In the world of data and business, your choice of a data warehousing methodology can significantly impact your organisation’s ability to harness data for strategic decision-making.

What are the “hard problems” that your team is dealing with? First, you may ask “what are hard problems?”. Scott Ambler – agile data coach and consulting methodologist – outlined exactly what he means.

Data warehouses and data lakes are two of the most used tools for storing and managing large volumes of data used by data engineers, business analysts, and more. Both have their advantages, but each performs a different role.

While economic forecasts for 2023 are focusing on a major slowdown in economic activity, all predictions for the data warehousing industry show the market continues to expand.

This is the second part of an interview by our Andrew Griffin, who spoke to Barry about his experiences, and his thoughts about the future of the industry.

During my time as a Data Engineer, I have observed first-hand the process of testing Data Warehouses, communicating the results between teams and how this presents new and interesting challenges to overcome.

Most senior executives today recognise the need to drive more value out of their data. The question for systems architects and data engineers is how to deliver what the business requires. The traditional stereotyped view of a Data Warehouse as a repository tacked onto the side of the IT architecture to allow business reporting and analytics is way out of date.

Which business cases succeed in today’s hard-nosed business environment? Business cases for Business Intelligence and Data Warehouses have always been hard to quantify.