Dynatrace

JULY 6, 2022

AIOps brings an additional level of analysis to observability, as well as the ability to respond to events that warrant it. This requires significant data engineering efforts, as well as work to build machine-learning models. Big data automation tools. IT automation, DevOps, and DevSecOps go together.

Artificial Intelligence 189

Artificial Intelligence Tuning Strategy Big Data 189

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

All Things Distributed

OCTOBER 7, 2015

We live in a world where massive volumes of data are generated from websites, connected devices and mobile apps. 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.

Cloud 137

Cloud Big Data AWS Analytics 137

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.” Netflix’s diverse data landscape made it challenging to capture all the right data and conforming it to a common data model.

Infrastructure 219

Infrastructure Big Data Transportation Architecture 219

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

All Things Distributed

NOVEMBER 15, 2016

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

Analytics Availability Media Social Media 152