📊 Assess Data Necessity: Evaluate which data is essential to retain and identify archival or deletion opportunities, ensuring only critical data consumes storage. ☁️ Utilize Scalable Cloud Storage: Opt for cloud solutions with pay-as-you-go models, allowing storage to scale with needs without hefty upfront costs, keeping expenses aligned with growth. 📉 Implement Data Compression: Apply compression techniques to reduce storage space requirements, maximizing efficiency and lowering costs without sacrificing data integrity. 🔄 Automate Data Lifecycle Management: Set up automated policies for data archiving and deletion, helping manage storage use effectively and stay within budget.

The "data temperature" and "Usage pattern" are concepts that it will help you to understand how data is usage from clients like internal & external systems and users. With this knowledge you can detect what activities the client is doing, how data is used and what storage generate the cost based on these previous components; so you can adjust your storage like add near-line storage to support better the main storage or give to the client alternative solution to support their need while reduce or hold the cost. A general best practices: - Use the right data storage to support the use cases. - Use right data compresion on table. - Move or delete data won't use on the storage based on the data usage lifecycle.

I will have a governance mechanism by design to monitor the frequency of access of the data and then the statutory requirement for retention of the data and then using a function of these two parameters I will build a data retention policy. Also there are low cost storage solutions with a balancing act of retrieval time if it is not critical for business then maybe I will leverage that option too.

Build a decoupled architecture like open data lake house where compute and storage are separated, this will minimize the cost. 80% of the data is cold and 20% is hot. Moreover, you can compress the cold data with highest compression and store on HDD storage and the Hot data should be stored in SSD drive for faster read and write

In my experience, a balanced approach to managing data storage on a budget starts with rigorous data classification. By categorizing data based on its value and usage, it's easier to prioritize storage solutions. For frequently accessed, high-priority data, consider fast, scalable cloud options, while archival data can be shifted to cost-effective, long-term storage. Additionally, automating the cleanup of redundant or obsolete files can reduce storage bloat significantly. Regular audits keep the system optimized, ensuring storage expenses align with business needs.

Managing data storage on a tight budget requires a strategic approach. Start by assessing your actual storage needs—determine which data is essential for quick access and what can be archived or safely deleted to free up space. Scalable cloud storage solutions offer a cost-effective option, allowing you to pay for what you use and scale as your storage needs grow, avoiding large upfront costs. Lastly, consider data compression and tiered storage strategies to optimize resources, ensuring budget-friendly, efficient storage.