Enterprise-Analytics-Journey-NielsenIQ

Overview

This repository presents my end-to-end analytics journey at NielsenIQ, showcasing how I progressed from enterprise reporting to BI transformation and database architecture within a global FMCG analytics environment.

Rather than isolated projects, this portfolio reflects real enterprise-scale work, structured into clear phases that demonstrate technical depth, business understanding, and stakeholder enablement.

All content is recreated using dummy data and conceptual examples to fully respect confidentiality.

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Career Progression at a Glance

Reporting Analyst → BI Analyst → Database Architect

Across this journey, I worked closely with FMCG clients, internal data engineering teams, and commercial stakeholders, helping translate complex data into actionable business insights.

Key highlights:

• Managed ~1000 recurring analytical reports
• Covered Swiss & Austrian markets
• Supported complex product hierarchies and market structures
• Played a key role in BI modernization and customer onboarding
• Recognized with a NielsenIQ award for onboarding excellence

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Repository Map (Start Here)

This master repository acts as a navigation hub.
Each phase below links to a dedicated deep-dive repository.

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1️⃣ Reporting & Analytics Foundation

Excel Automation | SQL-Based Analytics | Enterprise Reporting

This phase represents the foundation of my analytics career, focused on large-scale reporting delivery and analytical rigor.

Key themes

• SQL-based analytical logic via Answers
• Advanced Excel RTL (Reporting Table Layer) frameworks
• Automation, scalability, and data accuracy
• Business analysis and visualization
• Customer enablement on analytical tools

🔗 Explore full repository
👉 Nielseniq-reporting-analytics-foundation

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2️⃣ BI Transformation & Data Lake Migration

Legacy Migration | Discover | Change Management

This phase focuses on modernizing analytics by migrating legacy reports to a centralized enterprise data lake.

Key themes

• Migration from Answers to Discover
• Rebuilding reports to answer the same business questions with modern logic
• Explaining masking rules, access governance, and new data models
• Supporting customers through major platform change
• BI thinking beyond “copy-paste reporting”

🔗 Explore full repository
👉 Nielseniq-bi-transformation-discover

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3️⃣ Database Architecture & Customer Enablement

Data Modeling | Hierarchies | Business Translation

This phase highlights my role in database architecture, governance, and acting as a bridge between business and technical teams.

Key themes

• Database structure and complexity explanation
• Product hierarchy and item coding governance
• Translating customer needs into implementable requirements
• Managing expectations and ensuring data integrity
• Leading and supporting customer onboarding initiatives

🔗 Explore full repository
👉 Nielseniq-database-architecture-business-translation

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Award & Recognition

🏆 NielsenIQ Award – Customer Onboarding Excellence

Recognized for:

• Leading and supporting smooth onboarding of new customers
• Adapting templates and processes for international markets
• Collaborating with multiple internal teams
• Ensuring scalable, repeatable onboarding for future clients

This award reflects not only technical contribution, but also ownership, communication, and customer focus.

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Skills Demonstrated Across the Journey

Analytics & Data

• SQL-based analytical thinking
• KPI design and governance
• Trend, variance, and performance analysis
• FMCG domain analytics

Tools & Platforms

• Answers (SQL-driven analytics concepts)
• Advanced Excel (RTL automation, macros, formulas)
• Discover (Enterprise BI & Data Lake)
• Excel Add-ins & analytical interfaces

Data Modeling & Architecture

• Product and customer hierarchies
• Item coding and categorization logic
• Data quality and consistency management

Business & Stakeholder Enablement

• Customer training and enablement
• Business-to-technical translation
• Expectation management
• Cross-team collaboration

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Visuals & Documentation

Each linked repository includes:

• Conceptual data flow diagrams
• Architecture and hierarchy diagrams
• Sample charts and analytical visuals
• Clear written explanations of logic and decisions

These visuals are designed to explain how and why decisions were made, not just show outputs.

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Data Confidentiality Notice

All examples, diagrams, charts, and explanations in this portfolio use dummy data and simplified structures.

No proprietary NielsenIQ systems, schemas, logic, or client data are exposed.

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Final Note

This portfolio reflects how analytics work is done in real enterprise environments:

• At scale
• With governance
• With business accountability
• And with continuous evolution

Thank you for exploring my analytics journey.

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Navigation

• Overview: About Me It contain links to My portfolio and all major pages and projects

• NielsenIQ: NielsenIQ-Enterprise-Analytics-Journey Links to all Nielsen Repo

• ECO3: ECO3-enterprise-analytics-journey Links to all ECO3 Repo