CDP vendor Evergage launched a new Data Warehousing Solution.
To quote from their press release:
Using the Data Warehouse solution, companies can give their business analysts comprehensive access to the rich, unified customer and prospect data – collected, synthesized and housed in Evergage – to power in-depth analyses and drive informed business decisions.
Wait a second...
Don't most CDPs already provide access to their data from external systems?
That's true. Most CDPs do provide some level of access to the underlying data, mostly via APIs or by way of data and segment exports. However this is a bit more than that. Here, Evergage sends over raw data to another data warehouse, where your business analysts can connect their tools (e.g., Tableau) and carry out their analysis, outside of Evergage.
Previously, the vendor had released "Data Science Workbench" in October 2018, which shares some underlying technologies with this Data Warehouse. In that case, Evergage moves its data to another dedicated cluster which has several data science tools (e.g., the popular Jupyter notebook environment) preconfigured. Your data analysts can use this cluster to carry out advanced analytics and run their own data science models. They can also use existing models available in the catalog and do their own analysis. The results of these analytics can then be brought back into Evergage (e.g., as attributes in a customer profile) for further action.
What are other vendors doing?
For RSG's ongoing research into CDP vendor strengths and weaknesses, we've found other vendors have also released or are working on similar offerings that allow you to run your own data science models. You will hear about a data science workbench or AI workbench or simply "workbench" from many vendors in future.
The larger story here is that marketing and CX teams are looking for data warehouse and/or data lake-type services, but may not have recourse to that tooling internally. Note the Evergage release citing the role of "business analysts" (presumably working in marketing or customer operations) rather than "data analysts."
Ideally your analytics stack will not get too fragmented, but I see this as another marker of heavily expanding demand for customer-oriented reporting and analysis — just one of the nine business scenarios RSG uses to evaluate CDP vendors, but surely an important one...