Zeotap June 2022 Update: New Features

The month of June brings new exciting features: a new do-it-yourself capability within our Data Catalogue, a new data ingestion method – SFTP, a new real-time estimator of an audience size within a segment and a new platform integration with Marketo. I know, all that in a month! We hope you enjoy finding out more… Continue reading Zeotap June 2022 Update: New Features

Zeotap CDP May 2022 Update: New Key Features

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The month of May brings with it an exciting new feature: Source Ingestion Analytics, which provides complete visibility on ingested data. This helps clients understand the status of ingested data sources and to take corrective action in a timely manner if necessary.  We have also gone live with new integrations: Android SDK for mobile app… Continue reading Zeotap CDP May 2022 Update: New Key Features

Zeotap April 2022 Update: New Key Features

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It’s been a bumper month for updates! Among many new releases, we’ve introduced a best-in-market Raw Personal Data Encryption feature, which delivers the highest security for data in transit, and new integrations for Salesforce Marketing Cloud and LinkedIn. Enjoy the read and make sure to subscribe to our newsletter for future updates! Feature spotlight  Introducing… Continue reading Zeotap April 2022 Update: New Key Features

Zeotap Launches Predictive Audiences to Empower Marketers With Machine Learning

New functionality allows users of Zeotap’s Customer Data Platform to create and activate machine-learned segments without needing Data Science expertise  Wednesday, May 12, 2021 – Zeotap, the leading Customer Data Platform, has today announced the launch of Predictive Audiences as part of its award-winning Customer Data Platform (CDP). Designed to help marketing users increase the… Continue reading Zeotap Launches Predictive Audiences to Empower Marketers With Machine Learning

Asynchronous Spark Jobs With Apache Livy – A Comprehensive Guide

Asynchronous Spark jobs using Apache Livy - A Primer

At zeotap, a large amount of structured and unstructured data from data partners is transformed and converted to easily queryable, standardized data sets, which are fanned out to a variety of destinations. For this processing, the transformation jobs use Apache Spark as the distributed computing framework, with a fair share of them being batch processing… Continue reading Asynchronous Spark Jobs With Apache Livy – A Comprehensive Guide