Reading from a Single Source of Data Truth with the New York Post
Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- Ascend Unified Data Engineering Platform
Tech Stack
- Amazon Web Services
- Google Cloud
- BigQuery
- Vidora
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Digital Expertise
Technology Category
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Functions
- Business Operation
- Sales & Marketing
Services
- Cloud Planning, Design & Implementation Services
- Data Science Services
About The Customer
The New York Post is a highly data-driven publisher that relies on fast access to accurate data. 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. The company is hyper-focused on building robust data pipelines to feed insight and analytics teams. Ariscielle Novicio, SVP & head of technology for the New York Post, and her team needed to focus their efforts on quickly creating a scalable way to build data pipelines that power critical insights and changes for how readers and subscribers interact with digital content.
The Challenge
The New York Post, a highly data-driven publisher, was faced with the challenge of accelerating time-to-market for internal reporting, financial, and other data initiatives. 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 required a faster way to ingest, aggregate, transform, and write out a variety of critical new data feeds in order to meet various business demands and requirements.
The Solution
The Ascend Unified Data Engineering Platform was introduced to the New York Post 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. In order to meet the upcoming deadlines for reporting dashboards, the team at the New York Post needed a platform that could bridge systems including Amazon Web Services, Google Cloud, BigQuery, Vidora for AI and machine learning workloads, and, importantly, the internal Customer Data Platform. In addition to accelerating time-to-market for initiatives, the New York Post team needed to deliver a single source of truth for data across the enterprise, and the ETLT capabilities of the Ascend Platform helped the team deliver on that need.
Operational Impact
Quantitative Benefit
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