Our corporate background was in a company with one of the most complex data warehouses in the world. Legacy data warehouses were built on top of one another, each with an initial scope to be the ‘source of truth’ but ultimately finding it too complex and expensive to implement.
Instead, build was made on a compromise of requirements and provided piecemeal reporting that fed into an ever-growing web of manual analytical processes for end users to achieve their outcomes.
I was lucky, in that my early days as a customer service consultant inadvertently afforded me access to the source feeds across dozens of key applications. Having no technical literacy at the time, my only frame of reference was the end business purpose of the data I was looking at.
Seeking technical mentorship, I slowly started translating my business knowledge into data modelling and development. There was clear transformational potential in having complete, holistic datasets that represented what was really going on in the systems day to day.