Digital Intelligence, a February 2016 Forrester report by analysts James McCormick and Cinny Little, “To deliver comprehensive and actionable customer insights, firms must merge digital and offline channel data. Web analytics and customer data teams are attempting to work together, but their initiatives struggle to get off the ground due to a clash of approaches and cultures from [data types, skills, analysis and time-to-delivery].”
Davis explained that the Infinity Data Connector can help alleviate this struggle by eliminating time consuming and costly ETL (extract, transform, load) processes.
“This solution ensures that data from any digital channel is seamlessly delivered to Hadoop-based or other data stores,” explained Davis. “For brands that need to understand and act on customer behavior, the Infinity Data Connector will provide a major assist.”
The Infinity Data Connector offers:
- Flexible data collection options including a universal tag, advanced mobile SDKs and a data collection API
- Collection of data from any digital channel, including the Internet of Things (IoT)
- Delivery of all sessionized events and user-level details, enriched with geographic and device information
- High-speed, near real-time delivery
- PGP encryption of data in transit inside an SSL tunnel
- Monitoring and restart services ensure successful data delivery
The Infinity Data Connector supports technologies for storage – Hadoop/HDFS, Amazon S3, Amazon Redshift, Microsoft Azure, Teradata and others – as well as stream processing solutions, including Apache Kafka, Amazon Kinesis and Microsoft Azure Stream Analytics. This flexibility enables rapid loading of fully sessionized, user-centric data to any client or cloud database or data lake.
“To stay competitive, brands want a holistic view of their customers so they can deliver more personalized experiences and make more informed decisions,” said Davis. “We’re now able to help our clients leverage rich behavioral data with unprecedented simplicity, scalability and security.”
This article was originally published on www.finance.yahoo.com and can be viewed in full
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