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Data Engineers of Netflix?—?Interview with Kevin Wylie

The Netflix TechBlog

Data Engineers of Netflix?—?Interview Interview with Kevin Wylie This post is part of our “Data Engineers of Netflix” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Kevin, what drew you to data engineering?

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Incremental Processing using Netflix Maestro and Apache Iceberg

The Netflix TechBlog

For example, a job would reprocess aggregates for the past 3 days because it assumes that there would be late arriving data, but data prior to 3 days isn’t worth the cost of reprocessing. Backfill: Backfilling datasets is a common operation in big data processing. data arrives too late to be useful).

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Hyper Scale VPC Flow Logs enrichment to provide Network Insight

The Netflix TechBlog

Cloud Network Insight is a suite of solutions that provides both operational and analytical insight into the Cloud Network Infrastructure to address the identified problems. These characteristics allow for an on-call response time that is relaxed and more in line with traditional big data analytical pipelines.

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Expanding the Cloud: Introducing Amazon QuickSight

All Things Distributed

Today, I am excited to share with you a brand new service called Amazon QuickSight that aims to simplify the process of deriving insights from a wide variety of data sources in a fast and affordable manner. Big data challenges. Enter Amazon QuickSight.

Cloud 137
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5 data integration trends that will define the future of ETL in 2018

Abhishek Tiwari

In 2018, we will see new data integration patterns those rely either on a shared high-performance distributed storage interface ( Alluxio ) or a common data format ( Apache Arrow ) sitting between compute and storage. For instance, Alluxio, originally known as Tachyon, can potentially use Arrow as its in-memory data structure.

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Spice up your Analytics: Amazon QuickSight Now Generally Available in N. Virginia, Oregon, and Ireland.

All Things Distributed

They require teams of data engineers to spend months building complex data models and synthesizing the data before they can generate their first report. The cost and complexity to implement, scale, and use BI makes it difficult for most companies to make data analysis ubiquitous across their organizations.

Analytics 152