CIO

OCTOBER 1, 2022

We do that by leveraging data, AI, and automation with agility and scale across all dimensions of our business, accelerating innovation and increasing productivity in everything we do.”. It also involves large amounts of data and near real-time processing. The power of people.

Artificial Inteligence 363

Artificial Inteligence Azure IoT Analytics 363

d2iq

FEBRUARY 19, 2021

Going from a prototype to production is perilous when it comes to machine learning: most initiatives fail , and for the few models that are ever deployed, it takes many months to do so. As little as 5% of the code of production machine learning systems is the model itself. Adapted from Sculley et al.

Artificial Inteligence 103

Artificial Inteligence Machine Learning Technical Review Software Review 103

TechCrunch

APRIL 12, 2022

“Searching for the right solution led the team deep into machine learning techniques, which came with requirements to use large amounts of data and deliver robust models to production consistently … The techniques used were platformized, and the solution was used widely at Lyft.” ” Taking Flyte.

Artificial Inteligence 202

Artificial Inteligence Machine Learning Open Source Biotech 202

InfoQ Culture Methods

FEBRUARY 16, 2023

Have you ever wondered about systems based on machine learning? In those cases, testing takes a backseat. And even if testing is done, it’s done mostly by developers itself. A tester’s role is not clearly portrayed. Testers usually struggle to understand ML-based systems and explore what contributions they can make.

Artificial Inteligence 100

Artificial Inteligence Machine Learning System Testing 100

CIO

APRIL 3, 2023

Digital solutions and data analytics are changing the world of sports entertainment at a rapid clip. From how players train, to how teams make strategic decisions during games, to how venues operate and fans engage, sports organizations are turning to software engineers and data scientists to help transform the sport experience.

Sport 241

Sport Artificial Inteligence Coaching Games 241

CIO

DECEMBER 16, 2022

An average premium of 12% was on offer for PMI Program Management Professional (PgMP), up 20%, and for GIAC Certified Forensics Analyst (GCFA), InfoSys Security Engineering Professional (ISSEP/CISSP), and Okta Certified Developer, all up 9.1% since March.

Technical Review 246

Technical Review Analytics AWS SCRUM 246

OpenCredo

JULY 31, 2018

Machine Learning, alongside a mature Data Science, will help to bring IT and business closer together. By leveraging data for actionable insights, IT will increasingly drive business value. As an IT engineer the value of IT is self-evident, surely? The Role of Data. Machine learning produces predictions.

Artificial Inteligence 40

Artificial Inteligence Machine Learning Data Artificial Intelligence 40

CIO

JUNE 28, 2023

“These circumstances have induced uncertainty across our entire business value chain,” says Venkat Gopalan, chief digital, data and technology officer, Belcorp. “As Belcorp operates under a direct sales model in 14 countries. The team leaned on data scientists and bio scientists for expert support.

Technical Review 262

Technical Review Analytics Innovation Artificial Intelligence 262

CIO

DECEMBER 1, 2022

Tapped to guide the company’s digital journey, as she had for firms such as P&G and Adidas, Kanioura has roughly 1,000 data engineers, software engineers, and data scientists working on a “human-centered model” to transform PepsiCo into a next-generation company.

Analytics 362

Analytics KPI IoT Azure 362

CIO

AUGUST 2, 2023

At the business concept layer, finance leadership engages in a cadence of discussions with IT and data engineering leadership to discuss the process change necessary to create enterprise self-service revenue reporting. At the consumable layer, we decide how people will consume the revenue data. Who has access to the data?

Data 246

Data Architecture Government Strategy 246

InfoQ Culture Methods

JULY 17, 2020

To mix the power of the data and the importance of people to offer business intelligence is a key point nowadays. To be agile is to adapt to today's market. The result is not only the most imporant thing, the way you do it more important. By Alejandro Ruiz.

Agile 141

Agile Innovation Culture Business Intelligence 141

Cloudera

JUNE 2, 2021

As critical elements in supplying trusted, curated, and usable data for end-to-end analytic and machine learning workflows, the role of data pipelines is becoming indispensable. To keep up, data pipelines are being vigorously reshaped with modern tools and techniques.

Data 92

Data Data Engineering Machine Learning Artificial Inteligence 92

Kentik

APRIL 12, 2023

At the heart of DataOps is the agile development methodology, which emphasizes collaboration, iteration, and continuous delivery. Data scientists play a critical role in the DataOps ecosystem, leveraging advanced analytics and machine learning techniques to gain insights from large and complex data sets.

Network 52

Network Data Engineering Machine Learning Artificial Inteligence 52

Capgemini

NOVEMBER 14, 2022

The role of self-service BI for business agility Myles Suer 9 Nov 2022. Facebook Twitter Linkedin The move to self-service BI is driven by an organization’s need for agility in support of a hybrid workforce. But this requires data accessibility for every worker. The data catalog is foundational. Everything moves faster.

Agile 52

Agile Technical Review Systems Review Artificial Intelligence 52

Trigent

AUGUST 26, 2022

Expert assistance and agile technology solutions make your work easier. Trigent Software is one of those fantastic IT service providers that enable organizations to adopt customer engagement models and advanced digital processes to achieve outstanding end-user experience and results.

Software Review 52

Software Review Software Technical Review Artificial Intelligence 52

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

Mentormate

OCTOBER 31, 2023

The allure of the latest machine-learning techniques is undeniable, but without a well-structured approach, you risk getting lost in the technological maze. Transfer learning is both a time-saver and a resource optimizer, allowing you to leverage pre-existing solutions for your business case.

Artificial Inteligence 98

Artificial Inteligence Healthcare Budget Training 98

Hu's Place - HitachiVantara

JANUARY 3, 2019

Public cloud, agile methodologies and devops, RESTful APIs, containers, analytics and machine learning are being adopted. ” Deployments of large data hubs have only resulted in more data silos that are not easily understood, related, or shared.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Agile Engine

SEPTEMBER 29, 2023

Few people know this, but enterprises often employ a machine learning technique that’s instrumental in particle physics experiments at the Large Hadron Collider. One such challenge is subscriber churn prediction, a critical aspect of a recent project at AgileEngine Data Studio.

Video 52

Video Machine Learning Artificial Inteligence Automotive 52

O'Reilly Media - Ideas

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). AI products are automated systems that collect and learn from data to make user-facing decisions. Machine learning adds uncertainty.

Product Management 139

Product Management Artificial Inteligence Machine Learning Software Review 139

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

Dataiku

MAY 20, 2020

Collaboration across teams : Data projects are not only about data, but also require strong involvement from business teams to build experience, generate buy-in, and validate relevance. They also require data engineering and other teams to help with the operationalization steps.

Data 105

Data How To Machine Learning Artificial Inteligence 105

Cloudera

DECEMBER 20, 2022

McKinsey estimates that the use of data-driven technologies can drive operating and maintenance cost savings of more than 12%. For example, predictive maintenance, based on machine learning, will enable utility companies to take preventative action that avoids large-scale power outages and costs.

Energy 83

Energy Analytics Data Machine Learning 83

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. AI and machine learning.

Course 46

Course Training Artificial Inteligence Machine Learning 46

CIO

OCTOBER 18, 2023

“IDH holds a potentially severe immediate risk for patients during dialysis and therefore requires immediate attention from staff,” says Hanjie Zhang, director of computational statistics and artificial intelligence at the Renal Research Institute, a joint venture of Fresenius North America and Beth Israel Medical Center. “As

Artificial Inteligence 334

Artificial Inteligence Analytics Artificial Intelligence Machine Learning 334

O'Reilly Media - Ideas

APRIL 9, 2019

Or, why science and engineering are still different disciplines. "A He would have to ask an engineer to do it for him.". A few months ago, I wrote about the differences between data engineers and data scientists. That was interesting because the data engineers didn’t push back saying they’re data scientists.

Data Engineering 111

Data Engineering Engineering Data Technical Review 111

Xebia

MARCH 10, 2021

One example to illustrate what often happens in practice: a data scientist from a business team creates an analytical model on their own laptop and everything works. Next, the data scientist asks an engineer in the Data & Analytics domain to ‘productionize’ the analytical model. What is DevOps?

DevOps 130

DevOps Data Analytics Policies 130

InfoQ Culture Methods

FEBRUARY 24, 2023

In this article, Tariq King describes the metaverse concept, discusses its key engineering challenges and quality concerns, and then walks through recent technological advances in AI and software testing that are helping to mitigate these challenges.

Testing 127

Testing Engineering Software Artificial Inteligence 127

CTOvision

JUNE 15, 2015

They also launched a plan to train over a million data scientists and data engineers on Spark. As data and analytics are embedded into the fabric of business and society –from popular apps to the Internet of Things (IoT) –Spark brings essential advances to large-scale data processing.

Open Source 117

Open Source Big Data Machine Learning Artificial Inteligence 117

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

Altexsoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

Architecture 52

Architecture Data Storage Machine Learning 52

Altexsoft

AUGUST 25, 2020

Big data can be quite a confusing concept to grasp. What to consider big data and what is not so big data? Big data is still data, of course. But it requires a different engineering approach and not just because of its amount. Data engineering vs big data engineering.

Big Data 75

Big Data Data Engineering Engineering Data 75

Cloudera

JANUARY 15, 2021

Cloud data warehouses allow users to run analytic workloads with greater agility, better isolation and scale, and lower administrative overhead than ever before. CDW is one of several managed services that comprise the broader Cloudera Data Platform (CDP). The benchmark run by McKnight Consulting Group used the Impala engine.

Performance 96

Performance Cloud Data Storage 96

The Accidental Successful CIO

MAY 12, 2021

If you steer your business users into becoming ad hoc data engineers, you can end up with a chaotic mix of metrics that vary across departments, run into data security problems, and even run up big licensing if there’s no centralized control over tool rollout. What All Of This Means For You.

Business Intelligence 90

Business Intelligence Business Analytics Analytics Off-The-Shelf 90

Altexsoft

JUNE 25, 2019

Being at the top of data science capabilities, machine learning and artificial intelligence are buzzing technologies many organizations are eager to adopt. 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.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Coforge

AUGUST 31, 2020

The drastic shift from traditional and orthodox system frameworks and operations can be unarguably attributed to the influx of intelligent technologies such as Artificial Intelligence, Machine Learning, Big Data, Blockchain/DLT led smart contracts, and widespread usage of cloud systems. .

Insurance 40

Insurance Technology Artificial Inteligence Policies 40

Cloudera

AUGUST 24, 2022

Cloudera Machine Learning (CML) is a cloud-native and hybrid-friendly machine learning platform. It unifies self-service data science and data engineering in a single, portable service as part of an enterprise data cloud for multi-function analytics on data anywhere. Click +Add Runtime.

Machine Learning 83

Machine Learning Artificial Inteligence Open Source Windows 83