CIO

FEBRUARY 14, 2023

Organizations have balanced competing needs to make more efficient data-driven decisions and to build the technical infrastructure to support that goal. Many companies today struggle with legacy software applications and complex environments, which leads to difficulty in integrating new data elements or services.

Artificial Inteligence 290

Artificial Inteligence Strategy Data Machine Learning 290

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

Altexsoft

MAY 27, 2020

Analysis of more than 16.000 papers on data science by MIT technologies shows the exponential growth of machine learning during the last 20 years pumped by big data and deep learning advancements. Reasonably, with the access to data, anyone with a computer can train a machine learning model today.

Machine Learning 89

Machine Learning Artificial Inteligence Architecture Training 89

O'Reilly Media - Ideas

JUNE 4, 2019

Get hands-on training in Docker, microservices, cloud native, Python, machine learning, and many other topics. Learn new topics and refine your skills with more than 219 new live online training courses we opened up for June and July on the O'Reilly online learning platform. Azure Architecture: Best Practices , June 28.

Course 64

Course Training Artificial Inteligence Software Review 64

CIO

JANUARY 6, 2023

But 86% of technology managers also said that it’s challenging to find skilled professionals in software and applications development, technology process automation, and cloud architecture and operations. Companies will have to be more competitive than ever to land the right talent in these high-demand areas.

LAN 358

LAN Systems Administration How To WAN 358

CIO

SEPTEMBER 2, 2022

Full-stack software engineers are essentially high-level software engineers who are focused on designing, testing, and implementing software applications. Job duties include helping plan software projects, designing software system architecture, and designing and deploying web services, applications, and APIs. Data engineer.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

CIO

AUGUST 31, 2022

Full-stack software engineers are essentially high-level software engineers who are focused on designing, testing, and implementing software applications. Job duties include helping plan software projects, designing software system architecture, and designing and deploying web services, applications, and APIs. Data engineer.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

Confluent

JULY 11, 2019

Simon Aubury is a data geek on all things from databases to event streaming, architecture, IoT, and cloud. A data engineer architect from Sydney, Australia, he lives with his wife, two kids, and a grumpy cat. We can’t wait to see what amazing projects are created with KSQL by the fantastic community of developers.

Training 83

Training Course Exercises IoT 83

CIO

MARCH 12, 2024

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. As gen AI becomes increasingly prevalent, “we’re seeing value in having people who are cross-trained with these tools,” Lanehart says. “We

Software Development 328

Software Development Software Review Weak Development Team Software 328

TechCrunch

MAY 18, 2022

. “At the time, we all worked at different companies and in different industries yet shared the same struggle with model accuracy due to poor-quality training data. We agreed that the only viable solution was to have internal teams with domain expertise be responsible for annotating and curating training data.

Open Source 203

Open Source Weak Development Team Artificial Inteligence Data 203

Altexsoft

FEBRUARY 11, 2023

This specialist works closely with people on both business and IT sides of a company to understand the current needs of the stakeholders and help them unlock the full potential of data. To get a better understanding of a data architect’s role, let’s clear up what data architecture is. Feel free to enjoy it.

Data 87

Data Data Engineering Big Data Architecture 87

AWS Machine Learning - AI

JANUARY 26, 2024

Understanding and addressing LLM vulnerabilities, threats, and risks during the design and architecture phases helps teams focus on maximizing the economic and productivity benefits generative AI can bring. Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications.

Artificial Inteligence 116

Artificial Inteligence Generative AI Security Applications 116

O'Reilly Media - Ideas

JUNE 5, 2019

Get hands-on training in Docker, microservices, cloud native, Python, machine learning, and many other topics. Learn new topics and refine your skills with more than 219 new live online training courses we opened up for June and July on the O'Reilly online learning platform. Azure Architecture: Best Practices , June 28.

Course 49

Course Training Artificial Inteligence Software Review 49

O'Reilly Media - Ideas

MAY 1, 2019

Get hands-on training in machine learning, blockchain, cloud native, PySpark, Kubernetes, and many other topics. Learn new topics and refine your skills with more than 160 new live online training courses we opened up for May and June on the O'Reilly online learning platform. Data science and data tools.

Course 45

Course Training Artificial Inteligence Machine Learning 45

Confluent

FEBRUARY 6, 2019

This structure worked well for production training and deployment of many models but left a lot to be desired in terms of overhead, flexibility, and ease of use, especially during early prototyping and experimentation [where Notebooks and Python shine]. Impedance mismatch between data scientists, data engineers and production engineers.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

Altexsoft

JUNE 29, 2021

MLEs are usually a part of a data science team which includes data engineers , data architects, data and business analysts, and data scientists. Who does what in a data science team. Machine learning engineers are relatively new to data-driven companies.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

Mentormate

JANUARY 11, 2022

Sure, you might get lucky and find the right person with the right skills in the right geography, but it’s not realistic to scale up and retain a larger engineering organization that way. People need onboarding and training. Only the largest engineering organizations have the scale to make this kind of continuous investment.

Technical Review 98

Technical Review Trends Off-The-Shelf Software Review 98

Cloudera

MARCH 17, 2023

I love the enthusiasm surrounding ChatGPT and the eagerness to learn about modern data architectures such as data lakehouses, data meshes, and data fabrics. ChatGPT is trained on historical data and depending on how one phrases their question, it may offer inaccurate or misleading information.

ChatGPT 60

ChatGPT Education Data Comparison 60

Agile Engine

SEPTEMBER 29, 2023

Explore Data Studio projects and expertise in-depth Learn more Business challenge: addressing subscriber churn in the video streaming industry The client engaging our ML and data engineers is a premium streaming video on demand (SVOD) network top-listed by CNET in 2023.

Video 52

Video Machine Learning Artificial Inteligence Automotive 52

Cloudera

OCTOBER 4, 2023

On top of these core critical capabilities, we also need the following: Petabyte and larger scalability — particularly valuable in predictive analytics use cases where high granularity and deep histories are essential to training AI models to greater precision.

Analytics 83

Analytics Machine Learning Artificial Inteligence Telecommunications 83

O'Reilly Media - Data

JULY 18, 2018

My goal was to remind the data community about the many interesting opportunities and challenges in data itself. Because large deep learning architectures are quite data hungry, the importance of data has grown even more. Economic value of data.

Machine Learning 137

Machine Learning Artificial Inteligence Data Marketing 137

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. Model training.

Data Engineering 98

Data Engineering Engineering Data Machine Learning 98

O'Reilly Media - Ideas

FEBRUARY 2, 2020

First, the behavior of an AI application depends on a model , which is built from source code and training data. A model isn’t source code, and it isn’t data; it’s an artifact built from the two. You need a repository for models and for the training data. Second, the behavior of AI systems changes over time.

Meeting 72

Meeting Conference Training Testing 72

Apiumhub

JUNE 22, 2021

Data Innovation Summit topics. Same as last year, the event offers six workshops (crash-course) themes, each dedicated to a unique domain area: Data-driven Strategy, Analytics & Visualisation, Machine Learning, IoT Analytics & Data Management, Data Management and Data Engineering.

Innovation 84

Innovation Data Technical Review Artificial Inteligence 84

Capgemini

MARCH 16, 2023

These were trained on graph databases holding molecule properties, such as toxicity, binding energy, & antibiotic response. We then train them in important disciplines, such as manipulating and analyzing data, modeling, software engineering, and architecture. We hire staff with scientific academic backgrounds.

Pharmaceuticals 52

Pharmaceuticals Innovation Machine Learning Artificial Inteligence 52

O'Reilly Media - Data

APRIL 3, 2018

This year’s sessions on Data Engineering and Architecture showcases streaming and real-time applications, along with the data platforms used at several leading companies. In a vast majority of cases, machine learning applications require training data ( “labeled data is the new, new oil” ).

Machine Learning 155

Machine Learning Artificial Inteligence Company Case Study 155

CIO

MARCH 27, 2024

“Le azioni successive per il miglioramento della data quality possono essere sia di processo che applicative e includono la definizione di un modello organizzativo intorno alla data governance , assegnando ruoli e compiti chiari alle varie figure coinvolte (data scientist, data engineering, data owner, data steward, eccetera)”.

ChatGPT 130

ChatGPT Government Artificial Inteligence Business Intelligence 130

Cloudera

FEBRUARY 25, 2021

AMPs enable data scientists to go from an idea to a fully working ML use case in a fraction of the time, with an end-to-end framework for building, deploying, and monitoring business-ready ML applications instantly. . Train a convolutional neural network using only a few labeled data points. Analyzing News Headlines with SpaCy.

Machine Learning 81

Machine Learning Artificial Inteligence Telecommunications Enterprise 81

O'Reilly Media - Ideas

JULY 1, 2019

One area I’m particularly interested in is the application of AI and automation technologies in data science, data engineering, and software development. For a typical data scientist, data engineer, or developer, there is an explosion of tools and APIs they now need to work with and “master.”

Software Development 60

Software Development Artificial Inteligence Software Machine Learning 60

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

DECEMBER 21, 2020

Data Catalog profilers have been run on existing databases in the Data Lake. A Cloudera Data Warehouse virtual warehouse with Cloudera Data Visualisation enabled exists. A Cloudera Data Engineering service exists. The Data Scientist. Model training . The Data Engineer.

Data 97

Data Virtualization Banking Data Engineering 97

CTOvision

JANUARY 28, 2015

We''ve added new sessions and tracks to reflect challenges that have emerged in the data field— including security, ubiquitous computing, collaboration, reproducibility, new interfaces, emerging architecture, building data teams, machine data —and much more. Data scientists. Data engineers.

Big Data 109

Big Data Case Study Conference Study 109

O'Reilly Media - Ideas

DECEMBER 6, 2018

As I pointed out in previous posts, we learned many companies are still in the early stages of deploying machine learning: Companies cite “lack of data” and “lack of skilled people” as the main factors holding back adoption. In addition to data generation, another important aspect is data sharing. More help is on the way.

Technology 76

Technology Artificial Inteligence Machine Learning Hardware 76

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

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 Machine Learning Artificial Inteligence 325

Erik Bernhardsson

DECEMBER 15, 2020

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. It costs money and time to hire engineers and train them and getting things done. Supply-demand of software engineers.

Software Engineering 304

Software Engineering Engineering Tools Software 304

DataRobot

MARCH 10, 2022

With Snowflake’s newest feature release, Snowpark , developers can now quickly build and scale data-driven pipelines and applications in their programming language of choice, taking full advantage of Snowflake’s highly performant and scalable processing engine that accelerates the traditional data engineering and machine learning life cycles.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning IoT 52