Netflix Tech

OCTOBER 28, 2021

Data Engineers of Netflix?—?Interview Interview with Pallavi Phadnis This post is part of our “ Data Engineers of Netflix ” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Pallavi Phadnis is a Senior Software Engineer at Netflix.

Data Engineering 69

Data Engineering Engineering Data Software Engineering 69

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. Feature engineering.

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Cloudera

SEPTEMBER 17, 2020

With growing disparate data across everything from edge devices to individual lines of business needing to be consolidated, curated, and delivered for downstream consumption, it’s no wonder that data engineering has become the most in-demand role across businesses — growing at an estimated rate of 50% year over year.

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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

O'Reilly Media - Ideas

APRIL 9, 2019

A few months ago, I wrote about the differences between data engineers and data scientists. An interesting thing happened: the data scientists started pushing back, arguing that they are, in fact, as skilled as data engineers at data engineering. Data engineering is not in the limelight.

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Data Engineering Engineering Data Technical Review 111

Cloudera

OCTOBER 19, 2021

Airflow has been adopted by many Cloudera Data Platform (CDP) customers in the public cloud as the next generation orchestration service to setup and operationalize complex data pipelines. This makes our pipeline engine flexible to support multitude of orchestration services. Using the special syntax {{.}}

Data Engineering 116

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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 81

Data Engineering Engineering Data Serverless 81

Cloudera

APRIL 30, 2021

Apache Spark is now widely used in many enterprises for building high-performance ETL and Machine Learning pipelines. Cloudera Data Engineering (CDE) is a cloud-native service purpose-built for enterprise data engineering teams. Here is an example showing a simple PySpark program querying an ACID table.

Data Engineering 62

Data Engineering Engineering Data Software Review 62

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?

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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

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Cloudera

AUGUST 20, 2020

This blog illustrates how Cloudera Data Engineering (CDE), using Apache Spark , can be used to produce reports based on the PPP data while addressing each of the challenges outlined above. A mock scenario for the Texas Legislative Budget Board (LBB) is set up below to help a data engineer manage and analyze the PPP data.

Data Engineering 62

Data Engineering Engineering Programming Data 62

TechCrunch

OCTOBER 13, 2022

Data engineers have a big problem. Almost every team in their business needs access to analytics and other information that can be gleaned from their data warehouses, but only a few have technical backgrounds. The New York-based startup announced today that it has raised $7.6

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Operating System Technical Review Analytics Systems Review 233

TechCrunch

JULY 12, 2022

Machine learning can provide companies with a competitive advantage by using the data they’re collecting — for example, purchasing patterns — to generate predictions that power revenue-generating products (e.g. e-commerce recommendations). “It also enables companies to generate more accurate predictions.

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Altexsoft

APRIL 14, 2021

Within such an approach, a machine learning model tries to find any similarities, differences, patterns, and structure in data by itself. Let’s get back to our children-learn-from-their-own-experiences example from the intro to make unsupervised learning easier to digest. Unlabeled data is much easier and faster to get.

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CIO

DECEMBER 6, 2023

Meanwhile, a global vendor with resources deployed around the world, FPT Software’s ‘best shore’ model for example, can provide services to its clients optimally wherever they are. Despite logistics challenges caused by the global pandemic, the company managed to rapidly scale up its team to over 1,000 people in a period of only 11 months.

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Airlines Innovation Automotive Resources 290

CIO

FEBRUARY 15, 2024

But to achieve Henkel’s digital vision, Nilles would need to attract data scientists, data engineers, and AI experts to an industry they might not otherwise have their eye on. Whoever built the LLM that WeChat, for example, uses to answer that query is going to have an advantage in the marketplace. “If

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Xebia

MAY 16, 2023

Data Engineers were tempted by the pressure of the moment to give up on testing all together. There was no need for generating your own data; just take a percentage of production data. In many cases, these tasks ended up on the shoulders of the Data Engineers themselves. Overly restrictive governance.

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Testing How To Data Engineering Engineering 130

CIO

JUNE 7, 2022

Data analytics has become increasingly important in the enterprise as a means for analyzing and shaping business processes and improving decision-making and business results. Diagnostic analytics uses data (often generated via descriptive analytics) to discover the factors or reasons for past performance.

Analytics 334

Analytics Data Analysis Business Analytics 334

Cloudera

JANUARY 15, 2021

With the ability to quickly provision on-demand and the lower fixed and administrative costs, the costs of operating a cloud data warehouse are driven mostly by the price-performance of the specific data warehouse platform. CDW is one of several managed services that comprise the broader Cloudera Data Platform (CDP).

Performance 93

Performance Cloud Data Storage 93

TechCrunch

JULY 25, 2022

The funding will be used to add more features to Omni, including a recruitment module by the third quarter and a performance enhancement module by the end of the year. The company was founded in 2021 by Brian Ip, a former Goldman Sachs executive, and data engineer YC Chan. Localizing for each market can be quite complicated.

Recruiting 224

Recruiting Technical Review Software Review Systems Review 224

CIO

MARCH 12, 2024

Gen AI is playing a role in assisting with performing code reviews and early detection of potential issues.” Additionally, we are looking into training LLMs [large language models] on our code base to unlock further productivity boosts for our developers and data engineers. One example is with document search and summarization.

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Software Development Software Review Weak Development Team Software 328

CIO

AUGUST 5, 2022

Data visualization is the presentation of data in a graphical format such as a plot, graph, or map to make it easier for decision makers to see and understand trends, outliers, and patterns in data. Maps and charts were among the earliest forms of data visualization. What are some data visualization examples?

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Data Analytics Travel Business Intelligence 320

CIO

SEPTEMBER 18, 2023

The complex tool comprises a workflow engine, robotic process automation, and a data engineering framework that supports more than nine of Verizon’s legacy network systems. Network Alpha Factory also provides data intelligence and the ability to decommission legacy devices.

Telecommunications 262

Telecommunications Network Systems Review Software Review 262

Xebia

DECEMBER 22, 2023

Example: Showing the statuses, the transitions between them with the average time between them. Some examples: It’s not uncommon for us to observe a ‘testing’ status to take longer to complete than the actual implementation, often this relates to hand-offs, poor testability, or an inefficient test strategy.

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Weak Development Team Data Trends Software Review 244

CIO

NOVEMBER 9, 2022

But experienced data analysts and data scientists can be expensive and difficult to find and retain. Self-service analytics typically involves tools that are easy to use and have basic data analytics capabilities. Self-service analytics typically involves tools that are easy to use and have basic data analytics capabilities.

Analytics 341

Analytics Metrics Government Business Intelligence 341

CIO

APRIL 12, 2023

Real-time AI brings together streaming data and machine learning algorithms to make fast and automated decisions; examples include recommendations, fraud detection, security monitoring, and chatbots. Complexity across the data ecosystem impacts the speed to perform these updates accurately.

Artificial Inteligence 349

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CIO

FEBRUARY 14, 2023

Here are some examples: Fraud It’s critical to identify bad actors using high-quality AI models and data Product recommendations It’s important to stay competitive in today’s ever-expanding online ecosystem with excellent product recommendations and aggressive, responsive pricing against competitors.

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CIO

JULY 15, 2022

This enabled the team to select one engine to carry forward and to identify capabilities that the other engines offered that DTN should consider reimplementing in its selected platform, Ewe says. For example, Ewe didn’t want to lose the data those other engines worked with.

Systems Review 279

Systems Review Fractional CTO System Development Team Review 279

CIO

AUGUST 2, 2023

What are some examples of data solutions in each of those buckets? we’re putting sensors across our manufacturing processes, which give us vast sums of data our leaders use to rethink those processes. Microscopy and gene sequencing, for example, generate a very large amount of data, which our customers are trying to analyze.

Data 230

Data Architecture Government Strategy 230

Xebia

JULY 19, 2023

Take, for example, the code bug that bankrupted Knight Capital Group by making them lose USD 460M in less than an hour. AI systems are even more vulnerable as, besides code, they leverage data and algorithms, so you need to test all the components to avoid whammies. It has now become a prime example of why to test software.

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Artificial Inteligence Systems Review Testing System 130

Cloudera

NOVEMBER 17, 2021

You know the one, the mathematician / statistician / computer scientist / data engineer / industry expert. Some companies are starting to segregate the responsibilities of the unicorn data scientist into multiple roles (data engineer, ML engineer, ML architect, visualization developer, etc.),

Machine Learning 123

Machine Learning Artificial Inteligence Hotels Data Engineering 123

CIO

DECEMBER 6, 2023

Settling the months-long writers and actors strikes in Hollywood in early November required the studios to make concessions limiting the ways AI tools can be used to replace human writers and performers. That could go badly wrong if, for example, someone shares details of a family illness or losing a pet.

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Generative AI Artificial Inteligence Technical Review Weak Development Team 332

CIO

FEBRUARY 13, 2023

For example, New York-Presbyterian Hospital, which has a network of hospitals and about 2,600 beds, is deploying over 150 AI and VR/AR projects this year across all clinical specialties. For example, the hospital wants the ability to look at imaging and pathology data so staff can better diagnose patients faster and quicker, he says.

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Budget Artificial Inteligence Technical Review VR 363

CIO

NOVEMBER 7, 2023

It’s easy to see why breaking down barriers to data access would be appealing. But what exactly is involved in breaking down data silos? Here are a few examples of organizations that have found the answers. Companies should also incorporate data discovery, Higginson says. What are the challenges and potential rewards?

Data 354

Data Artificial Inteligence Architecture Analytics 354

Kentik

APRIL 12, 2023

With modern networks’ increasing complexity and scale, it has become essential to collect and analyze data from various sources to gain insights into network performance, security, and availability. DataOps team roles In a DataOps team, several key roles work together to ensure the data pipeline is efficient, reliable, and scalable.

Network 52

Network Data Engineering Machine Learning Artificial Inteligence 52

Cloudera

NOVEMBER 28, 2023

With its rise in popularity generative AI has emerged as a top CEO priority, and the importance of performant, seamless, and secure data management and analytics solutions to power those AI applications is essential. This means you can expect simpler data management and drastically improved productivity for your business users.

Data 81

Data Scalability Analytics Quality Assurance 81

Kentik

APRIL 25, 2016

Database design for Web-scale ad hoc queries In a previous post, Beyond Hadoop , we looked at how the MapReduce approach to database design runs up against performance limits when queries can’t be defined in advance, and we introduced Google’s response to those limits: Dremel/BigQuery.

Data Engineering 40

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