The author suggests a multi-tiered data management strategy that balances centralization and diversification. This includes understanding your data needs and adopting suitable technology solutions, embracing and optimizing the hybrid cloud, prioritizing data accessibility, and accelerating AI and other technology innovations. The article emphasizes that data management is a long-term investment and organizations should take incremental steps to address specific data needs and achieve ROI over time.
Key takeaways:
- Modern data use cases demand greater flexibility than traditional databases can offer, as they are too rigid to handle the diverse types of data and structures in the cloud environment.
- A robust data strategy should strike a balance between centralization and diversification, adopting a multi-tiered architecture that provides a unified view of data across diverse environments.
- Embracing a hybrid data strategy, which combines cloud and on-premise systems, can optimize datasets for the right environment and leverage the benefits of both worlds.
- Advancements in AI, data analytics and other technologies are revolutionizing data management, and businesses should future-proof their data infrastructure to take full advantage of these solutions.