Data Warehouse Requirement sheet

 

Sample Data Warehouse Requirements Sheet

Zupa Insurance Co. is seeking a comprehensive data warehouse solution ("MOI") to consolidate data from disparate sources, enable advanced analytics, and support business intelligence initiatives. This document outlines the key requirements for this project.

Note: This document outlines the basic requirements for the MOI project. Zupa Insurance Co. has a team of architects, data modelers, and other specialists who will provide guidance throughout the development process. Our primary focus is on ELT and data warehouse development concepts, with a foundational approach to modeling and architecture.

1. Introduction

Zupa Insurance Co. is seeking a comprehensive data warehouse solution ("MOI") to consolidate data from disparate sources, enable advanced analytics, and support business intelligence initiatives. This document outlines the key requirements for this project.

2. Business Objectives

The primary objectives of the MOI project are to:

• Provide a single source of truth for all critical business data.
• Improve the accuracy and consistency of reporting.
• Enable in-depth analysis of customer behavior, product performance, and operational efficiency.
• Support regulatory reporting requirements.
• Facilitate data-driven decision-making across the organization.
• Enhance customer experience through personalized insights.
• Detect and prevent fraudulent activities.
• Optimize underwriting and risk assessment processes.

3. Data Sources

The MOI will integrate data from the following sources:

• Zift Oracle CRM and Offline CRM Data:
  • Customer demographics, policy information, transaction history, and interactions.
  • Data should be integrated from both the online Oracle CRM solution and offline systems.
  • Focus on customer data related to high-selling insurance products.
• RCM PostgreSQL Database:
  • Detailed policy information, claims data, and related financial data.
• Microsoft CRM Dynamics:
  • Online transaction data, customer interactions, and marketing campaign data.
• CSV Files:
  • Encrypted files containing sensitive user information (e.g., PII). The solution must address data security and compliance requirements for handling this data.
• SCD (for Master Data Management and Identity Resolution):
  • The MOI will provide data to an existing SCD system for master data management and identity resolution. Integration with this system is a key requirement.

4. Data Warehouse Requirements

• Platform:
  • The data warehouse platform will be SQL-based. Please specify the recommended SQL platform (e.g., Microsoft SQL Server, Snowflake, etc.) and justify the choice.
• Data Modeling:
  • Design and implement a dimensional data model (star or snowflake schema) optimized for reporting and analysis.
  • The data model must support the following key entities and their relationships:
    • Customers
    • Policies (including policy types, coverage, premiums)
    • Claims (including claim status, amounts, dates, involved parties)
    • Agents/Brokers
    • Products (insurance products)
    • Transactions (payments, renewals, etc.)
  • Ensure referential integrity across all data sources to maintain data consistency and accuracy.
• ETL/ELT Processes:
  • Develop robust and scalable ETL (Extract, Transform, Load) or ELT processes using SSIS and ADF.
  • Data Extraction:
    • Extract data from all specified sources with minimal impact on source systems.
    • Implement change data capture (CDC) where appropriate to capture incremental changes.
  • Data Transformation:
    • Cleanse, transform, and standardize data to ensure consistency and quality.
    • Implement data validation and error handling mechanisms.
    • Address data quality issues, including missing values, duplicates, and inconsistencies.
    • Implement data masking and encryption for sensitive data (especially data from CSV files) to comply with data privacy regulations.
  • Data Loading:
    • Load transformed data into the data warehouse in an efficient and timely manner.
    • Support both batch and real-time data loading where necessary.
• Data Quality:
  • Implement data quality checks and validation rules at each stage of the ETL/ELT process.
  • Establish data quality metrics and monitoring mechanisms.
  • Provide mechanisms for data profiling and data cleansing.
• Performance:
  • Design the data warehouse to support high-performance querying and reporting.
  • Optimize ETL/ELT processes for performance and scalability.
  • Implement indexing, partitioning, and other performance optimization techniques.
• Scalability:
  • The data warehouse architecture should be scalable to accommodate future data growth and increasing user demand.
  • Consider cloud-based solutions for scalability and flexibility.
• Security:
  • Implement robust security measures to protect sensitive data.
  • Establish role-based access control (RBAC) to restrict data access.
  • Comply with all relevant data privacy regulations (e.g., GDPR, CCPA).
  • Implement audit trails to track data access and changes.
• Metadata Management:
  • Implement a comprehensive metadata management solution to capture and manage technical and business metadata.
  • Provide tools for data lineage tracking.

5. Business Intelligence and Reporting Requirements

• Reporting Platform:
  • The data warehouse will support reporting and analysis using Tableau. Ensure seamless integration with Tableau.
• Reporting Requirements:
  • Design and develop a suite of standard reports and dashboards to meet key business needs. Examples include:
    • Claims processing time by region, agent, and claim type.
    • Customer retention rate by policy type, demographics, and channel.
    • Fraudulent claims analysis and detection reports.
    • Policy performance and profitability analysis.
    • Customer segmentation for personalized marketing.
    • Agent/broker performance reports.
    • Underwriting risk assessment reports.
    • Financial performance reports (e.g., premiums, losses, expenses).
  • Support ad-hoc reporting and analysis capabilities.
  • Enable users to drill down into data for more detailed insights.
• Visualization:
  • Design reports and dashboards with clear and intuitive visualizations.
  • Follow best practices for data visualization.

6. Integration Requirements

• SCV Integration:
  • The MOI must integrate with Zupa Insurance Co.'s existing SCV system.
  • Provide a mechanism to transfer data to the SCV system for master data management and identity resolution.
  • Define the data transfer frequency and format.
• Source System Integration:
  • Ensure seamless integration with all specified source systems (Zift Oracle CRM, RCM PostgreSQL, Microsoft CRM Dynamics, and CSV files).
  • Address any data format or compatibility issues.

7. Automation and Monitoring Requirements

• Automation:
  • Automate all ETL/ELT processes using tools such as SSIS and ADF.
  • Schedule data refreshes and updates.
  • Automate report generation and distribution.
• Monitoring:
  • Implement comprehensive monitoring mechanisms to track data warehouse performance, data quality, and system health.
  • Establish alerts and notifications for critical issues.
  • Provide tools for monitoring ETL/ELT process execution.

8. Deliverables

The IT consultancy firm is expected to deliver the following:

• A detailed project plan with timelines and milestones.
• A comprehensive data warehouse design document, including data models, ETL/ELT specifications, and system architecture.
• A fully functional and tested data warehouse (MOI).
• All ETL/ELT code and related scripts.
• Documentation for all components of the data warehouse.
• Training for Zupa Insurance Co. staff on data warehouse usage and maintenance.
• Ongoing support and maintenance services.

9. Acceptance Criteria

The data warehouse solution will be accepted based on the following criteria:

• Successful completion of all functional and technical requirements.
• Successful integration with all specified source systems and the SCD system.
• Acceptance testing by Zupa Insurance Co. business users.
• Delivery of all required documentation and training materials.
• Adherence to project timelines and budget.

10. Proposal Requirements

The IT consultancy firm is requested to submit a proposal that includes the following:

• Company overview and experience.
• Proposed solution architecture and technology stack.
• Project plan, including timelines, milestones, and resource allocation.
• Cost estimate, including development, implementation, and ongoing support costs.
• Team qualifications and experience.
• References from similar projects.
• Approach to data security and compliance.
• Approach to data quality and governance.

11. Contact Information

Zupa Insurance Co.