DevOps in Analytics and Data Warehousing

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Submitted Mar 21, 2018

Technical level: Intermediate

Products & Data DevOps - Handling them in different Angles
How did we Solve our Problem in a space that grows over 80 TB a month?
The Ecosystem that encouraged the platform evolution

Outline

Diversity in the two realms - Data and Application

The Design that solves over 200 + Analytics and Data warehousing requests in a day

Orchestrator
Middleware
Integrations
Service Abstractions
Cognitive Leaning
Application Lineage
Service Handlers
Metadata Managers

Supporting Ecosystems Applicaiton and Tools

Requirements

Fundamental exposure to Warehousing applications is desired.

Speaker bio

Open source Enthusiasist doing software development for over a decade, Loves to spend all day on building open source products. Currently Leading the DevX Space for Data Technology in PayPal. Experince in infecting people with ideas in PyCon and Scipy conferences.

Slides

https://www.slideshare.net/KarthikeyanSelvaraj16/rootconf-92501475

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