CIO

AUGUST 9, 2022

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. The data engineer role.

Data Engineering 197

Data Engineering Analytics Engineering Data 197

CIO

JANUARY 17, 2023

It shows in his reluctance to run his own servers but it’s perhaps most obvious in his attitude to data engineering, where he’s nearing the end of a five-year journey to automate or outsource much of the mundane maintenance work and focus internal resources on data analysis. It’s not a good use of our time either.”

Data Engineering 189

Data Engineering Engineering Data CTO Coach 189

Erik Bernhardsson

DECEMBER 15, 2020

It's a popular attitude among developers to rant about our tools and how broken things are. I had my first job as a software engineer in 1999, and in the last two decades I've seen software engineering changing in ways that have made us orders of magnitude more productive. The insatiable demand for software.

Software Engineering 325

Software Engineering Engineering Tools Software 325

CIO

MARCH 13, 2025

Gen AI-related job listings were particularly common in roles such as data scientists and data engineers, and in software development. Were building a department of AI engineering, mostly by bringing in people from data engineering and training them to work with gen AI and AI in general, says Daniel Avancini, Indiciums CDO.

Part-Time VPE 205

Part-Time VPE Weak Development Team Fractional VPE Fractional CTO 205

Xebia

JANUARY 19, 2023

The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. This book is as good for a project manager or any other non-technical role as it is for a computer science student or a data engineer.

Data Engineering 130

Data Engineering Engineering Data Technical Review 130

Cloudera

JULY 13, 2021

After the launch of CDP Data Engineering (CDE) on AWS a few months ago, we are thrilled to announce that CDE, the only cloud-native service purpose built for enterprise data engineers, is now available on Microsoft Azure. . Prerequisites for deploying CDP Data Engineering on Azure can be found here.

Data Engineering 127

Data Engineering Azure Engineering Enterprise 127

TechCrunch

NOVEMBER 18, 2021

There are three core roles involved in ML modeling, but each one has different motivations and incentives: Data engineers: Trained engineers excel at gleaning data from multiple sources, cleaning it and storing it in the right formats so that analysis can be performed. The proliferation of ML tools.

Enterprise 344

Enterprise Artificial Inteligence Data Engineering Data Center 344

CIO

DECEMBER 12, 2024

Seventy percent of those IT pros spend one to four hours a day remediating data issues, while 14% spend more than four hours each day, according to the survey. Theres a perspective that well just throw a bunch of data at the AI, and itll solve all of our problems, he says.

Data 201

Data Survey Artificial Inteligence Education 201

TechCrunch

OCTOBER 19, 2021

Mage , developing an artificial intelligence tool for product developers to build and integrate AI into apps, brought in $6.3 Founder Tommy Dang started the company at the end of 2020 after working together to build internal low-code tools at Airbnb. million in seed funding led by Gradient Ventures. Shirazi found that in Mage.

Artificial Inteligence 248

Artificial Inteligence Machine Learning Tools Technical Review 248

CIO

NOVEMBER 27, 2024

People : To implement a successful Operational AI strategy, an organization needs a dedicated ML platform team to manage the tools and processes required to operationalize AI models. The team should be structured similarly to traditional IT or data engineering teams.

Architecture 193

Architecture Artificial Inteligence Data Development Team Review 193

Netflix Tech

DECEMBER 14, 2023

Engineers from across the company came together to share best practices on everything from Data Processing Patterns to Building Reliable Data Pipelines. The result was a series of talks which we are now sharing with the rest of the Data Engineering community! In this video, Sr.

Data Engineering 106

Data Engineering Engineering Data Software Engineering 106

Xebia

OCTOBER 18, 2024

This creates the opportunity for combining lightweight tools like DuckDB with Unity Catalog. To get similar notebook integration, we have built a solution using Jupyter notebooks, a web-based tool for interactive computing. Dbt is a popular tool for transforming data in a data warehouse or data lake.

Open Source 162

Open Source AWS Government Technical Review 162

CIO

APRIL 23, 2025

The raw data can be streamed using a variety of methods, either batch or streaming (using a message broker such as Kafka). Platforms like Databricks offer built-in tools like autoloader to make this ingestion process seamless. Next, clean and organize the raw data. Silver layer: Clean and standardize.

Insurance 164

Insurance Artificial Inteligence Data Architecture 164

TechCrunch

DECEMBER 1, 2020

DevOps continues to get a lot of attention as a wave of companies develop more sophisticated tools to help developers manage increasingly complex architectures and workloads. “Users didn’t know how to organize their tools and systems to produce reliable data products.”

Tools 214

Tools Data Weak Development Team Big Data 214

TechCrunch

JUNE 17, 2021

Now, three alums that worked with data in the world of Big Tech have founded a startup that aims to build a “metrics store” so that the rest of the enterprise world — much of which lacks the resources to build tools like this from scratch — can easily use metrics to figure things out like this, too.

Metrics 247

Metrics Tools Data Big Data 247

CIO

DECEMBER 20, 2024

Provide user interfaces for consuming data. Beyond breaking down silos, modern data architectures need to provide interfaces that make it easy for users to consume data using tools fit for their jobs. Choose the right tools and technologies.

Architecture 183

Architecture Data Fractional CTO Technical Review 183

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. Data pipelines are composed of multiple steps with dependencies and triggers. New in 2021.

Data Engineering 118

Data Engineering Technical Review Software Review Engineering 118

CIO

MARCH 13, 2025

By early 2024, according to a report from Microsoft , 75% of employees reported using AI at work, with 80% of that population using tools not sanctioned by their employers. People feel overwhelmed; they need solutions fast, and if we dont give them the right tools, theyll find their own.

Company 186

Company Generative AI Insurance Education 186

CIO

JANUARY 3, 2025

At the same time, the scale of observability data generated from multiple tools exceeds human capacity to manage. With situational insights, IT operations, SREs, DevOps, and platform engineering teams can reduce time to remediation and quickly restore services with a pre-built set of automations.

Organization 158

Organization Artificial Intelligence Artificial Inteligence DevOps 158

CIO

NOVEMBER 19, 2024

The challenges of integrating data with AI workflows When I speak with our customers, the challenges they talk about involve integrating their data and their enterprise AI workflows. The core of their problem is applying AI technology to the data they already have, whether in the cloud, on their premises, or more likely both.

Artificial Inteligence 174

Artificial Inteligence Engineering Data Storage 174

CIO

FEBRUARY 19, 2025

This is a use case thats been rolled out widely, he says, though not all tools are available to all employees. With these paid versions, our data remains secure within our own tenant, he says. Today, all customer service representatives use the gen AI tool, which is over 40,000 people.

Google Cloud 206

Google Cloud Survey CTO Coach Software Development 206

Xebia

APRIL 9, 2025

For example, events such as Twitters rebranding to X, and PySparks rise in the data engineering realm over Spark have all contributed to this decline. In my opinion, sbt (Simple Build Tool) is a perfect example of this evolution. Various business decisions have altered its public perception.

Systems Review 130

Systems Review Programming Technical Review Engineering 130

CIO

DECEMBER 10, 2024

to GPT-o1, the list keeps growing, along with a legion of new tools and platforms used for developing and customizing these models for specific use cases. To integrate AI into enterprise workflows, we must first do the foundation work to get our clients data estate optimized, structured, and migrated to the cloud. From Llama3.1

Artificial Inteligence 174

Artificial Inteligence Off-The-Shelf Insurance Analytics 174

CIO

APRIL 1, 2025

Job titles like data engineer, machine learning engineer, and AI product manager have supplanted traditional software developers near the top of the heap as companies rush to adopt AI and cybersecurity professionals remain in high demand. Theres real hand-holding that needs to be done.

Marketing 152

Marketing Software Development Software Development 152

Cloudera

FEBRUARY 14, 2022

When we introduced Cloudera Data Engineering (CDE) in the Public Cloud in 2020 it was a culmination of many years of working alongside companies as they deployed Apache Spark based ETL workloads at scale. Each unlocking value in the data engineering workflows enterprises can start taking advantage of. Usage Patterns.

Data Engineering 113

Data Engineering Engineering Data Storage 113

CIO

DECEMBER 4, 2024

And since the latest hot topic is gen AI, employees are told that as long as they don’t use proprietary information or customer code, they should explore new tools to help develop software. These tools help people gain theoretical knowledge,” says Raj Biswas, global VP of industry solutions.

Recruiting 202

Recruiting Artificial Inteligence Programming Technology 202

Xebia

FEBRUARY 28, 2025

The development- and operations world differ in various aspects: Development ML teams are focused on innovation and speed Dev ML teams have roles like Data Scientists, Data Engineers, Business owners. Cloud providers have answered the market need for better tooling in the Machine Learning space. That is massively useful.

Technical Review 182

Technical Review Weak Development Team Artificial Inteligence Machine Learning 182

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

The Crazy Programmer

NOVEMBER 6, 2021

They also use tools like Amazon Web Services and Microsoft Azure. Big Data Engineer. Another highest-paying job skill in the IT sector is big data engineering. And as a big data engineer, you need to work around the big data sets of the applications. AI or Artificial Intelligence Engineer.

Artificial Inteligence 290

Artificial Inteligence Blockchain Software Review Artificial Intelligence 290

Xebia

NOVEMBER 21, 2024

dbt (data build tool) has seen increasing use in recent years as a tool to transform data in data warehouses. of the repository, while other times this is in an external tool like Confluence or Notion. As with any new tool, one question that is commonly asked is about its speed. But what about dbt?

Weak Development Team 130

Weak Development Team Testing Analytics Engineering 130

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

Operating System 233

Operating System Technical Review Analytics Systems Review 233

Altexsoft

JULY 23, 2020

introduces available tools and platforms to automate MLOps steps. It facilitates collaboration between a data science team and IT professionals, and thus combines skills, techniques, and tools used in data engineering, machine learning, and DevOps — a predecessor of MLOps in the world of software development.

Artificial Inteligence 145

Artificial Inteligence Machine Learning DevOps Tools 145

Dzone - DevOps

DECEMBER 31, 2024

MLOps, or Machine Learning Operations, is a set of practices that combine machine learning (ML), data engineering, and DevOps to streamline and automate the end-to-end ML model lifecycle. MLOps is an essential aspect of the current data science workflows.

Machine Learning 96

Machine Learning Artificial Inteligence Scalability Data Engineering 96

TechCrunch

JULY 12, 2022

But building data pipelines to generate these features is hard, requires significant data engineering manpower, and can add weeks or months to project delivery times,” Del Balso told TechCrunch in an email interview. Systems use features to make their predictions. This is a difficult transition for enterprises.

Artificial Inteligence 249

Artificial Inteligence Machine Learning Marketing Data Engineering 249

TechCrunch

JUNE 22, 2022

CloudQuery CEO and co-founder Yevgeny Pats helped launch the startup because he needed a tool to give him visibility into his cloud infrastructure resources, and he couldn’t find one on the open market. He built his own SQL-based tool to help understand exactly what resources he was using, based on data engineering best practices.

Infrastructure 206

Infrastructure Cloud Open Source Data Engineering 206

Xebia

DECEMBER 23, 2024

Modern Pay-As-You-Go Data Platforms: Easy to Start, Challenging to Control It’s Easier Than Ever to Start Getting Insights into Your Data The rapid evolution of data platforms has revolutionized the way businesses interact with their data.

Data 130

Data Storage Culture Resources 130

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 195

Analytics Data Engineering Artificial Inteligence Machine Learning 195