The Netflix TechBlog

JUNE 20, 2024

To address this, we propose developing an intelligent agent that can automatically discover, map, and query all data within an enterprise. This “Enterprise Data Model/Architect Agent” employs generative AI techniques for autonomous enterprise data modeling and architecture. Until next time!

Data Engineering 201

Data Engineering Engineering Entertainment Software Engineering 201

Dynatrace

JANUARY 16, 2023

Open-source software drives a vibrant Kubernetes ecosystem. Most Kubernetes clusters in the cloud (73%) are built on top of managed distributions from the hyperscalers like AWS Elastic Kubernetes Service (EKS), Azure Kubernetes Service (AKS), or Google Kubernetes Engine (GKE). Java, Go, and Node.js

Open Source 339

Open Source Java Operating System Programming 339

Dynatrace

MARCH 24, 2023

Originally created by Google, Kubernetes was donated to the CNCF as an open source project. Part of its popularity owes to its availability as a managed service through the major cloud providers, such as Amazon Elastic Kubernetes Service , Google Kubernetes Engine , and Microsoft Azure Kubernetes Service.

Infrastructure 181

Infrastructure Open Source Operating System Cloud 181

Scalegrid

MAY 13, 2020

In this blog post, we explain what Greenplum is, and break down the Greenplum architecture, advantages, major use cases, and how to get started. Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. Greenplum Advantages.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

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. In addition, this approach is more tailored for both structured as well unstructured data sets. Classic ETL. Challenges.

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. Why use a data lakehouse for causal AI? Why is ITOA important? Apache Spark.

Analytics 183

Analytics Artificial Intelligence Big Data Open Source 183

The Netflix TechBlog

JULY 26, 2021

This happens at an unprecedented scale and introduces many interesting challenges; one of the challenges is how to provide visibility of Studio data across multiple phases and systems to facilitate operational excellence and empower decision making. We will deep dive into Data Delivery and Data Consumption in the following sections.

Big Data 254

Big Data Government Analytics Processing 254