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.

Data Engineering 112

Data Engineering Engineering Data Technical Review 112

Netflix Tech

JUNE 20, 2024

A summary of sessions at the first Data Engineering Open Forum at Netflix on April 18th, 2024 The Data Engineering Open Forum at Netflix on April 18th, 2024. At Netflix, we aspire to entertain the world, and our data engineering teams play a crucial role in this mission by enabling data-driven decision-making at scale.

Data Engineering 82

Data Engineering Engineering Data Generative AI 82

CIO

OCTOBER 9, 2024

The data preparation process should take place alongside a long-term strategy built around GenAI use cases, such as content creation, digital assistants, and code generation. Known as data engineering, this involves setting up a data lake or lakehouse, with their data integrated with GenAI models.

Strategy 215

Strategy Data Artificial Inteligence Storage 215

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 Machine Learning 98

CIO

OCTOBER 13, 2023

Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes. Application data architect: The application data architect designs and implements data models for specific software applications.

Data 199

Data Data Engineering Database Administration Artificial Inteligence 199

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 72

Data Engineering Engineering Data Software Engineering 72

TechCrunch

MAY 24, 2022

Preql founders Gabi Steele and Leah Weiss were data engineers in the early days at WeWork. They later opened their own consultancy to help customers build data stacks, and they saw a stubborn consistency in the types of information their clients needed. That’s really what motivates us.

Data 202

Data Metrics Data Engineering Storage 202

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

TechCrunch

APRIL 12, 2022

“We [founded Union] because we believe that machine learning and data workflows are fundamentally different from software deployments. This is because software is more precise with a slower lifecycle while machine learning and data workflows start off being experimental and may need to be quickly productionized.”

Artificial Inteligence 202

Artificial Inteligence Machine Learning Open Source Biotech 202

CIO

JUNE 19, 2024

BSH’s previous infrastructure and operations teams, which supported the European appliance manufacturer’s application development groups, simply acted as suppliers of infrastructure services for the software development organizations. Our gap was operational excellence,” he says. “We

Weak Development Team 208

Weak Development Team Engineering UI/UX Software Development 208

CIO

SEPTEMBER 2, 2022

If you’re an IT pro looking to break into the finance industry, or a finance IT leader wanting to know where hiring will be most competitive, here are the top 10 in-demand tech jobs in finance, according to data from Dice. Software engineer. Full-stack software engineer. Back-end software engineer.

Software Engineering 148

Software Engineering Data Engineering DevOps AWS 148

CIO

AUGUST 31, 2022

If you’re an IT pro looking to break into the finance industry, or a finance IT leader wanting to know where hiring will be most competitive, here are the top 10 in-demand tech jobs in finance, according to data from Dice. Software engineer. Full-stack software engineer. Back-end software engineer.

Software Engineering 148

Software Engineering Data Engineering DevOps AWS 148

Hu's Place - HitachiVantara

JANUARY 15, 2019

For lack of similar capabilities, some of our competitors began implying that we would no longer be focused on the innovative data infrastructure, storage and compute solutions that were the hallmark of Hitachi Data Systems. A REST API is built directly into our VSP storage controllers.

Systems Review 72

Systems Review Storage System Software Review 72

TechCrunch

DECEMBER 1, 2020

That will include more remediation once problems are identified: that is, in addition to identifying issues, engineers will be able to start automatically fixing them, too. And as data workloads continue to grow in size and use, they continue to become ever more complex. Doing so manually can be time-consuming, if not impossible.

Tools 214

Tools Data Weak Development Team Big Data 214

CIO

JUNE 22, 2023

Every business unit has a stake in the IT services, apps, networks, hardware, and software needed to meet business goals and objectives, and many of them are hiring their own technologists. It’s an industry that handles critical, private, and sensitive data so there’s a consistent demand for cybersecurity and data professionals.

Industry 183

Industry UI/UX Telecommunications Quality Assurance 183

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

TechCrunch

MAY 18, 2022

We agreed that the only viable solution was to have internal teams with domain expertise be responsible for annotating and curating training data. ” Software developers Malyuk, Maxim Tkachenko, and Nikolay Lyubimov co-founded Heartex in 2019. Who can provide the best results other than your own experts?”

Open Source 203

Open Source Weak Development Team Data Artificial Inteligence 203

AWS Machine Learning - AI

NOVEMBER 15, 2024

The first data source connected was an Amazon Simple Storage Service (Amazon S3) bucket, where a 100-page RFP manual was uploaded for natural language querying by users. The data source allowed accurate results to be returned based on indexed content. Joel Elscott is a Senior Data Engineer on the Principal AI Enablement team.

Generative AI 111

Generative AI AWS Groups Artificial Inteligence 111

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

Erik Bernhardsson

DECEMBER 6, 2022

I then spent six years as a CTO, although I managed the data team directly for a long time and would occasionally write some data code. Data 1 strikes me a a discipline that deserves a bit more love. Data as its own discipline. Whether you're running SQL or doing ML, it's often pointless to do that on non-production data.

CTO Coach 242

CTO Coach Fractional CTO Software Engineering Serverless 242

Altexsoft

NOVEMBER 28, 2019

The number of business domains the data comes from can be large. Thanks to Earth there is a software for everything. Let’s break them down: A data source layer is where the raw data is stored. Those are any of your databases, cloud-storages, and separate files filled with unstructured data.

Business Intelligence 22

Business Intelligence Development Technical Review Storage 22

CIO

JUNE 7, 2022

Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. Data analytics and data science are closely related.

Analytics 203

Analytics Data Analysis Business Analytics 203

Altexsoft

AUGUST 21, 2019

Data obsession is all the rage today, as all businesses struggle to get data. But, unlike oil, data itself costs nothing, unless you can make sense of it. Dedicated fields of knowledge like data engineering and data science became the gold miners bringing new methods to collect, process, and store data.

Development 44

Development Software Engineering Data Engineering Architecture 44

CIO

FEBRUARY 14, 2023

Demand for real-time AI is accelerating Software applications enable businesses to fuel their processes and revolutionize the customer experience. Many companies today struggle with legacy software applications and complex environments, which leads to difficulty in integrating new data elements or services.

Artificial Inteligence 174

Artificial Inteligence Strategy Data Machine Learning 174

Altexsoft

JANUARY 14, 2021

Snowflake, Redshift, BigQuery, and Others: Cloud Data Warehouse Tools Compared. From simple mechanisms for holding data like punch cards and paper tapes to real-time data processing systems like Hadoop, data storage systems have come a long way to become what they are now. Is it still so?

Backup 115

Backup Azure Software Review Architecture 115

O'Reilly Media - Ideas

JANUARY 8, 2019

The demand for data skills (“the sexiest job of the 21st century”) hasn’t dissipated. LinkedIn recently found that demand for data scientists in the US is “off the charts,” and our survey indicated that the demand for data scientists and data engineers is strong not just in the US but globally.

Trends 108

Trends Data Machine Learning Artificial Inteligence 108

Hu's Place - HitachiVantara

APRIL 11, 2019

Few if any data management frameworks are business focused, to not only promote efficient use of data and allocation of resources, but also to curate the data to understand the meaning of the data as well as the technologies that are applied to the data so that data engineers can move and transform the essential data that data consumers need.

Data Engineering 81

Data Engineering Machine Learning Artificial Inteligence Technical Review 81

Cloudera

APRIL 22, 2021

Today’s enterprise data analytics teams are constantly looking to get the best out of their platforms. Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Supports Disaggregation of compute and storage.

Data 101

Data Storage Architecture Big Data 101

InfoWorld

FEBRUARY 9, 2024

Microsoft Fabric is an end-to-end, software-as-a-service (SaaS) platform for data analytics. It is built around a data lake called OneLake, and brings together new and existing components from Microsoft Power BI, Azure Synapse, and Azure Data Factory into a single integrated environment.

Big Data 78

Big Data Data Azure Google Cloud 78

Altexsoft

DECEMBER 4, 2020

Hardware and software become obsolete sooner than ever before. So data migration is an unavoidable challenge each company faces once in a while. Transferring data from one computer environment to another is a time-consuming, multi-step process involving such activities as planning, data profiling, testing, to name a few.

Software Review 69

Software Review Software Data Technical Review 69

CIO

JUNE 14, 2023

Going from petabytes (PB) to exabytes (EB) of data is no small feat, requiring significant investments in hardware, software, and human resources. Start with storage. Before you can even think about analyzing exabytes worth of data, ensure you have the infrastructure to store more than 1000 petabytes! Much larger.

Data 97

Data Scalability Storage Big Data 97

Confluent

FEBRUARY 6, 2019

This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. Impedance mismatch between data scientists, data engineers and production engineers. For now, we’ll focus on Kafka.

Machine Learning 107

Machine Learning Artificial Inteligence Scalability Data Engineering 107

Xebia

OCTOBER 23, 2024

ADF is a Microsoft Azure tool widely utilized for data ingestion and orchestration tasks. A typical scenario for ADF involves retrieving data from a database and storing it as files in an online blob storage, which applications can utilize downstream. It will require a basic understanding of the concepts used in ADF.

Azure 130

Azure Software Review Technical Review Resources 130

Xebia

JUNE 9, 2023

How it started out When installing software on my new MacBook Pro M2, I started out with a fresh install instead of restoring from a back-up. This worked out great until I tried to follow a tutorial written by a colleague which used the Azure Python SDK to create a dataset and upload it to an Azure storage account. Well not really.

Azure 130

Azure Architecture Software Storage 130

AWS Machine Learning - AI

JULY 15, 2024

Data intake A user uploads photos into Mixbook. The raw photos are stored in Amazon Simple Storage Service (Amazon S3). The data intake process involves three macro components: Amazon Aurora MySQL-Compatible Edition , Amazon S3, and AWS Fargate for Amazon ECS. AWS enables us to scale the innovations our customers love most.

Generative AI 110

Generative AI Artificial Inteligence AWS Technical Review 110

Cloudera

MAY 18, 2021

Second, since IaaS deployments replicated the on-premises HDFS storage model, they resulted in the same data replication overhead in the cloud (typical 3x), something that could have mostly been avoided by leveraging modern object store. Storage costs. using list pricing of $0.72/hour hour using a r5d.4xlarge

Cloud 86

Cloud Technical Review Storage Backup 86

Altexsoft

FEBRUARY 11, 2023

Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. What is the main difference between a data architect and a data engineer? By the way, we have a video dedicated to the data engineering working principles.

Data 87

Data Data Engineering Big Data Architecture 87