One trend that doesn’t look like it’s slowing down anytime soon is the desire for data teams to move reporting infrastructure from on-premises to one of the major cloud providers: Amazon Web Services, Microsoft Azure, or Google Cloud Platform. There are several reasons for this. Cloud implementations are more secure by default, easier to hire for, and generally more scalable. The flip
side to this is that you need a special set of skills to make the migration happen smoothly or even at all. In the following paragraphs, we’ll cover what this looks like in practice using an actual project I worked on as a case study.
“Move everything to the cloud!” was the directive from the C-Suite. Before diving into the project details, it’s important to note that any cloud migration project should have executive buy-in. Technical willingness and ability come second to alignment with leadership’s vision. In this case, there was both clear vision and alignment. My portion of the project was mostly focused on front end work. The
ETL pipelines were already established using cloud technology, however the reports were still served on-premises.
I started by researching the steps needed to translate the reports from one language to another. The core SQL queries would remain the same, however the semantic layer needed modification. Once the translation pattern was clear, the next step was to roll up my sleeves and implement the pattern one by one until each report was fully reconciled and surfaced in the cloud platform. The research process took roughly two weeks, the development process took about 6 weeks.
The organization was able to retire the on-premises server once the development process completed. The business immediately realized the value of completing this project due to added features and ease of use. This is what success looks like – Short and Sweet.
Stay tuned for Part II, which will cover Long and Bitter :).
– DQC