Articles & Case Studies

A collection of frameworks, best practices, and real-world case studies on data.

Marketing Mix Modeling (MMM) in 2026: Google Meridian, Geo Testing, and Offline Incrementality
An advanced guide to Marketing Mix Modeling in 2026 covering Google Meridian, geo experiments, offline incrementality for TV, cinema, OOH and radio, counterfactual measurement, and budget allocation under modern privacy and iOS data constraints.
Marketing Mix Modeling Google Measurement 2026 Geo Experimentation Incrementality Causal Inference Bayesian Modeling Budget Optimization
The Ultimate Guide to A/B Testing Statistics: From Theory to Practice
Go beyond p-values. This deep dive covers everything from choosing the right statistical test for your metrics to calculating sample size with power analysis. A complete guide for data-driven professionals in e-commerce, marketing, and product.
ab testing statistics data science product analytics conversion rate optimization power analysis
Manual Predictions & Backpropagation in a 2–2–1 Neural Network (Sigmoid + MSE)
A full, step-by-step walkthrough that computes a 2–2–1 neural network by hand: forward pass, MSE loss, formal objective, dependency map, backpropagation derivations, and one complete weight update—ready-to-learn math with concrete numbers.
neural networks machine learning backpropagation algebra calculus deep learning tutorial
The Strategic Imperative of RAG: An Investment Framework for Unlocking Enterprise Knowledge
Generative AI is a transformative platform, but its true enterprise value is unlocked when grounded in proprietary data. This analyst report provides a strategic framework for investing in Retrieval-Augmented Generation (RAG), detailing the technology, a portfolio of high-ROI use cases, and a phased roadmap for implementation. RAG is not an experiment; it is a critical investment in building a durable competitive moat.
RAG Generative AI LLM AI Strategy Enterprise AI Vector Database Knowledge Management
The Foundations of a Digital Mind: How Neural Networks Actually Work
From basic algebra to the calculus of learning, this in-depth guide demystifies neural networks. Using a simple, step-by-step example, we'll explore the core concepts of linear algebra, statistics, and backpropagation that allow machines to learn.
neural networks machine learning data science algebra statistics backpropagation deep learning
From Monolith to Modular: A Case Study in Migrating to a Modern Data Stack with dbt Cloud
Our most critical dashboard was failing, powered by a monolithic tangle of Airflow DAGs and raw SQL scripts. This is the in-depth story of how we broke down that monolith and migrated our legacy infrastructure to dbt Cloud, applying Kimball's dimensional modeling to build a platform that restored trust and accelerated the entire business.
dbt data modeling analytical engineering data strategy airflow monolith kimball

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