Operational data warehouses came into existence in most enterprises as a way to consolidate data across the enterprise and apply some standards, controls and consistency to the data being stored in these systems. While operational data warehouses have come a long way towards helping organizations centralize data, control data access and enforce a data governance policy to hopefully maintain some degree of master data management, these systems tend to be too restrictive and too slow in their ability to adapt and enhance for most marketing departments.
The primary difference between an operational data warehouse and a marketing database is that a typical operational data warehouse only consists of customer data, transactions and financials necessary to support operational activities, whereas a marketing database is typically implemented as a data mart consisting of both customer and prospect data, transactional data, as well as marketing campaign & program data, response data, and any other data such as behavioral, demographic or credit data, which is frequently used to support the ongoing and quickly changing needs of the marketing department. While most marketing databases receive customer data and transactional data from their corresponding operation data warehouse brethren, that’s where the similarities stop. Marketing databases are designed from the ground up to be flexible enough to receive any number of input data sources, with customer and transactional data being just two of the data sources possible.
While operational data warehouse projects are typically embarked upon as a result of a comprehensive data consolidation initiative and then deployed by the internal IT team after buy in and consensus about included attributes from all internal groups who plan on using the data warehouse. Operational data warehouse builds are massive undertakings and sometimes take years to fully design and deploy.
Marketing Databases are designed by teams specializing in these types of systems and who have an in-depth knowledge of BigData challenges as applied to the needs of marketing users including data hygiene issues, postal standardization and data consolidation methods such as house-holding using complex name and address matching logic.
Operational data warehouses simply don’t make sense for marketing because they take the one-size-fits-all approach, which just does not bode well for modern marketing departments. Today’s fast paced and ever changing landscape requires marketers to not only be more agile but also requires data systems, like a marketing database, which can be faster to deploy, more cost effective and more flexible in order to grow and adapt to new data sources quickly and easily without a major overhaul or non-marketing department involvement.