JOIN 2017 - Deep Dive - To Use or Not Use PDT's

Why is a pragmatic balance between PDT’s and ETL important?

• Makes your database resources more efficient and effective


• Improves the end user experience


• An optimized data pipeline provides stable infrastructure for scaleable analytics

1. When to EDT, PDT or ETL

EDT

• Real-time data


• Quick to query


• Dynamic Builds

PDT

• Data freshness


• Available database resources


• Prototyping

ETL

• Powerful ETL tool - Discourse Discussion
  
  
  
  • To name a few: Matillion, Talend, Alooma, ETLeap, Keboola, DataVirtuality, Xplenty
  
  
  
  


• Well understood PDT


• Consistently used PDT


• PDT used outside of Looker

2. Know your database

Discourse Discussion

3. Optimize your database to improve PDT development and ETL performance

Fabio’s Deep Dive - Redshift Optimization with Looker’s Redshift Block presentation provides specifics for Redshift as well as general database optimization concepts and techniques that apply to a wide range of databases

Looker Analytic Block

You can find my JOIN 2017 presentation [here](https://docs.google.com/presentation/d/e/2PACX-1vSsKcPJfT3kmWPY6WoGFTW2sBaHXAXGkKTAz5yUVdOi-mlDenU_BQbsmc9AWlatvJkrrBSffkyCPtC4/pub?start=true&loop=true&delayms=15000).