Abhishek Tiwari

DECEMBER 22, 2017

Last but not least, ELT attracts a very different type of audience - data scientists who want to perform more exploratory analysis and ad-hoc interactive queries. This type of analysis is greatly eased by open source tools such RStudio, Jupyter, Zeppelin along with scripting languages R and Python. Challenges.

Big Data 40

Big Data Retail Storage Google 40

The Netflix TechBlog

DECEMBER 21, 2020

Some of the optimizations are prerequisites for a high-performance data warehouse. Sometimes Data Engineers write downstream ETLs on ingested data to optimize the data/metadata layouts to make other ETL processes cheaper and faster.

Storage 203

Storage Latency Efficiency Data Engineering 203

The Netflix TechBlog

FEBRUARY 9, 2022

Let’s define some requirements that we are interested in delivering to the Netflix data engineers or anyone who would like to schedule a workflow with some external assets in it. Conclusions This new method available for Netflix data engineers makes workflow management easier, more transparent and more reliable.

Storage 201

Storage Data Engineering Testing Code 201

The Netflix TechBlog

JUNE 6, 2022

Security Strategy and Roadmap, Threat Model, Deliverable Tracking, Residual Risk Criteria, etc). Our focus has been on improving overall security assurance as opposed to just vulnerability prevention. We are now expanding this approach to more parts of our ecosystem.

Software Engineering 169

Software Engineering Scalability Education Engineering 169

The Netflix TechBlog

JULY 21, 2022

Since memory management is not something one usually associates with classification problems, this blog focuses on formulating the problem as an ML problem and the data engineering that goes along with it. Some nuances while creating this dataset come from the on-field domain knowledge of our engineers.

Big Data 179

Big Data Cache Engineering Data Engineering 179

The Netflix TechBlog

NOVEMBER 20, 2023

These challenges are currently addressed in suboptimal and less cost efficient ways by individual local teams to fulfill the needs, such as Lookback: This is a generic and simple approach that data engineers use to solve the data accuracy problem. Users configure the workflow to read the data in a window (e.g.

Processing 210

Processing Big Data Efficiency Engineering 210

The Netflix TechBlog

OCTOBER 30, 2020

We partner closely with the business strategy team to provide as much information as we can to our content executives, so that?—?combined Being an Analytics Engineer is like being a hybrid of a librarian ?? combined with their industry experience?—?they they can make the best decisions for Netflix.

Analytics 136

Analytics Engineering Innovation Metrics 136

All Things Distributed

OCTOBER 7, 2015

While BI solutions have existed for decades, customers have told us that it takes an enormous amount of time, engineering effort, and money to bridge this gap. These solutions lack interactive data exploration and visualization capabilities, limiting most business users to canned reports and pre-selected queries.

Cloud 137

Cloud Big Data AWS Analytics 137

The Netflix TechBlog

JANUARY 11, 2022

To learn about Analytics and Viz Engineering, have a look at Analytics at Netflix: Who We Are and What We Do by Molly Jackman & Meghana Reddy and How Our Paths Brought Us to Data and Netflix by Julie Beckley & Chris Pham. Curious to learn about what it’s like to be a Data Engineer at Netflix?

Innovation 243

Innovation Metrics Engineering Testing 243