The Netflix TechBlog

JUNE 20, 2024

In this talk, Jason Reid discusses the pros and cons of both data warehouse bundling and unbundling in terms of performance, governance, and flexibility, and he examines how the trend of data warehouse unbundling will impact the data engineering landscape in the next 5 years. Until next time!

Data Engineering 201

Data Engineering Engineering Entertainment Software Engineering 201

Rigor

SEPTEMBER 11, 2019

Jake is a developer advocate at Google working with the Chrome team to develop and promote web standards and developer tools, as well as a contributor to the Chromium blog. Jake is a frequent speaker at many popular conferences and events, such as 100 Days of Google Dev , JAMstakConf , JSConf , SmashingConf , and dozens of others.

Performance 89

Performance Education Google Website 89

Abhishek Tiwari

DECEMBER 22, 2017

Cheap storage and on-demand compute in the cloud coupled with the emergence of new big data frameworks and tools are forcing us to rethink the whole ETL and data warehousing architecture. You can also use cloud and SaaS services such as Google BigQuery, Amazon Redshift Spectrum, Amazon Athena, Qubole to implement ELT approach.

Big Data 40

Big Data Retail Storage Google 40

Dynatrace

MAY 1, 2023

Then, big data analytics technologies, such as Hadoop, NoSQL, Spark, or Grail, the Dynatrace data lakehouse technology, interpret this information. Here are the six steps of a typical ITOA process : Define the data infrastructure strategy. Choose a repository to collect data and define where to store data.

Analytics 183

Analytics Artificial Intelligence Big Data Open Source 183

The Netflix TechBlog

JULY 26, 2021

Once the data has landed in the Iceberg tables in Netflix Data Warehouse, they could be used for ad-hoc or scheduled querying and reporting. Centralized data will be moved to third party services such as Google Sheets and Airtable for the stakeholders. Data Delivery via Data Mesh What is Data Mesh?

Big Data 254

Big Data Government Analytics Processing 254

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 101

Hardware Storage Big Data Blockchain 101

ACM Sigarch

APRIL 8, 2019

big-data processing, machine learning, quantum computing, and so on). Communities in other fields have made a substantial effort towards “democratization,” where tools are not just made open source, but also accessible to everyone. Lena Olson is a Software Engineer at Google. .

Architecture 74

Architecture Open Source Hardware Software Engineering 74