Study the current and potential long term business needs. Assess the existing infrastructure, identify performance bottlenecks, and understand the data growth trajectory. Engage stakeholders; to ensure alignment between technical changes and business objectives. Next, explore potential cloud-native solutions focus on scalability and elasticity. Consult with industry experts if dealing with critical workloads. Run a pilot project to testing the feasibility of promising solutions in a controlled environment, evaluate performance, cost, and ease of migration. Based on pilot results, select the solution that aligns with long-term goals. Use a phased transition approach to minimize disruption, accommodate future needs.

For Seek expert advice, I often consult the Wecommit community. There are database experts who can help me assess the current state of the database and identify where the gaps are.

I have not done anything with databases in quite some time. Nothing in my current profile suggests that I am an any kind of expert in databases, yet LinkedIn keeps on asking me to contribute to database-related topics. Something is wrong with their model. Quite annoying.

Understand the data growth trend , business long term road map . Evaluate the existing infrastructure, technology and required skills . Understand the business objectives vs technology needs . Explore the AI and cloud approach align to organizations vision. Consult with industry SME . Plan and execute pilots with high volume analytics . Design phase based poc approach to review and test . Finalize the approach and finalize the solution design from learning during poc approach . Plan for solution implementation.

- Assess Current Architecture: Conduct a thorough analysis of the existing database structure. Identify bottlenecks, performance issues, and areas where scalability is limited. - Engage Stakeholders: Collaborate with key stakeholders—development teams, operations, and management—to understand their needs and gather insights on pain points. - Define Requirements: Based on feedback, define the requirements for a more scalable and efficient database system. - Explore Solutions: Research and evaluate different database technologies (e.g., SQL vs. NoSQL, cloud-based solutions) that align with the identified needs. Consider options like database sharding, replication, or even a complete migration to a new system.