Find out the difference between a CDP and a data warehouse and how to apply these technologies to create architecture that best reflects your business objectives.
Brand & Marketing Lead
A Customer Data Platform (CDP) and a data warehouse are all concepts related to data management, and all of these systems are used to store data and enable advanced analytics. However, each concept has distinct characteristics, serves different purposes, and caters to specific organizational data management needs. In short, they are not interchangeable but can be used together to provide a comprehensive data ecosystem.
Let’s break down each concept and identify the differences between customer data platforms (CDP) and data warehouses and how they can complement each other.
A data warehouse is a centralized repository for storing, organizing, and analyzing large volumes of structured data from various sources within an organization (e.g., databases, CRM systems, ERP systems, and other external data feeds). It supports historical reporting, business intelligence, and data analysis. Data warehouses are typically characterized by their ability to efficiently handle structured data, enabling complex queries and transformations. They follow a schema-on-write approach, where data is structured and organized before being ingested into the warehouse.
A typical data warehouse architecture consists of the following components:
A customer data platform (CDP) is designed to collect, store, consolidate, and manage customer data from various online & offline sources, such as websites, mobile apps, CRM systems, etc., to create unified and comprehensive customer profiles. CDPs focus on individual user-level data and provide a 360-degree view of customer interactions, behaviors, and preferences across multiple touchpoints. This information allows businesses to:
Generally, a CDP would support data integration, audience segmentation, and activation across marketing channels. A good full-stack CDP would also include data management features such as ETL/Reverse ETL (Extract, Transform, Load) for schemaless ingestion of raw data, which allows it to ingest and harmonize data on the fly without requiring extensive data modeling upfront, saving time and resources for the client organization.
A Customer Data Platform (CDP) architecture typically comprises three key components:
Unleash the full potential of your customer data. Let’s talk!
Eli joined Meiro to take care of digital and content marketing satisfying her passion for communications and interest in MarTech and CX. At the same time she studies psychology, loves hiking, and is a proud plant (and cat) mama.