Ascend.io Case Studies Reading from a Single Source of Data Truth with the New York Post

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

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

Ascend.io

Technology Category	Analytics & Modeling - Big Data Analytics Platform as a Service (PaaS) - Data Management Platforms
Applicable Functions	Business Operation Sales & Marketing
Services	Cloud Planning, Design & Implementation Services Data Science Services
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. Read More
About 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. Read More
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. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Big Data Analytics

Platform as a Service (PaaS) - Data Management Platforms

Applicable Functions

Business Operation

Sales & Marketing

Services

Cloud Planning, Design & Implementation Services

Data Science Services

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.

About 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.

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.

Impact #1	Ascend Platform 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.
Impact #2	Ascend’s automation of data orchestration freed up the team to work on other business needs.

Impact #1

Ascend Platform 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.

Impact #2

Ascend’s automation of data orchestration freed up the team to work on other business needs.

Benefit #1	Went from pilot to production with Ascend in three months for a complete view of reader, advertising and other data.

Benefit #1

Went from pilot to production with Ascend in three months for a complete view of reader, advertising and other data.

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Overview

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

Operational Impact

Quantitative Benefit