> Author

Darin Briskman

Data Person => doing interesting things with scale, speed, and streaming with Apache Druid, Imply Polaris, and other cool stuff

Why Data needs more than CRUD

After over 30 years of working with data analytics, we’ve been witness (and sometimes participant) to three major shifts in how we find insights from data – and now we’re looking at the fourth.

#architecture

For people getting started with Apache Druid, this lesson takes a developer through all the key planning phases for a Druid project, including purpose, queries, data sources, visualization, infrastructure, and documentation.

#deployment

Generating Synthetic Data for Development and Testing

This lesson outlines various approaches to generating synthetic data for nonproduction uses, including data requirements and programmatic generation.

#deployment

Ingesting Batch Data

It’s easy to ingest batch data into Druid, turning files into full-indexed, high-performance tables using SQL commands. This lesson provides an overview of ingesting data from batch sources with in-database transformation capabilities and overall workflow automation.

#ingestion

Ingesting Stream Data

This lesson outlines the key considerations when ingesting data from streaming pipelines including Apache Kafka and Amazon Kinesis. It includes information on Data Sources, Schema Definition, Ingestion Spec, and Monitoring.

#ingestion

Working with changing data

This lesson covers key considerations when working with data sources that mutate over time, including creating tables from streaming data and using schema auto-discovery.

#modeling

Working with Nested JSON in Druid

This lesson covers key considerations for how to use nested data in Apache Druid.

#modeling

Scaling a Druid cluster

This lesson walks through design and implementation of Druid infrastructure, including Initial Cluster Creation, Infrastructure Provider Choice, Adding and Removing Capacity, Landscape Design, and Performance Tuning

#operations