Rigor

SEPTEMBER 11, 2019

Presented here alphabetically by last name: Rachel Andrew. You’ll find his articles, initiatives, and speaking engagements on his website , and you simply must read his writing about web optimization for Google and watch nearly 50 of his presentations on YouTube. Here is our (ever-growing!) Rachel Andrew. Jason Grigsby. .”

Performance 89

Performance Education Google Website 89

SQL Server According to Bob

FEBRUARY 15, 2018

When I started to write this post I thought I knew who all was presenting but then I had to go back over the session lineup to see for myself. Best practices on Building a Big Data Analytics Solution – Michael Rys. If you want to learn about Azure Data Lake, there is no one better.

Engineering 40

Engineering Azure Best Practices Servers 40

Dynatrace

MARCH 11, 2021

I took a big-data-analysis approach, which started with another problem visualization. During the implementation of the real-time visualization I presented in part three , I had an idea for another visualization; I wanted to visualize the number of detected problems globally, for a longer timeframe. Stay tuned!

Tuning 263

Tuning Architecture Monitoring Big Data 263

The Netflix TechBlog

OCTOBER 27, 2020

Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy. The processed data is typically stored as data warehouse tables in AWS S3.

Latency 243

Latency Storage Big Data Tuning 243

The Netflix TechBlog

DECEMBER 21, 2020

We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits. This article will list some of the use cases of AutoOptimize, discuss the design principles that help enhance efficiency, and present the high-level architecture.

Storage 203

Storage Latency Efficiency Data Engineering 203

O'Reilly

SEPTEMBER 19, 2023

Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.

Hardware 98

Hardware Storage Big Data Blockchain 98

All Things Distributed

NOVEMBER 30, 2016

Effectively applying AI involves extensive manual effort to develop and tune many different types of machine learning and deep learning algorithms (e.g. automatic speech recognition, natural language understanding, image classification), collect and clean the training data, and train and tune the machine learning models.

AWS 166

AWS Lambda Artificial Intelligence Mobile 166