Support for managing the technology transfer program and production of the Brazilian Covid-19 Vaccine
Optimizing Data Governance at Unilever
Support for managing the technology transfer program and production of the Brazilian Covid-19 Vaccine
Optimizing Data Governance at Unilever
Case studies

Enhanced data reliability for strategic decision-making at XP

Implementation of an Agile Data Pipeline to enhance governance, operational efficiency, and reduce the time required to calculate precise indicators to support strategic business decisions

Explore the content:

  1. The challenge
  2. Our method
  3. Technologies used in this project
  4. Achieved results

Improving data governance controls to mitigate redundancies and obsolescence, resulting in greater accessibility and reduced manual effort for data collection and analysis.

The challenge

The Technology Governance area at XP sought support from Bridge to build strategic indicator dashboards and improve existing ones.

The development and optimization process covered the entire data cycle, from requirements gathering and indicator ideation to building new data layers and pipelines in the company's data lake, developing ETL processes, and creating dashboards.

The agile pipeline served four central areas within Technology Governance, with products requested directly by the CTO.

This resulted in the creation of more than 40 pipelines, over 80 tables in the data lake, and more than 20 dashboards. Key themes included technological risks, infrastructure cost allocation, critical customer journey visualization for products like PIX and TED, and tactical indicators for information security, compliance, and audit points.

Company: XP Inc.

Industry: Financial Services

Size: large

Our method

Step 1 - Requirement analysis

Requirements analysts work with requesting and adjacent areas to map needs, design indicators and dashboards, identify data sources, define business rules, and support demand prioritization.

Step 2 - Data Engineering

Data engineers build and adjust data pipelines, layers, and tables. They orchestrate jobs for recurring updates, monitor flows, and ensure consistent data delivery.

Step 3 - Dashboard development

Develop dashboards in Power BI, using technologies like Power Apps and Power Automate for app and automation development. Apply UX best practices with standardized models. Conduct internal testing and user acceptance testing. Deploy to production for stakeholder access.

Step 4 - Documentation and assisted operation

Provide documentation and assisted operation, ensuring the proper functioning of developed products and making adjustments as necessary.

Technologies used in this project

The technology architecture primarily relied on the Microsoft environment, utilizing Azure Data Factory, Power BI, and DataBricks. Additionally, Power Apps and Power Automate were used for routine automation and creating integrations.

Achieved results

Operational efficiency gains through reduction in manual effort

Avoided potential fines for non-compliance with audited data

Enhanced security and compliance through data governance implementation

Improved quality of information disseminated within the company

Microsoft's Data Analytics solution, which spans from data structuring in Azure to visualization in Power BI, is gaining increasing relevance in the market. Click here to see client testimonials on the Gartner Peer Review portal.

Read reviews

Drive your business forward with Bridge & Co.

Contact Us