Narrator Data Blog | Narrator.ai

How to calculate data warehouse cost and prevent it from exploding

A realistic way to estimate warehouse cost and techniques to prevent the warehouse cost from getting out of hand.

The cost of product analytics data in your data warehouse

Syncing product analytics data into your warehouse is more expensive than you might think. This explains why, and what to do about it.

Data Analysis

What's missing from the Amplitude and Snowflake partnership

Amplitude and Snowflake's partnership is a great first pass at warehouse-powered data analytics. However, this sync is missing many data team requirements for a complex and secure production data system.

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

Forget about the product

Last week at Narrator, we did an interesting product thinking exercise that reminded me of the incredible value of constantly going back to the customer and reasoning from there, so I thought I’d share what it was and why it ended up being so valuable for us. Here’s

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.

A collage of all blog authors mentioned in the post

Data Science

Comprehensive, original, insightful, and otherwise interesting data science blogs

Most blogs in data science are like most people at a cocktail party: they talk news, weather, or politics, and do not venture into deep, interesting subjects. I provide a list of blogs that do.

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,

Data Engineering

Handling slowly changing dimensions in an Activity Schema

The simplicity of modeling slowly changing dimensions in an Activity Schema vs a Star Schema

Data Engineering

Identifying bot traffic with SQL

Systematically identify bot users in your web traffic with a simple SQL query.

Data Analysis

A guide to data-driven prioritization for product managers

PMs use data to prioritize, align their team, and communicate the impact of their work. How does this work in practice?

Unlocking the Value of Data Governance

How deploying data governance can bring meaning to your data and accelerate your digital transformation.

Data Analysis

What (actually) is self service analytics?

Why data-informed decisions are more important than broad access to data for self service analytics

Data Science

When Correlation is Better than Causation

A heuristic approach for using correlations to inform decisions

Data Analysis

Self Service Analytics

Will business users ever be able to ask ad hoc questions without involving data teams? Narrator’s self-service analytics solution is the answer.

Sources and Destinations: Data Engineering

In a recent podcast of Sources and Destinations, our CEO Ahmed talks about data engineering, industry confusions and what is it really like to be a data-driven company.

SQL

PostgreSQL's missing DateDiff function

DATEDIFF is an extremely useful function for analytical queries. Given two timestamps it'll tell you how many days, weeks, months, hours, etc they are apart. Here we show an implementation of this function for Postgres.

Marketing

Identity Resolution in a privacy-first, cookie-less future: How to prepare tracking for analytics

Learn how we’ve been able to get 95% identity attribution to devices and modern browsers in a world of cookie consent banners and privacy-first updates.

Data Engineering

Shareable data analyses using templates

We've been using shared data analyses in production for three years. Here's how you can create reusable templates for common metrics and analyses.

Data Engineering

How To Do Data Democratization With Flexible Data Modeling

Data democratization usually means simple dashboards. Here's how to safely give stakeholders the ability to ask any question

SQL

Using PostgreSQL as a Data Warehouse

With some tweaking Postgres can be a great data warehouse. Here's how to configure it.

Data Engineering

Unleash your data's full potential with a modern data stack

How to know if you're ready for a modern data platform built on a data warehouse.

Data Engineering

Data Dictionary: A Symptom, not a Solution

Having a data dictionary is really a symptom of a complex data modeling layer. With a simpler layer it's possible to avoid maintaining a dictionary altogether.

Data Stories: Fun Insights 5 Startups Found in their Data

5 startups share a story of how they arrived at an interesting insight using their data.

SQL

Synthetic Data: Generating realistic user timestamps in SQL

How to generate timestamps in SQL that match realistic user behavior data.