Condé Nast's Journey Mapping with Fivetran: A Case Study
Technology Category
- Platform as a Service (PaaS) - Application Development Platforms
- Robots - Parallel Robots
Applicable Industries
- Buildings
- Consumer Goods
Applicable Functions
- Sales & Marketing
Use Cases
- Behavior & Emotion Tracking
- Livestock Monitoring
Services
- System Integration
About The Customer
Condé Nast is a global media leader with titles such as Vogue, GQ, The New Yorker, Vanity Fair, Wired, Architectural Digest (AD), and Bon Appétit. The company's 37 brands reach 72 million consumers in print, 442 million in digital, and 452 million across social platforms. Hundreds of millions of people around the world consume Condé Nast’s content across the company’s digital assets, generating trillions of data points and potential insights into their wants and needs. The company aims to deliver powerful, personalized and relevant experiences that inform and delight, while opening up new, sustainable revenue streams.
The Challenge
Condé Nast, a global media leader with 37 brands reaching millions of consumers, was faced with the challenge of managing and monetizing trillions of data points generated from its digital assets. The company lacked a central mechanism for managing and maintaining data integration sources, making data not readily available to consumers downstream. The demand to integrate more sources globally continued to grow, and pulling data into the data lake with custom scripts was cost prohibitive. Each marketing technology platform had its own API, data structure and other properties that required its own custom script. Creating the connectors on the fly and managing them on an ongoing basis wasn’t scalable, posing a significant challenge to the company.
The Solution
To address this challenge, Condé Nast implemented Fivetran’s data integration solution. This solution was chosen for its intuitive controls, vast connector library and white-glove service. Fivetran automatically pulls data from dozens of scattered sources into Delta Lake, where it’s transformed and segmented into three layers – Gold, Silver and Bronze – for analysis in Qlik, Mode, and Databricks SQLA. This segmentation allows the team to maintain changes from the source via Fivetran and what they expose to the business. When a new source needs connecting, the team simply enters credentials in the Fivetran dashboard, and the data starts to flow. This solution has allowed Condé Nast to automate the data migration from first-, second- and third- party sources into the company’s lakehouse, Delta Lake on Databricks.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
.png)
Case Study
Improving Vending Machine Profitability with the Internet of Things (IoT)
The vending industry is undergoing a sea change, taking advantage of new technologies to go beyond just delivering snacks to creating a new retail location. Intelligent vending machines can be found in many public locations as well as company facilities, selling different types of goods and services, including even computer accessories, gold bars, tickets, and office supplies. With increasing sophistication, they may also provide time- and location-based data pertaining to sales, inventory, and customer preferences. But at the end of the day, vending machine operators know greater profitability is driven by higher sales and lower operating costs.
Case Study
Energy Saving & Power Monitoring System
Recently a university in Taiwan was experiencing dramatic power usage increases due to its growing number of campus buildings and students. Aiming to analyze their power consumption and increase their power efficiency across 52 buildings, the university wanted to build a power management system utilizing web-based hardware and software. With these goals in mind, they contacted Advantech to help them develop their system and provide them with the means to save energy in the years to come.
Case Study
Intelligent Building Automation System and Energy Saving Solution
One of the most difficult problems facing the world is conserving energy in buildings. However, it is not easy to have a cost-effective solution to reduce energy usage in a building. One solution for saving energy is to implement an intelligent building automation system (BAS) which can be controlled according to its schedule. In Indonesia a large university with a five floor building and 22 classrooms wanted to save the amount of energy being used.
Case Study
Powering Smart Home Automation solutions with IoT for Energy conservation
Many industry leaders that offer Smart Energy Management products & solutions face challenges including:How to build a scalable platform that can automatically scale-up to on-board ‘n’ number of Smart home devicesData security, solution availability, and reliability are the other critical factors to deal withHow to create a robust common IoT platform that handles any kind of smart devicesHow to enable data management capabilities that would help in intelligent decision-making
