DZone

DECEMBER 21, 2020

Setting up a data warehouse is the first step towards fully utilizing big data analysis. Still, it is one of many that need to be taken before you can generate value from the data you gather. An important step in that chain of the process is data modeling and transformation.

Big Data 196

Big Data Google Scalability Processing 196

The Netflix TechBlog

MARCH 2, 2021

At Netflix, our data scientists span many areas of technical specialization, including experimentation, causal inference, machine learning, NLP, modeling, and optimization. Together with data analytics and data engineering, we comprise the larger, centralized Data Science and Engineering group.

Analytics 207

Analytics C++ Innovation Engineering 207

The Netflix TechBlog

MARCH 5, 2019

This operational component places some cognitive load on our engineers, requiring them to develop deep understanding of telemetry and alerting systems, capacity provisioning process, security and reliability best practices, and a vast amount of informal knowledge about the cloud infrastructure.

Infrastructure 182

Infrastructure Cloud Scalability AWS 182

The Netflix TechBlog

NOVEMBER 22, 2019

This entertaining romp through the tech stack serves as an introduction to how we think about and design systems, the Netflix approach to operational challenges, and how other organizations can apply our thought processes and technologies. We share everything attendees need to implement CloudTrail in their own organizations.

AWS 100

AWS Entertainment Open Source Benchmarking 100

The Netflix TechBlog

NOVEMBER 22, 2019

This entertaining romp through the tech stack serves as an introduction to how we think about and design systems, the Netflix approach to operational challenges, and how other organizations can apply our thought processes and technologies. We share everything attendees need to implement CloudTrail in their own organizations.

AWS 100

AWS Entertainment Open Source Benchmarking 100

O'Reilly

FEBRUARY 2, 2020

A model isn’t source code, and it isn’t data; it’s an artifact built from the two. Given source code and the training data, you could re-produce a model, but it almost certainly wouldn’t be the same because of randomization in the training process. Models almost certainly react to incoming data; that’s their point.

Software Architecture 70

Software Architecture Monitoring Software Engineering Architecture 70

The Netflix TechBlog

NOVEMBER 22, 2019

This entertaining romp through the tech stack serves as an introduction to how we think about and design systems, the Netflix approach to operational challenges, and how other organizations can apply our thought processes and technologies. In 2019, Netflix moved thousands of container hosts to bare metal.

AWS 37

AWS Entertainment Open Source Benchmarking 37

O'Reilly

FEBRUARY 18, 2020

Usage specific to Python as a programming language grew by just 4% in 2019; by contrast, usage that had to do with Python and ML—be it in the context of AI, deep learning, and natural language processing, or in combination with any of several popular ML/AI frameworks—grew by 9%. In aggregate, data engineering usage declined 8% in 2019.

Software Architecture 136

Software Architecture DevOps Data Engineering Architecture 136

The Netflix TechBlog

JULY 21, 2022

We at Netflix, as a streaming service running on millions of devices, have a tremendous amount of data about device capabilities/characteristics and runtime data in our big data platform. With large data, comes the opportunity to leverage the data for predictive and classification based analysis.

Big Data 179

Big Data Cache Engineering Data Engineering 179

The Netflix TechBlog

SEPTEMBER 18, 2020

But there is far less agreement on what that term “data analytics” actually means?—?or Even within Netflix, we have many groups that do some form of data analysis, including business strategy and consumer insights. or what to call the people responsible for the work.

Analytics 240

Analytics Engineering Data Engineering Tuning 240

Abhishek Tiwari

JULY 7, 2023

In the era of big data and complex data processing, data pipelines have emerged as a popular solution for managing and manipulating data. They provide a systematic approach to extract, transform, and load (ETL) data from various sources, enabling organizations to derive valuable insights.

Logistics 52

Logistics Transportation Scalability Data Engineering 52

The Netflix TechBlog

MARCH 25, 2019

We adopted the following mission statement to guide our investments: “Provide a complete and accurate data lineage system enabling decision-makers to win moments of truth.” We are loading the lineage data to a graph database to enable seamless integration with a REST data lineage service to address business use cases.

Infrastructure 219

Infrastructure Big Data Transportation Architecture 219

All Things Distributed

OCTOBER 7, 2015

In such a data intensive environment, making key business decisions such as running marketing and sales campaigns, logistic planning, financial analysis and ad targeting require deriving insights from these data. However, the data infrastructure to collect, store and process data is geared toward developers (e.g.,

Cloud 137

Cloud Big Data AWS Analytics 137

The Netflix TechBlog

OCTOBER 30, 2020

We started out with a small working group where we brainstormed the key questions to address, what data we could use to answer said questions, and came up with a work plan for how the analysis might take shape. Then I put on my headphones and got to work, writing SQL and using Tableau to present the data in a useful way.

Analytics 136

Analytics Engineering Innovation Metrics 136

The Netflix TechBlog

SEPTEMBER 10, 2019

After recreating the dataset, you can plot the raw numbers and perform custom analyses to understand the distribution of the data across test cells. With our new platform for experimentation analysis, it’s easy for scientists to perfectly recreate analyses on their laptops in a notebook.

Metrics 215

Metrics Architecture Infrastructure Innovation 215

O'Reilly

MARCH 2, 2020

When a project is going off track because some requirement wasn’t understood properly, you need to fix that as soon as possible—not after a year-long development process. When processes change, who wins, who loses, and why? Radar data points: Recent research and analysis. Adopting AI can help data quality.

Artificial Intelligence 21

Artificial Intelligence Software Architecture Programming Infrastructure 21

All Things Distributed

NOVEMBER 15, 2016

Previously, I wrote about Amazon QuickSight , a new service targeted at business users that aims to simplify the process of deriving insights from a wide variety of data sources quickly, easily, and at a low cost. Put simply, data is not always readily available and accessible to organizational end users.

Analytics 152

Analytics Availability Media Social Media 152