This comprehensive approach ensures a cohesive data strategy that caters to the specific needs of model development, business intelligence, and campaign management, while maintaining consistency and reliability across the board.
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- Data must be structured in a cubical format, summarized at fixed dimension levels for most of the dashboards.
- Well-defined functions should be established to utilize cubical data accurately across various levels.
- The strategy should account for varying BI requirements, from account-level to transaction-level records, prioritizing the most frequent to less frequent BI needs.
🚀 Campaign Management Perspective:
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- Both account-level and transaction-level data are essential for campaign management.
- Data storage considerations include month-end and cycle-level data.
🔧 Common Strategies Across All Perspectives:
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- Define storage strategies for recent, historical, and archival data.
- Establish protocols for regular automated data quality checks.
- Implement triggers to preemptively address errors or issues in subsequent processes.
- Design a careful hierarchy for data granularity, ensuring seamless reconciliation and access across customer, account, and card levels in scenarios like credit card business.
This comprehensive approach ensures a cohesive data strategy that caters to the specific needs of model development, business intelligence, and campaign management, while maintaining consistency and reliability across the board.
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- A clear strategy is imperative for model development, necessitating the ability to maintain account-level and monthly data.
- Procedures should be in place to generate account-level data spanning multiple months, incorporating defined methodologies such as aggregations (e.g., last, sum, average, max, min).
📊 Business Intelligence (BI) Perspective:
-
- Data must be structured in a cubical format, summarized at fixed dimension levels for most of the dashboards.
- Well-defined functions should be established to utilize cubical data accurately across various levels.
- The strategy should account for varying BI requirements, from account-level to transaction-level records, prioritizing the most frequent to less frequent BI needs.
🚀 Campaign Management Perspective:
-
- Both account-level and transaction-level data are essential for campaign management.
- Data storage considerations include month-end and cycle-level data.
🔧 Common Strategies Across All Perspectives:
-
- Define storage strategies for recent, historical, and archival data.
- Establish protocols for regular automated data quality checks.
- Implement triggers to preemptively address errors or issues in subsequent processes.
- Design a careful hierarchy for data granularity, ensuring seamless reconciliation and access across customer, account, and card levels in scenarios like credit card business.
This comprehensive approach ensures a cohesive data strategy that caters to the specific needs of model development, business intelligence, and campaign management, while maintaining consistency and reliability across the board.
