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Apache Kafka 1.0, IBM Watson upgrades, and Cisco’s first voice assistant for meetings, in today’s trending stories in data science news.

New version releases

Apache Kafka goes 1.0

Open source distributed streaming platform Apache Kafka has released its version 1.0.0. Apache Kafka 1.0 includes performance improvements with exactly-once semantics, significantly faster TLS and CRC32C implementations with Java 9 support, significantly faster controlled shutdown, and better JBOD support, among other general improvements and bug fixes, according to the official announcement. Apache Kafka is in use at large and small companies worldwide, including Capital One, Goldman Sachs, ING, LinkedIn, Netflix, Pinterest, Rabobank, Target, The New York Times, Uber, Yelp, and Zalando, among others.

Pentaho 8.0 integrates Spark and Kafka, boosts real-time data processing capabilities

Pentaho 8.0, the next generation of Pentaho data integration and analytics platform software, has been unveiled at the PentahoWorld 2017 user conference. The new version comes with a better preparedness for real time data deluge. Pentaho 8.0 fully supports stream data ingestion and processing using its native engine or Spark. It also now enables real-time processing with specialized steps that connect Pentaho Data Integration (PDI) to Kafka. The 8.0 version adds support for the Knox Gateway used for authenticating users to Hadoop services. It is now easier to read and write to popular big data file formats and process with Spark using Pentaho’s visual editing tools. To increase productivity across the data pipeline, Pentaho 8.0 adds new features such as granular filters for preparing data, improved repository usability and easier application auditing.

Platform upgrades and enhancements

IBM announces set of upgrades to Watson Data Platform

IBM has announced several upgrades to its Watson Data Platform, giving data professionals a stronger foundation for AI applications. The new services include Data Catalog, which creates a complete, searchable index of structured and unstructured data in a system; Data Refinery, a tool to prepare, cleanse and process data for AI purposes; and Analytics Engine, an intelligent repository for data that combines Apache Spark and Apache Hadoop, powered by IBM Cloud Object storage.

Adobe Analytics enhanced with advanced features for faster analysis, better customer intelligence

Adobe has added several advanced features into Adobe Analytics, that provide employees with intelligence curated for their roles throughout the organization. Adobe Analytics will now have Context-Aware Sessions, Audience Analytics, and new Visualizations features which make it easier for brands to combine dimensions, metrics and date range in any combination with the ability to query billions of rows of data in seconds. Also, there will be improvements to the virtual report suite for mobile teams.These new capabilities will enable increased collaboration, faster analysis and improved customer intelligence, allowing high-growth brands to derive meaningful insights faster, and with more precision.

Breakthrough innovations in AI

Cisco Spark Assistant: World’s first AI Voice Assistant for Meetings

Cisco Spark Assistant is going to be the world’s first enterprise-ready voice assistant for meetings, the company announced at Cisco Partner Summit. Cisco Spark Assistant will be available first on the Cisco Spark Room Series portfolio, including the new flagship Cisco Spark Room 70 , the company said. “During the next few years, AI meeting bots will be joining our work teams. When they do, people will be able to ditch the drudgery of meeting setup and other logistics to become more creative than ever,” said Rowan Trollope, SVP and GM at Cisco.

Using machine learning, Factual’s Engine will tell developers when to engage users

Location data provider Factual has launched Engine, a mobile software development kit (SDK) using which developers can add location data and intelligence into mobile apps. Engine uses machine learning to help developers know the right time to engage users. The AI considers business operating hours, device usage patterns, speed and direction of travel to determine the specific circumstance of a user. “The bar for smart and intelligent apps is rising exponentially, and developers demand solutions that help them provide personalized, effortless experiences to end users,” said Gil Elbaz, founder and CEO of Factual. “Engine is uniquely able to understand a device’s exact location and movement, and using that location intelligence, design customized outcomes for users.” Engine is available for both Android and iOS.


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