Data Warehouse and Business Intelligence (BI) solution

1. Data Warehouse Architecture & Modernization Design and implement a modern, AWS-native data warehouse and lakehouse architecture.

Scope Includes:

• Architecture design aligned to AWS Well-Architected Analytics best practices
• Centralized data lake using Amazon S3 with Bronze, Silver, and Gold zones
• Curated enterprise data warehouse using Amazon Redshift or Redshift Serverless
• Schema design using dimensional or hybrid modeling patterns

Outcomes:

• Consolidated, trusted enterprise data foundation
• High-performance analytics optimized for BI workloads
• Scalable architecture designed for future growth

2. Data Ingestion & Integration Pipelines Implement automated, reliable ingestion pipelines from operational and third-party systems.

Scope Includes:

• Batch and incremental ingestion using AWS DMS, AppFlow, Kinesis, and APIs
• Change Data Capture (CDC) for supported databases
• Secure ingestion with IAM-based access and encryption
• Error handling, retry logic, and pipeline monitoring

Outcomes:

• Reliable, repeatable data ingestion with reduced manual effort
• Near-real-time or scheduled data availability for analytics
• Improved visibility into pipeline health and data freshness

3. ETL / ELT Transformation & Data Quality Develop standardized transformation pipelines to produce analytics-ready datasets.

Scope Includes:

• Data cleansing, normalization, enrichment, and validation using AWS Glue
• Business rule implementation and data standardization
• Partitioning and performance optimization for analytics queries
• Data quality checks and reconciliation against source systems

Outcomes:

• Consistent, analytics-ready datasets
• Improved data accuracy and trust
• Reduced reporting discrepancies across teams

4. Business Intelligence & Analytics Enablement Enable interactive dashboards and self-service analytics for business users.

Scope Includes:

• Amazon QuickSight dataset modeling and dashboard development
• Department-level dashboards for finance, operations, sales, marketing, and leadership
• Row-level and column-level security configuration
• Scheduled refreshes and performance optimization

Outcomes:

• Real-time visibility into business performance
• Secure, governed self-service analytics
• Faster decision-making across the organization

5. Data Governance, Security & Optimization Establish governance, monitoring, and optimization for long-term operational success.

Scope Includes:

• Metadata cataloging and lineage using AWS Glue Data Catalog
• Encryption and access controls using IAM and AWS KMS
• Monitoring and logging using CloudWatch and CloudTrail
• Performance and cost optimization for Glue, Redshift, and QuickSight

Outcomes:

• Secure and compliant analytics environment
• Improved observability and operational control
• Optimized performance and cloud cost efficiency