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ADR 016: Business Intelligence Solution Implementation

Date:

2024-09-30

Status:

Accepted

Context:

The organization requires a Business Intelligence (BI) solution to analyze data, generate insights, and create reports for various stakeholders. The solution must be scalable, user-friendly, and capable of integrating with existing data sources.

Key factors considered:

  • Ease of Use: The solution should allow non-technical users to easily create reports and dashboards.
  • Integration: The BI tool must seamlessly integrate with AWS services and data sources.
  • Scalability: It must handle varying amounts of data as the organization grows.
  • Cost-Effectiveness: The solution should fit within budget constraints.

Decision

We will use AWS QuickSight as the BI solution for our data visualization and reporting needs.

Considered Options:

AWS QuickSight

  • Pros:
    • Fully managed and serverless, reducing operational overhead.
    • Easy integration with AWS data sources (e.g., S3, RDS, Redshift).
    • Supports interactive dashboards and visualizations.
    • Offers a pay-per-session pricing model, making it cost-effective for variable usage.
  • Cons:
    • Limited customization options compared to some other BI tools.
    • May require additional setup for complex data transformations.

Tableau

  • Pros:
    • Highly customizable and offers powerful data visualization capabilities.
    • Strong community and support.
  • Cons:
    • Higher cost, especially for licensing.
    • More complex setup and maintenance compared to QuickSight.

Power BI

  • Pros:
    • Good integration with Microsoft products.
    • Robust features for data modeling and visualization.
  • Cons:
    • Requires additional licensing for enterprise features.
    • Integration with AWS data sources can be cumbersome.

Looker

  • Pros:
    • Strong data modeling capabilities and collaboration features.
  • Cons:
    • Higher operational costs.
    • More complex deployment and maintenance.

Decision Rationale

We chose AWS QuickSight because it effectively meets our requirements:

  • Ease of Use: QuickSight's intuitive interface allows non-technical users to create dashboards and reports without extensive training.
  • Seamless Integration: It integrates well with our existing AWS ecosystem, allowing for straightforward access to data stored in AWS services.
  • Scalability and Performance: As a serverless solution, QuickSight automatically scales with our data, ensuring performance remains high as usage grows.
  • Cost-Effective: The pay-per-session pricing model makes it suitable for our budget, especially considering variable user engagement.

Consequences

  • Limited Customization: While QuickSight is user-friendly, it may not provide the same level of customization as other tools. We will need to balance user needs with available features.
  • Data Preparation: Some complex data preparation tasks may require additional tools or services, which could add to the overall solution complexity.

Next Steps

  1. Set up AWS QuickSight and connect it to our data sources.
  2. Train users on how to create and manage dashboards and reports.
  3. Develop a plan for ongoing data governance and management to ensure data quality and accessibility.