NYP Case Study Blog

Reading from a Single Source of Data Truth with the New York Post

Understanding advertising information as well as how readers interact with digital content is crucial to the growth and success of the New York Post and its associated online properties. Already hyper-focused on building robust data pipelines to feed insight and analytics teams, the upcoming crackdown from Google on third-party cookie data in the Chrome browser accelerated the need to drive more data-driven personalization and engagement across the New York Post sites.

The team at the New York Post needed to quickly create a scalable way to build data pipelines that power critical insights and changes for how readers and subscribers interact with digital content.

As the Ascend Unified Data Engineering Platform was introduced to the team, which is composed of software engineers and project managers, they quickly realized that deploying an ETL platform using Ascend would dramatically accelerate their time to market and ability to continuously deliver new data streams.

 

“With the breadth and speed we require, Ascend meets the demands. We no longer look at individual data sources to pull into Ascend, we look at our entire enterprise—customer-facing and internal—and decide how to pull that into Ascend and then feed it into other systems for visualizations. Ascend is the gateway that processes all our data.”

 

Ariscielle Novicio, SVP & Head of Technology at the New York Post

The ability to rapidly iterate on ETL enabled the New York Post team to focus on the higher-level work that provided value across many business units without the need to manually transform dozens—if not hundreds—of distinct data sources.

Read more in the case study to learn how the New York Post went from pilot to production with Ascend in three months for a complete view of reader, advertising, and other data.

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