Overview
Syllabus
Introduction
What is a data system
Common sources of complexity
Human fault tolerance
Design for human error
Data loss
Mutability
Immutability
Normalization vs Denormalization
Denormalization
Schemas
Schemas are bad
Schemas are confusing
What is a schema
What is structural integrity
Preventing corruption
Detecting corruption
Preventing mistakes
Learning from experience
Why schemas are painful
My ideal schema tool
Apache Thrift
New Sequel
No Sequel
How would you build a better data system
What do we actually use data systems for
Data Systems
Example
Realtime Queries
Pre Computation
Pre Computation Example
Architecture
Functions
View
Batch Processing
MapReduce
BatchView Databases
BatchView Properties
BatchView Architecture
Batch Computation
RealTime Views
Lambda Architecture
Cap Theorem
Eventually Accurate
Maximizing Value
Tools
Land Architecture
Movement Mistakes
Normalization Personalization
The Future
Book
Performance
Taught by
GOTO Conferences