The document discusses the first Metabase Ljubljana meetup, emphasizing Metabase as an open-source analytics tool with notable users and a focus on user experience. It outlines best practices for data management, including the use of ETL processes, optimal database choices, and deployment strategies. Upcoming features mentioned include instance serialization and support for joins, aimed at improving user experience.

1. Metabase Ljubljana
meetup #1

2. Metabase ❤
github.com/metabase/metabase
• Open source analytics tool
• 11k companies use us daily
• Largest user: Go-Jek with 4000 DAU
• Other notable users: N26, Under Armour, Swisscom,
Bang & Olufsen, NuBank, Convoy …
• Focus on UX and friendliness

3. Collect as much different
types of data as possible

4. Invest in a proper ETL
• Repeatability
• Visibility
• Extensibility
• Scalability
• Recoverability (don’t loose data, ever!)

5. ETL in a box
• segment.com
• Snowplow

6. Data warehouse topology
• Big fat denormalised tables, or
• Star schema
• Use materialised views to tailor
the representation to your tools

7. Which DB?
• TL;DR: use Postgres
• Optimize for ease of ad-hoc querying
• Should be decently performant (waiting kills productivity) but is
unlikely to be the bottleneck
• Simple to deploy, connect to, and use
• Data validation/schemas where possible
• Sane handling of timezones/dates, numbers

8. Choosing an analytics tool
• Who will be using it?
• What are the deliverables?
• Size of data & scaling
• Will it be part of an existing proces or the core of a new one?

9. Deploying Metabase
• Switch app DB to Postgres (or MySQL)
• Docker
• Setup logging
• Upgrade to latest (but backup first)
• Ideally have 1 instance for all (if you need fine grained
access control talk to us about enterprise version)
• Have fun and fall in love! ❤

10. Coming soon
• Instance serialisation
• Reduced memory footprint
• More extensive support for joins (and a new query builder)

11. Questions
https://metabase.com
github.com/metabase/metabase
@sbelak