Reading from a Single Source of Data Truth with the New York Post
公司规模
1,000+
地区
- America
国家
- United States
产品
- Ascend Unified Data Engineering Platform
技术栈
- Amazon Web Services
- Google Cloud
- BigQuery
- Vidora
实施规模
- Enterprise-wide Deployment
影响指标
- Digital Expertise
- Productivity Improvements
技术
- 分析与建模 - 大数据分析
- 平台即服务 (PaaS) - 数据管理平台
适用功能
- 商业运营
- 销售与市场营销
服务
- 云规划/设计/实施服务
- 数据科学服务
关于客户
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.
挑战
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.
解决方案
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.
运营影响
数量效益
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