Interana Extends Leadership in Analyzing Behavior Across Diverse Data Sources

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Interana, a leader in interactive behavioral analytics, announced the general availability of Interana 2.24. Notable features include a new streaming ingest API, JavaScript SDK, and integrations with Segment, mParticle, and Kafka for quicker and simpler data ingest across multiple data sources.

As more people rely on data to inform and guide critical decisions, analytics solutions need to be capable of rapidly analyzing large volumes of data across multiple sources. While scalability and performance are often seen as the most important characteristics of analytics solutions, a survey of 170 analytics end-users conducted by Interana earlier this year found that 43% of respondents felt their solution was not flexible enough to meet their needs. This lack of flexibility is often due to analytic solutions’ architectures that restrict what, how, and when data can be ingested.

Unlike analytics solutions with approaches limited to client tagging, Interana 2.24 offers a variety of options to ingest event data, making it easy for users to blend data from disparate data sources for holistic analysis and exploration. Users can ingest data into Interana by importing event files or using Kafka consumption or the new streaming ingest API to connect to existing data pipelines and other upstream data sources.

Enabling people to routinely and interactively explore real behavior to inform everything they do has been our core vision from the very beginning,” said Christina Noren, chief product officer at Interana. “Interana 2.24 further extends our leadership in offering interactive behavioral analytics across all sources of event data and supports accelerating trends toward modern data pipelines.”

New features in Interana 2.24 include:

  • Streaming ingest API to accept events via an HTTP API in addition to ingesting events in the form of files
  • JavaScript SDK to track client events and send them to Interana via the streaming ingest API
  • New integrations with Segment and mParticle
  • Ability to consume from external Kafka topics
  • Easier exploration from dashboards


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