Embedding📖 6 min read
Build vs. buy embedded analytics: an honest breakdown
Build vs buy embedded analytics: cost, timeline, and technical trade-offs when deciding between building from scratch or using a platform like Metabase.
All Guides
Embedding📖 7 min read
Why your app needs embedded analytics (and why it's harder than it looks to build yourself)
Build embedded analytics for your app: why customers demand it, the complexity, and how to deliver it without massive engineering investment.
Data📖 5 min read
Common data model mistakes that break your analytics
Avoid common data model mistakes: improper normalization, inconsistent definitions, and architectural decisions that tank analytics performance.
Data📖 5 min read
dbt and Metabase: how they work together
How dbt and Metabase work together: transform raw data in dbt, organize it in Metabase, and build analytics without data engineers.
Data📖 5 min read
What is a semantic layer and do you need one?
What is a semantic layer? Transform raw data into business definitions, ensure consistent metrics, and empower non-technical teams to analyze data.
Data📖 6 min read
Do you need a data warehouse? A dev's guide to the honest answer
Do you need a data warehouse? Understand when traditional databases stop scaling and when a warehouse becomes essential for analytics.
Metrics📖 6 min read
What is retention rate and how to measure it
Understand retention rate: measure how many users return to your product, identify churn patterns, and improve long-term engagement.
Metrics📖 5 min read
What is MRR and how to calculate it correctly
Monthly Recurring Revenue (MRR) guide: calculate, track, and improve this essential metric for SaaS businesses and recurring revenue models.
Metrics📖 6 min read
What is activation rate and how do you measure it
Activation rate explained: measure the percentage of new users who reach your product's core value moment and drive long-term engagement.
Metrics📖 6 min read
How to calculate churn rate (and which formula to use)
Calculate churn rate: the formula, what it tells you about product health, and why it matters more than growth for sustainable businesses.
Metrics📖 6 min read
DAU, WAU, and MAU: what they mean and how to calculate them
Understand DAU, WAU, and MAU: the core metrics for engagement that show daily, weekly, and monthly active users and how to interpret them correctly.
Data📖 6 min read
Querying your data: SQL, without-SQL, and AI
Analytics with SQL and NoSQL: how relational and document databases handle analytics workloads differently and what each is best for.
Analytics📖 6 min read
Embedding analytics in your product: what to know before you build
Build embedded analytics into your product: understand why customers demand it, the technical challenges, and how to do it without hiring a data team.
Deployment📖 5 min read
Self-hosted vs. cloud analytics: what you're actually trading off
Compare self-hosted vs cloud analytics: trade-offs in control, cost, maintenance, compliance, and how to choose the right model for your needs.
Deployment📖 6 min read
Time to insight: why speed matters in an analytics platform
Time to insight is critical: the gap between asking a question and getting an answer determines whether teams act on data or abandon analytics.
Deployment📖 5 min read
Why open source matters for an analytics platform
Why open-source analytics tools matter: flexibility, control, vendor independence, and the economics of building analytics infrastructure.
Analytics📖 6 min read
You built the product. Now you're the analyst.
How developers become accidental data analysts: SQL queries, dashboards, and the tools that let engineers answer business questions independently.
Growth📖 6 min read
Analytics at Series A and B: the debt you didn't know you were taking on
Navigate analytics debt at Series A and B: consolidate data sources, align on metrics, and build dashboards that drive business decisions.
Getting Started📖 5 min read
When startups actually need analytics (and what happens when you skip it)
Essential metrics for startup analytics: user growth, activation, retention, and cohort analysis to validate product-market fit and guide development.
Getting Started📖 5 min read
Analytics for indie hackers and side project builders
Guide to setting up analytics for indie hackers: track users, measure product-market fit, and make data-driven decisions with minimal infrastructure.
Getting Started📖 5 min read
Why developers need analytics (not just monitoring)
Learn why developers need analytics to track feature adoption, activation, retention, and drop-off without building from scratch.