Case Study on Optimising Database Storage Space

The Challenge

A prominent payment processing company faced a significant challenge in efficiently managing its database storage space. The rapid accumulation of data from various activities and system jobs led to bloated storage, posing risks of performance degradation and increased costs.

To address this challenge, a thorough system analysis was conducted to identify the primary sources of database storage consumption. It was crucial to pinpoint activities, system jobs, and related records that were major contributors to the storage bloat.

The Solution

The solution involved a multi-faceted approach to analyse, manage, and optimise database storage space effectively:

1. Activity Analysis: A comprehensive examination of all activities, system jobs, and associated records was undertaken to identify their impact on database storage usage. This step provided insights into which areas of the system were contributing the most to storage bloat.
2. Time-Bound Record Assessment: The company collaborated closely with the relevant stakeholders to establish time-bound record retention policies. Time-bound record details were shared to determine which data needed to be retained and for how long. This collaborative effort helped prioritise data retention based on business requirements.
3. Bulk Deletion Initiatives: An initial bulk deletion process was executed to purge unnecessary old data from the system, significantly reducing database usage. This step helped reclaim valuable storage space and improve system performance.
4. Scheduled Deletion Jobs: Monthly bulk deletion jobs were set up to ensure ongoing optimisation. These automated processes targeted data that had exceeded a two-year threshold, adhering to the established retention policies. The system maintained optimal performance and storage efficiency by regularly removing outdated data.

The Benefits

Implementing the solution above yielded several key benefits:

1. Reduced Database Storage Usage: Optimisations substantially reduced database storage consumption, alleviating concerns about storage constraints and associated costs.
2. Removal of Unnecessary Data: By systematically purging outdated records, unnecessary clutter was removed from the system. This streamlined data management and improved overall system efficiency.
3. Maintained Data Relevance: With monthly bulk deletion jobs in place, the system ensured that only relevant data within a two-year timeframe was retained, helping maintain data relevance and accuracy.
4. Enhanced Monitoring: Regular monitoring of database storage usage allowed for proactive identification of potential issues. By staying vigilant, the company could prevent the accumulation of irrelevant data and uphold optimal system performance.

In conclusion, the strategic approach to analysing and optimising Databa optimising space has empowered the company to maintain a lean and efficient data environment. By implementing time-bound record assessments, bulk deletion initiatives, and scheduled deletion jobs, the company has successfully mitigated the challenges associated with database storage bloat, ensuring a streamlined and high-performing system.