What is the Fuss About CDP, DMP, Data Lake and Data Warehouse?
Customer Data Platforms (CDP), Data Management Platforms (DMP), Data Lake and Data Warehouse are not interchangeable terms. Lakes, warehouses and platforms – you often hear these terms attached with data. And although they all have a common association with the word ‘data’, each one of them has a different purpose, serving various departments within an […]
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Customer Data Platforms (CDP), Data Management Platforms (DMP), Data Lake and Data Warehouse are not interchangeable terms.
Lakes, warehouses and platforms – you often hear these terms attached with data. And although they all have a common association with the word ‘data’, each one of them has a different purpose, serving various departments within an organisation.
Organisations are now handling a vast amount of data from multiple sources and platforms, which require data storage and analytics solutions to turn it into actionable insights.
Let us understand what each of these Data Management terms truly means.
Customer Data Platforms (CDP)
In today’s business world, the challenge posed by complex customer relationships has encouraged brands to look at CDPs to help unify customer data and provide thoughtful customer experiences.
According to David Raab, Founder of the CDP Institute, “A Customer Data Platform is packaged software that creates a persistent, unified customer database that is accessible to other systems.”
In an interview with MarTech Vibe, he further stated – “Building a unified customer database is the core purpose of the CDP. It addresses fragmentation by bringing together data from multiple sources into a single system, by storing that data so identifiers that change over time can still be linked to the underlying customer, and by enabling other systems to access a consistent central database rather than each system building its own partial customer view.”
CDPs excel at collecting data on a customer’s journey, cleaning it and putting it together, offering marketers valuable customer insights to orchestrate experiences across touchpoints intelligently.
A CDP collects and stores all 1st, 2nd and 3rd party data.
Data Management Platforms (DMP)
A DMP collects anonymous web and digital data, comprehending information about prospects psychographics and demographics.
It is a unifying platform that collects anonymous data, stores, organises and interprets customer segment and ad campaign data from a variety of sources.
The USP of a DMP is the ability to understand customers demographics and psychographics.
DMPs do not provide a unified view of the customer and cannot accept 1st party data and work almost exclusively with anonymous information such as cookies, devices, IP addresses.
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They are designed to build targets for advertising and customer acquisition while dealing with known and unknown customers. DMPs are most frequently used by publishers, agencies and ad networks to enhance targeted digital advertising.
Data Lake
Data Lakes store large sets of unstructured data. It is not packaged, ready to use, and collects customer data from various external sources through several channels.
A Data Lake holds data in its rawest form – not processed or analysed and in various formats.
It accepts data from all sources, supporting all data types and the schema (the organisation of data as a blueprint of how the database is constructed) can be applied after the data is stored.
A Data Lake provides more agility as it lacks structure and is relatively easy to make changes to queries or models.
If mismanaged, they can turn into vast amounts of uncontrolled data which is often useless. Data Scientists are typically the ones who access the Data Lake.
Data Warehouse
A Data Warehouse is a repository that stores data in a structured manner with entry criteria built for the data’s entry point based on data models that organisations want to examine.
These are specific organisational requirements and is controlled.
This results in a well-structured set of data and the schemas are defined before the data is stored. A lot of planning goes in before building a Data Warehouse as it has distinct purposes.
It provides less agility as several business processes are tied to it. Since Data Warehouses are far more structured, they offer a sense of security in terms of the vulnerability of the data.
Namrata Balwani, Digital and Customer Experience Consultant explains, “A CDP is like having friends in your home. You know exactly who they are (customers) and you’ve interacted with them for years, so you know what they like and you plan your party accordingly.
A DMP is like walking into a bar and chatting up with people you’ve never met (prospects) so you may not know their name or anything about them. Some of them will become your friends (customers) and they move from the DMP to the CDP. Some you might just wave hi to the next time you are at the same bar so they stay in the DMP (remarketing).
A Data Lake is the bar. It’s a container and cannot tell you anything meaningful by itself.”
