It is no secret that analytics and planning projects are based on data. Typically projects involve wrangling some historical datasets, each with their own peculiarities, and then adding in some projection or prediction. Because data is essential, it is also a common stumbling block as business users consider beginning ...
In my previous post, Data Warehouse versus Data Lake – The What and the Why (Part one), I discussed the differences between data lakes and data warehouses and when you would use each pattern. In this post I’ll discuss, at a high level, an iterative process for building a data warehouse.
The AI revolution is here, and the finance teams that adapt their operating model will win. The best time to start was yesterday; the second best is today.
