About CGIAR
CGIAR is a global research organization focused on advancing agriculture, sustainability and food systems across multiple regions. With diverse programs and stakeholders, the organization relies heavily on digital platforms to monitor engagement, evaluate campaign performance and measure impact.
As data volume and reporting needs increased, insights became fragmented across systems. CGIAR required a centralized analytics foundation that could unify data, standardize metrics and support consistent, enterprise-level decision making.
Key Business Challenges
As CGIAR expanded its digital initiatives, reporting complexity increased. Critical insights were distributed across platforms, including Google Analytics 4, Google Search Console, Sprout Social, SplashThat, Meltwater and Campaign Studio. While each system provided valuable data, there was no centralized analytics environment to bring these insights together.
This led to several operational challenges:
- Data is spread across multiple independent tools
- No unified view of cross-platform performance
- Manual report compilation by different stakeholders
- Delays in executive level reporting
- Inconsistent KPI definitions across teams
- Limited ability to compare and analyze metrics collectively
Without structured data integration and standardized reporting, leadership lacked timely, consolidated insights. CGIAR required a centralized and automated analytics foundation to restore clarity, alignment and confidence in decision making.
What CGIAR Set Out to Achieve?
The objective was to transition CGIAR from fragmented, platform-based reporting to a centralized and reliable analytics environment that simplified access to insights and reduced manual effort.
- Centralize reporting into a single source of truth across all platforms
- Standardize KPI definitions to ensure consistent performance measurement
- Automate recurring reporting processes and dashboard updates
- Improve executive visibility and cross-center collaboration
- Implement automated data integration from multiple sources
- Develop a scalable data model within Microsoft Fabric
- Establish a structured analytics workspace with governed Power BI reporting
Program Scope and Deliverables
The engagement covered the complete development of a centralized enterprise analytics platform for CGIAR, from data extraction to executive level reporting. The scope included:
- API integration with Google Analytics 4, Google Search Console, Sprout Social, SplashThat, Meltwater, and Campaign Studio
- Automated data ingestion into Microsoft Fabric
- Structured pipeline development using Bronze, Silver, and Gold data layers
- Data cleaning and normalization of raw inputs
- Development of a scalable data model and centralized semantic layer
- Power BI dashboard design using standardized and validated datasets
- Workspace configuration with governed access controls
- Documentation and structured handover for internal continuity
Implementation Framework
Step 1: Discovery and KPI Alignment
Stakeholder sessions were conducted to define reporting requirements, standardize KPI definitions, and map cross-platform metrics.
Step 2: Source System Integration
Each platform was integrated individually through secure APIs. Data ingestion pipelines were configured and validated before moving to the next source.
Step 3: Data Structuring and Standardization
Raw data was stored in a controlled environment and progressively cleaned, normalized and aligned to standardized metric definitions.
Step 4: Semantic Model Development
A centralized semantic layer was created to define relationships, performance metrics, and reusable business logic across reports.
Step 5: Dashboard Development
Power BI dashboards were built using governed datasets, including executive summaries, performance comparisons, and platform level insights.
Step 6: Validation and Testing
Data accuracy was validated against source systems. KPI calculations were reviewed with stakeholders to ensure alignment.
Step 7: Deployment and Governance
Content was promoted through controlled deployment pipelines. Version control practices were implemented to manage updates and maintain stability.
Solution Architecture
Measurable Impact Across the Organization
The centralized analytics platform significantly improved how CGIAR accesses, interprets and uses performance data across its global network. Reporting shifted from manual consolidation to a fully automated enterprise analytics environment.
Key outcomes included:
- Accelerated reporting cycles through automated dashboards
- A single source of truth across six digital platforms
- Standardized KPI definitions across global centers
- Improved cross-platform analysis and performance comparison
- Reduced manual reporting workload
- Stronger executive visibility and data-driven decision support
- Scalable analytics infrastructure ready for future expansion
This engagement reinforced critical principles for enterprise analytics. Centralized data integration strengthens organizational alignment. Automation improves both speed and reliability of reporting. Standardized metrics build trust across teams. Most importantly, scalable architecture must be intentionally designed to support long term growth.
The Resulting Transformation
By implementing a centralized analytics platform built on Microsoft Fabric and Power BI, CGIAR transitioned from fragmented reporting to a structured, automated, and governed enterprise environment.
The organization now operates with unified visibility across digital channels, supported by consistent data integration and standardized reporting. This foundation enables faster decision making, improved collaboration, and sustainable growth in enterprise analytics capabilities.
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