Data Engineering Podcast
Podcast tekijän mukaan Tobias Macey - Sunnuntaisin

Kategoriat:
419 Jaksot
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The Benefits And Challenges Of Building A Data Trust - Episode 118
Julkaistiin: 3.2.2020 -
Pay Down Technical Debt In Your Data Pipeline With Great Expectations - Episode 117
Julkaistiin: 27.1.2020 -
Replatforming Production Dataflows - Episode 116
Julkaistiin: 20.1.2020 -
Planet Scale SQL For The New Generation Of Applications - Episode 115
Julkaistiin: 13.1.2020 -
Change Data Capture For All Of Your Databases With Debezium - Episode 114
Julkaistiin: 6.1.2020 -
Building The DataDog Platform For Processing Timeseries Data At Massive Scale - Episode 113
Julkaistiin: 30.12.2019 -
Building The Materialize Engine For Interactive Streaming Analytics In SQL - Episode 112
Julkaistiin: 23.12.2019 -
Solving Data Lineage Tracking And Data Discovery At WeWork - Episode 111
Julkaistiin: 16.12.2019 -
SnowflakeDB: The Data Warehouse Built For The Cloud - Episode 110
Julkaistiin: 9.12.2019 -
Organizing And Empowering Data Engineers At Citadel - Episode 109
Julkaistiin: 3.12.2019 -
Building A Real Time Event Data Warehouse For Sentry - Episode 108
Julkaistiin: 26.11.2019 -
Escaping Analysis Paralysis For Your Data Platform With Data Virtualization - Episode 107
Julkaistiin: 18.11.2019 -
Designing For Data Protection - Episode 106
Julkaistiin: 11.11.2019 -
Automating Your Production Dataflows On Spark - Episode 105
Julkaistiin: 4.11.2019 -
Build Maintainable And Testable Data Applications With Dagster - Episode 104
Julkaistiin: 28.10.2019 -
Data Orchestration For Hybrid Cloud Analytics - Episode 103
Julkaistiin: 22.10.2019 -
Keeping Your Data Warehouse In Order - Episode 102
Julkaistiin: 15.10.2019 -
Fast Analytics On Semi-Structured And Structured Data In The Cloud - Episode 101
Julkaistiin: 8.10.2019 -
Ship Faster With An Opinionated Data Pipeline Framework - Episode 100
Julkaistiin: 1.10.2019 -
Open Source Object Storage For All Of Your Data - Episode 99
Julkaistiin: 23.9.2019
This show goes behind the scenes for the tools, techniques, and difficulties associated with the discipline of data engineering. Databases, workflows, automation, and data manipulation are just some of the topics that you will find here.