A few years ago, I had a beer with a former classmate who happened to be one of the first Hadoop engineers. He complained about his company having twenty-three Hadoop clusters that were functioning perfectly, but no one knew how to use them. These clusters remained unused for years and were eventually forgotten.
Data experts are often asked by clients to build data warehouses, leading to immediate discussions about technology, cloud, and tools. Although the scale of the data warehouse may make technology challenging, it is not the most significant factor in success. The key to success is having a clear goal. Without having clarity on what you want to achieve, it becomes difficult to determine the data that you want to include once the project is complete. It is imperative to think about the hidden patterns you want to uncover before taking any action.
A decade back, building a data warehouse needed a significant investment in specialized hardware and software tools. However, over the years, all major cloud vendors have started offering scalable, pay-for-what-you-use platforms such as Google BigQuery, AWS RedShift, Azure Synapse, Snowflake, and Databricks. These allow deploying a data warehouse without investing in hardware or software tools.
If you want to build a data warehouse, start by thinking about your end goals and the insights you wish to uncover. Once you have a clear vision in mind, you can start thinking about the technology, cloud, and tools that will help you achieve your objective. Bear in mind that building a data warehouse is not just about technology, but also about having a clear purpose and goal in mind. By focusing on your endgame, you can build a data warehouse that provides significant value.