Brittany Davis

Hey there, I’m the head of data at Narrator. Before Narrator, I was a senior data scientist at WeWork (on the rec systems team). I like data, analytics, tiny homes, and mixology :)

📍 New York, NY

Data Engineering

Does Incremental Modeling Truly Save Money? Avoiding Pitfalls for Data Engineers

Discover effective cost-saving strategies for data engineers to optimize incremental data processing. Learn how to overcome challenges and maximize the benefits of this powerful approach.

Rethink Your Metrics and Drive Meaningful Change

While big-picture metrics like total sales and annual recurring revenue (ARR) give you an overview, they don't provide the practical insights needed for real change.

New Activity Schema Course by DeepSkyData

Discover a new course from DeepSkyData that empowers product managers, data analysts, and analytics engineers to master the Activity Schema.

Data Analysis

The Data Modeling Paradox: Are we sacrificing insights for structure?

While companies heavily rely on data to inform their strategies, the very data models they employ often hinder their ability to ask deep and insightful questions.

Data Engineering

Leaving Data Chaos Behind: A Paradigm Shift towards Activity-based Modeling

Explore a powerful approach that can revolutionize the way you understand and utilize data: modeling data as activities. Activities can bring clarity and organization to your data, allowing you to gain valuable insights and make the most of your data.

Data Analysis

Bad data analysis questions I see every week (and how to fix them)

For the past few years at Narrator, I’ve been collecting the bad data questions I often stumble upon and reflecting on how to make them better. This simple exercise, done regularly for a few years, significantly improved the quality of questions I ask. Last week, I thought other data

Data Analysis

How I frame data questions to make analyses more useful

A simple yet effective mental model I use to turn a vague stakeholder request into something that can be analyzed with data.

Why star schema is set up for failure

What is star schema? Star schema [https://en.wikipedia.org/wiki/Star_schema] is the most common approach to data modeling — primarily made up of fact and dimension tables. Why you need data modeling * Your company has a lot of data across many different data sources: website and marketing interactions,