Netflix Tech

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty At Netflix, our Membership and Finance Data Engineering team harnesses diverse data related to plans, pricing, membership life cycle, and revenue to fuel analytics, power various dashboards, and make data-informed decisions.

Data Engineering 107

Data Engineering Engineering Data Systems Review 107

Mobilunity

MAY 3, 2024

When it comes to financial technology, data engineers are the most important architects. As fintech continues to change the way standard financial services are done, the data engineer’s job becomes more and more important in shaping the future of the industry.

Data Engineering 52

Data Engineering Fintech Engineering Data 52

CIO

APRIL 4, 2023

In order to move AI forward, we need to first build and fortify the foundational layer: data architecture. This architecture is important because, to reap the full benefits of AI, it must be built to scale across an enterprise versus individual AI applications. Constructing the right data architecture cannot be bypassed.

Architecture 130

Architecture Data Analysis Construction 130

Cloudera

DECEMBER 21, 2021

Since the release of Cloudera Data Engineering (CDE) more than a year ago , our number one goal was operationalizing Spark pipelines at scale with first class tooling designed to streamline automation and observability. The post Cloudera Data Engineering 2021 Year End Review appeared first on Cloudera Blog.

Data Engineering 117

Data Engineering Technical Review Software Review Engineering 117

Apiumhub

JANUARY 26, 2022

Data engineer roles have gained significant popularity in recent years. Number of studies show that the number of data engineering job listings has increased by 50% over the year. And data science provides us with methods to make use of this data. Who are data engineers?

Data Engineering 52

Data Engineering Engineering Data Artificial Inteligence 52

Altexsoft

JUNE 25, 2019

If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Cloudera

SEPTEMBER 9, 2022

The promise of a modern data lakehouse architecture. Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested.

Architecture 102

Architecture Innovation Data Open Source 102

Altexsoft

OCTOBER 30, 2021

If you’re an executive who has a hard time understanding the underlying processes of data science and get confused with terminology, keep reading. We will try to answer your questions and explain how two critical data jobs are different and where they overlap. Data science vs data engineering.

Data Engineering 98

Data Engineering Engineering Data Artificial Inteligence 98

O'Reilly Media - Data

MAY 24, 2018

In particular, we examined the evolution of key topics covered in this podcast: data science and machine learning, data engineering and architecture, AI, and the impact of each of these areas on businesses and companies. Continue reading The evolution of data science, data engineering, and AI.

Data Engineering 121

Data Engineering Engineering Data Artificial Inteligence 121

Perficient

FEBRUARY 13, 2023

Introduction: We often end up creating a problem while working on data. So, here are few best practices for data engineering using snowflake: 1.Transform Each data model has its own advantages and storing intermediate step results has significant architectural advantages.

Data Engineering 69

Data Engineering Engineering Data Storage 69

Trigent

JUNE 20, 2022

To do this, they are constantly looking to partner with experts who can guide them on what to do with that data. This is where data engineering services providers come into play. Data engineering consulting is an inclusive term that encompasses multiple processes and business functions.

Data Engineering 52

Data Engineering Engineering Data Strategy 52

Altexsoft

APRIL 22, 2020

So, along with data scientists who create algorithms, there are data engineers, the architects of data platforms. In this article we’ll explain what a data engineer is, the field of their responsibilities, skill sets, and general role description. What is a data engineer?

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

Cloudera

APRIL 14, 2021

What is Cloudera Data Engineering (CDE) ? Cloudera Data Engineering is a serverless service for Cloudera Data Platform (CDP) that allows you to submit jobs to auto-scaling virtual clusters. Refer to the following cloudera blog to understand the full potential of Cloudera Data Engineering. .

Data Engineering 83

Data Engineering Engineering Data Serverless 83

CIO

DECEMBER 22, 2022

DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and organizational structures to support the data-focused enterprise. What is DataOps?

Analytics 325

Analytics Data Engineering Artificial Inteligence Machine Learning 325

Altexsoft

AUGUST 25, 2020

That’s why a data specialist with big data skills is one of the most sought-after IT candidates. Data Engineering positions have grown by half and they typically require big data skills. Data engineering vs big data engineering. Big data processing. maintaining data pipeline.

Big Data 75

Big Data Data Engineering Engineering Data 75

Netflix Tech

JUNE 1, 2021

Data Engineers of Netflix?—?Interview Interview with Samuel Setegne Samuel Setegne This post is part of our “Data Engineers of Netflix” interview series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. What drew you to Netflix?

Data Engineering 52

Data Engineering Engineering Data Culture 52

CIO

SEPTEMBER 19, 2024

The challenge is that these architectures are convoluted, requiring multiple models, advanced RAG [retrieval augmented generation] stacks, advanced data architectures, and specialized expertise.” Reinventing the wheel is indeed a bad idea when it comes to complex systems like agentic AI architectures,” he says.

CTO Coach 345

CTO Coach Artificial Inteligence Fractional CTO Open Source 345

Mobilunity

AUGUST 3, 2021

The cloud offers excellent scalability, while graph databases offer the ability to display incredible amounts of data in a way that makes analytics efficient and effective. Who is Big Data Engineer? Big Data requires a unique engineering approach. Big Data Engineer vs Data Scientist.

Big Data 52

Big Data Data Engineering Engineering Data 52

Cloudera

AUGUST 30, 2022

Modern data architectures. To eliminate or integrate these silos, the public sector needs to adopt robust data management solutions that support modern data architectures (MDAs). Towards Data Science ). Deploying modern data architectures. Forrester ).

Architecture 79

Architecture Data Artificial Inteligence Artificial Intelligence 79

CIO

JUNE 23, 2023

Not only should the data strategy be cognizant of what’s in the IT and business strategies, it should also be embedded within those strategies as well, helping them unlock even more business value for the organization.

Strategy 290

Strategy Technical Review Data Software Review 290

Cloudera

JANUARY 12, 2018

I mentioned in an earlier blog titled, “Staffing your big data team, ” that data engineers are critical to a successful data journey. That said, most companies that are early in their journey lack a dedicated engineering group. Image 1: Data Engineering Skillsets.

Data Engineering 53

Data Engineering Big Data Engineering Data 53

Altexsoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two. What data mesh IS.

Architecture 52

Architecture Data Analytics Data Engineering 52

Dzone - DevOps

SEPTEMBER 6, 2024

Considering data engineering and data science, Astro and Apache Airflow rise to the top as important tools used in the management of these data workflows. This article compares Astro and Apache Airflow, explaining their architecture, features, scalability, usability, community support, and integration capabilities.

Comparison 67

Comparison Microservices Data Engineering Software Development 67

Abhishek Tiwari

FEBRUARY 26, 2020

The evolution of your technology architecture should depend on the size, culture, and skill set of your engineering organization. There are no hard-and-fast rules to figure out interdependency between technology architecture and engineering organization but below is what I think can really work well for product startup.

Architecture 81

Architecture MVC Engineering Technology 81

CIO

MAY 21, 2024

In the past, to get at the data, engineers had to plug a USB stick into the car after a race, download the data, and upload it to Dropbox where the core engineering team could then access and analyze it. You can monitor and act on the data and you can set thresholds.”

Data 317

Data Azure Engineering Analytics 317

CIO

AUGUST 2, 2023

So Thermo Fisher Scientific CIO Ryan Snyder and his colleagues have built a data layer cake based on a cascading series of discussions that allow IT and business partners to act as one team. Martha Heller: What are the business drivers behind the data architecture ecosystem you’re building at Thermo Fisher Scientific?

Data 246

Data Architecture Government Strategy 246

Altexsoft

AUGUST 29, 2023

Data lakes emerged as expansive reservoirs where raw data in its most natural state could commingle freely, offering unprecedented flexibility and scalability. This article explains what a data lake is, its architecture, and diverse use cases. Watch our video explaining how data engineering works.

Architecture 52

Architecture Data Storage Machine Learning 52

CIO

AUGUST 7, 2023

While the changes to the tech stack are minimal when simply accessing gen AI services, CIOs will need to be ready to manage substantial adjustments to the tech architecture and to upgrade data architecture. Shapers want to develop proprietary capabilities and have higher security or compliance needs.

Generative AI 246

Generative AI Off-The-Shelf Architecture Infrastructure 246

CIO

MAY 30, 2024

The course covers principles of generative AI, data acquisition and preprocessing, neural network architectures, natural language processing, image and video generation, audio synthesis, and creative AI applications. Upon completing the learning modules, you will need to pass a chartered exam to earn the CGAI designation.

Generative AI 344

Generative AI Artificial Inteligence Programming Azure 344

CIO

APRIL 27, 2023

The demand for specialized skills has boosted salaries in cybersecurity, data, engineering, development, and program management. Solutions architect Solutions architects are responsible for building, developing, and implementing systems architecture within an organization, ensuring that they meet business or customer needs.

Technical Review 290

Technical Review Software Review Systems Review Software Engineering 290

CIO

NOVEMBER 7, 2024

It covers essential topics like artificial intelligence, our use of data models, our approach to technical debt, and the modernization of legacy systems. We explore the essence of data and the intricacies of data engineering. I think we’re very much on our way.

Artificial Inteligence 300

Artificial Inteligence Development Generative AI Artificial Intelligence 300

TechCrunch

FEBRUARY 2, 2022

But, as RudderStack CEO Soumyadeb Mitra argued when I talked to him ahead of today’s announcement, most of the existing customer data pipeline solutions were built for selling to marketing teams, using architectures that make it harder to build the advanced applications that businesses are now looking for.

Data 204

Data Machine Learning Artificial Inteligence Architecture 204

Xebia

FEBRUARY 3, 2023

You start out really small, perhaps a Proof of Concept, a small app or data engineering pipeline. So it is a pytest plugin that helps you define (architectural) rules (archon means ruler, but it also sounds a bit like the arch in architecture ) for your application. Hence, minimal effort is put into architecture.

How To 130

How To Architecture Data Engineering Applications 130

Altexsoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Traditional data warehouse platform architecture. Data lake architecture example.

Architecture 52

Architecture Data Storage Machine Learning 52

CIO

NOVEMBER 29, 2022

A sea of complexity For years, data ecosystems have gotten more complex due to discrete (and not necessarily strategic) data-platform decisions aimed at addressing new projects, use cases, or initiatives. Layering technology on the overall data architecture introduces more complexity. Data and cloud strategy must align.

Organization 278

Organization Technical Review Data Artificial Inteligence 278

CIO

JUNE 19, 2024

They may also ensure consistency in terms of processes, architecture, security, and technical governance. Our platform engineering teams, which support more than 200 applications, have innovated around automation,” says Bob Simms, former director of enterprise infrastructure delivery at the US Patent and Trademark Office (USPTO).

Weak Development Team 347

Weak Development Team Engineering UI/UX Software Development 347

O'Reilly Media - Ideas

DECEMBER 6, 2018

As the use of machine learning and analytics become more widespread, we’re beginning to see tools that enable data scientists and data engineers to scale and tackle many more problems and maintain more systems. Continue reading Tools for generating deep neural networks with efficient network architectures.

Network 56

Network Architecture Tools Artificial Inteligence 56