Here's how you can strategically plan in Database Engineering using your knowledge of database architecture.

During database designing, it's important to understanding requirements whether you need a performant dB or a structured dB or an unstructured dB. Along with this it is also important to decide on normalized the tables should be, exceed the limit and you price by lengthy, time consuming and complex queries. To get your select queries working fine, indexing on the right column should also be decided. Also that the DB should be designed such that the future needs are also met. Understanding the requirement is the most important state as this answers most of your questions and helps you design a better and more application specific db.

Choosing the right tech for your project is also important. Like said going for a relational dB or NoSql dB depends totally on the need as well as the expertise of the team. One thing that I would like to add here is that going for new Advanced tech should always be a priority no matter the learning curve. I did work with a team wherein new technology was introduced and the team adapted to it quiet good, learning curve is something that a techie will always look for and if you get the opportunity go for it. Definitely the team won't let you down.

People and teams tend to gravitate towards the product they have experience with. However, that may not always be the optimal choice. Throughout my career, I have made people stop, think and justify their DB choice not just based on the current requirements but whether it makes sense for the foreseeable future, and outcomes have been fructuous. They had to learn a new technology many times, but thats fine because: - This one decision significantly impact the complexity of the systems as well as associated costs eg infrastructure, maintenance, and potentially migration. - Learning a new database technology is not cost prohibitive - Continuously learning new stuff is an implicit requirement and necessity to stay relevant in our profession

Schema designing is yet another step in getting a more robust, performance efficient and highly volatile dB. The right normalization, the table relations helps in getting a dB which can be updated according to future needs and also a dB which has less complexity and efficient performance.

Adding MFA to your database access controls further strengthens security by requiring users to verify their identity through multiple methods, such as a password and a time-sensitive code sent to their mobile device. This reduces the risk of unauthorized access even if credentials are compromised.

Connection pooling helps manage the number of database connections efficiently by reusing active connections instead of creating new ones for every request. This reduces the overhead on the database server, improves response times, and enhances overall performance, especially in high-traffic environments.

Besides all this, I would add archiving old data to storage as an important factor in optimizing performance. This reduced total data to go through.

Auto-scaling allows your database infrastructure to automatically adjust its capacity based on current demand. By configuring auto-scaling policies, you can ensure that your database resources are dynamically allocated during peak times and scaled down during low-traffic periods, optimizing both performance and cost-efficiency.