Data Engineering Efficiency Training 
The Netflix TechBlog
MARCH 7, 2024
For ETL and other heavy lifting of data, we mainly rely on Apache Spark. In addition to Spark, we want to support last-mile data processing in Python, addressing use cases such as feature transformations, batch inference, and training. Correspondingly, each application brings its own bespoke set of dependencies.
The Netflix TechBlog
MARCH 4, 2024
Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. the retry success probability) and compute cost efficiency (i.e., Multi-objective optimizations.
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Dynatrace
JULY 6, 2022
Ultimately, IT automation can deliver consistency, efficiency, and better business outcomes for modern enterprises. Automating IT practices offers enterprises faster data centers and cloud operations, as well as increased flexibility and accuracy. AI that is based on machine learning needs to be trained. Read eBook now!
The Netflix TechBlog
NOVEMBER 20, 2023
It also improves the engineering productivity by simplifying the existing pipelines and unlocking the new patterns. We will show how we are building a clean and efficient incremental processing solution (IPS) by using Netflix Maestro and Apache Iceberg. Introduction Netflix relies on data to power its business in all phases.
The Netflix TechBlog
SEPTEMBER 18, 2020
A role in data science eventually seemed like a natural transition, but it wasn’t without its hurdles: With my consulting background, I had to go through a few other roles first while learning how to code on the side. Julie] Chris and I have the same primary stakeholders (or engineering team that we support): Encoding Technologies.
The Netflix TechBlog
OCTOBER 18, 2022
by Jun He , Akash Dwivedi , Natallia Dzenisenka , Snehal Chennuru , Praneeth Yenugutala , Pawan Dixit At Netflix, Data and Machine Learning (ML) pipelines are widely used and have become central for the business, representing diverse use cases that go beyond recommendations, predictions and data transformations.
High Scalability
MARCH 3, 2020
Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.
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