CIO

JUNE 7, 2022

What is data analytics? Data analytics is a discipline focused on extracting insights from data. The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. What are the four types of data analytics?

Analytics 338

Analytics Data Analysis Business Analytics 338

CIO

APRIL 26, 2024

billion acquisition of data and analytics company Neustar in 2021, TransUnion has expanded into other services such as marketing, fraud detection and prevention, and robust analytical services. We’re modernizing existing products to get to this entire data analytics value chain.” But following its $3.1

Artificial Inteligence 286

Artificial Inteligence Generative AI Machine Learning Analytics 286

Dataiku

JANUARY 8, 2024

In the past few years, machine learning (ML) has gone from a discipline restricted to data scientists and engineers to the mainstream of business and analytics.

Machine Learning 81

Machine Learning Artificial Inteligence Analytics Engineering 81

TechCrunch

MAY 2, 2022

Nagaraj, a Harness investor, has long been close within Bansal’s orbit, previously serving as the VP of software engineering at AppDynamics for seven years. Businesses need machine learning here. billion) and Harness (which recently raised a $230 million Series D). To have zero trust you need API clarity. ”

Artificial Inteligence 234

Artificial Inteligence Machine Learning Technical Cofounder Cloud 234

CIO

AUGUST 25, 2023

Hot Melt Optimization employs a proprietary data collection method using proprietary sensors on the assembly line, which, when combined with Microsoft’s predictive analytics and Azure cloud for manufacturing, enables P&G to produce perfect diapers by reducing loss due to damage during the manufacturing process.

IoT 246

IoT Analytics Artificial Inteligence Software Review 246

CIO

OCTOBER 5, 2023

Foundry’s CIO Tech Priorities 2023 found that IT leaders are investing in technologies that provide greater efficiencies, better security, and improved end-user experience, with most actively researching or piloting projects around artificial intelligence (AI) and machine learning, data analytics, automation, and IT/OT intelligence.

Technical Review 317

Technical Review Engineering Technology Applications 317

CIO

AUGUST 4, 2023

As automation increases, organizations across every industry are looking for automation engineers to help facilitate, manage, and oversee enterprise automation. The automation engineer role Automation has been a cornerstone of the manufacturing industry for decades, but it’s relatively new to the business, healthcare, and finance industries.

Engineering 246

Engineering Artificial Inteligence Quality Assurance Hardware 246

TechCrunch

MAY 9, 2022

Pervasive BI remains elusive, but statistics on the category reveal that about a third of employees use BI tools for analytics to inform strategy. The big data and business analytics market could be worth $684 billion by 2030, according to Valuates Reports, if such outrageously high estimates are to be believed.

Analytics 215

Analytics Business Intelligence Software Review Business Analytics 215

Altexsoft

JUNE 29, 2021

In a world fueled by disruptive technologies, no wonder businesses heavily rely on machine learning. Google, in turn, uses the Google Neural Machine Translation (GNMT) system, powered by ML, reducing error rates by up to 60 percent. The role of a machine learning engineer in the data science team.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

CIO

JANUARY 19, 2024

Whether you’re looking to earn a certification from an accredited university, gain experience as a new grad, hone vendor-specific skills, or demonstrate your knowledge of data analytics, the following certifications (presented in alphabetical order) will work for you. Check out our list of top big data and data analytics certifications.)

Artificial Inteligence 317

Artificial Inteligence Data Machine Learning Azure 317

CIO

OCTOBER 13, 2023

In the next six to 12 months, some of the most popular anticipated uses for gen AI include content creation (42%), data analytics (53%), software development (41%), business insight (51%), internal customer support (45%), product development (40%), security (42%), and process automation (51%).

Generative AI 359

Generative AI Company Machine Learning Artificial Inteligence 359

CIO

SEPTEMBER 12, 2022

Data engine on wheels’. Today, NJ Transit is a “data engine on wheels,” says the CIDO. Fazal and his team have moved most of NJ Transit’s data to the cloud, evolving from simple reports to advanced analytics and AI/ML models that generate insights that transportation business analysts could only dream about in the past, he says. “We

Data Engineering 290

Data Engineering Engineering Data Transportation 290

Hacker Earth Developers Blog

AUGUST 2, 2022

Looking beyond the conventional HR practices and managing every part of the software engineer lifecycle is a key to increasing talent acquisition margin. In some cases, Data-driven recruiting and HR analytics use tangible company analysis and skills insights to solve recurring recruitment challenges and create high-quality talent pipelines.

Software Engineering 246

Software Engineering Artificial Inteligence Engineering Software 246

CIO

MARCH 31, 2023

As a chipmaker, AMD is a vital supplier for the public cloud’s compute engine, and among Ranjan’s key remits is to support the engineering of semiconductors that power the cloud. And for AMD’s most critical engineering applications, the answer remains its own data centers — not the cloud.

Engineering 289

Engineering Data Center AWS Cloud 289

Cloudera

OCTOBER 14, 2020

To maximize safety for all passengers and crew members, while also delivering profits, airlines have heavily invested in predictive analytics to gain insight on the most cost-effective way to maintain real-time engine performance. Fig 1: Turbofan jet engine. The Process. This is done at both sea level and all flight conditions.

Machine Learning 97

Machine Learning Artificial Inteligence Engineering Airlines 97

Perficient

FEBRUARY 27, 2023

Machine learning is now being used all around the world and its helping analytics team greatly in saving costs and improving business decisions. A Machine learning project starts with Raw data and Ends with a web application that can predict outcomes and generate insights from raw data.

Machine Learning 64

Machine Learning Artificial Inteligence Training Metrics 64

TechCrunch

NOVEMBER 4, 2021

Propelo (previously known as LevelOps ) wants to bring order to this chaos and aims to build an “AI-driven engineering excellence platform” that brings together a set of machine learning-powered analytics services and no-code robotic process automation (RPA) tools to help users turn these data points into something actionable.

Engineering 199

Engineering Artificial Inteligence DevOps Machine Learning 199

TechCrunch

DECEMBER 13, 2022

Dataiku — which sells tools to help customers build, test and deploy AI and analytics applications — has managed to avoid major layoffs, unlike competitors such as DataRobot. ” Dataiku, which launched in Paris in 2013, competes with a number of companies for dominance in the AI and big data analytics space.

Analytics 191

Analytics Big Data Machine Learning Artificial Inteligence 191

O'Reilly Media - Data

APRIL 3, 2018

The growing role of data and machine learning cuts across domains and industries. Companies continue to use data to improve decision-making (business intelligence and analytics) and for automation (machine learning and AI). Data Science and Machine Learning sessions will cover tools, techniques, and case studies.

Machine Learning 155

Machine Learning Artificial Inteligence Company Case Study 155

Cloudera

AUGUST 31, 2018

We learned a lot about data center automation based on real-time application and diagnostic feedback using applied machine learning. Witnessing these challenges, we focused on solving them through machine learning applied to workload and cluster optimization.

Machine Learning 66

Machine Learning Artificial Inteligence Analytics Engineering Culture 66

Cloudera

APRIL 9, 2021

And this blog will focus on Predictive Analytics. Specifically, we’ll focus on training Machine Learning (ML) models to forecast ECC part production demand across all of its factories. Data Enrichment – data engineering. Predictive Analytics – AI & machine learning. Here are the key stages: .

Machine Learning 98

Machine Learning Artificial Inteligence Data Data Engineering 98

CIO

APRIL 12, 2023

After walking his executive team through the data hops, flows, integrations, and processing across different ingestion software, databases, and analytical platforms, they were shocked by the complexity of their current data architecture and technology stack. Sound familiar?) It isn’t easy. A unified data ecosystem enables this in real time.

Artificial Inteligence 363

Artificial Inteligence Artificial Intelligence Machine Learning Agile 363

OTS Solutions

JULY 18, 2023

To meet this demand, enterprises have turned to DevOps and digital engineering practices to streamline their software development and delivery processes. What are DevOps and Digital Engineering? Why are DevOps and Digital Engineering Important? Why are DevOps and Digital Engineering Important?

DevOps 130

DevOps Engineering Artificial Inteligence Software Review 130

TechCrunch

JULY 20, 2022

Contentsquare remains focused on its original bread and butter, which is to say web and app analytics. Contentsquare also provides an API that customers can use to integrate the platform with web apps and other systems, like personalization engines. billion valuation for its code analytics suite for digital customer experiences.

Analytics 235

Analytics Artificial Inteligence Technical Review Nonprofit 235

Altexsoft

JULY 23, 2020

When speaking of machine learning, we typically discuss data preparation or model building. The fusion of terms “machine learning” and “operations”, MLOps is a set of methods to automate the lifecycle of machine learning algorithms in production — from initial model training to deployment to retraining against new data.

Artificial Inteligence 145

Artificial Inteligence Machine Learning DevOps Tools 145

CIO

OCTOBER 20, 2023

I recently spoke with Michael Cullum, Bud’s vice president of engineering and data, who shared valuable lessons on extracting valuable insights from financial data and delivering them effectively to clients. Cultivating a culture where every team member actively uses data and analytics tools ( Looker is a great example) is essential.

Google Cloud 328

Google Cloud Artificial Inteligence Development Team Review Banking 328

Openxcell

MARCH 30, 2023

From human genome mapping to Big Data Analytics, Artificial Intelligence (AI),Machine Learning, Blockchain, Mobile digital Platforms (Digital Streets, towns and villages),Social Networks and Business, Virtual reality and so much more. What is Machine Learning? Machine Learning delivers on this need.

Artificial Inteligence 98

Artificial Inteligence Machine Learning IoT Internet 98

CIO

JULY 28, 2022

We try to be data-driven in our decisions so we have a great need for analytics skill sets. … That is backed up by a 2021 survey by industry analysts at Forrester, which showed that, of 2,329 data and analytics decision-makers worldwide, 55% want to hire data scientists. We have a very focused approach around building that pipeline.”.

Data 359

Data Machine Learning Artificial Inteligence Fractional CTO 359

Confluent

FEBRUARY 6, 2019

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. Impedance mismatch between data scientists, data engineers and production engineers.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

OTS Solutions

JULY 18, 2023

To meet this demand, enterprises have turned to DevOps and digital engineering practices to streamline their software development and delivery processes. What are DevOps and Digital Engineering? Why are DevOps and Digital Engineering Important? Why are DevOps and Digital Engineering Important?

DevOps 130

DevOps Engineering Artificial Inteligence Software Review 130

Harvard Business Review

APRIL 16, 2024

Having a crisp mental model around a problem, being able to break it down into steps that are tractable, perfect first-principle thinking, sometimes being prepared (and able to) debate a stubborn AI — these are the skills that will make a great engineer in the future, and likely the same consideration applies to many job categories.

Study 140

Study Engineering Development Machine Learning 140

Altexsoft

MAY 12, 2022

Today, we have AI and machine learning to extract insights, inaudible to human beings, from speech, voices, snoring, music, industrial and traffic noise, and other types of acoustic signals. For instance, Nuance Gatekeeper biometric engine verifies employees and customers by their voices in the banking sector. Music recognition.

Machine Learning 122

Machine Learning Artificial Inteligence Analysis Energy 122

Erik Bernhardsson

AUGUST 4, 2016

I joined Spotify in 2008 to focus on machine learning and music recommendations. So instead, I switched gears and ran the “Analytics team” for 2 years. In the majority of all products, machine learning will not be a key differentiator in the first five years. Most machine learning is sprinkles on the top.

Machine Learning 124

Machine Learning Artificial Inteligence Sustainability System 124

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. However, at the same time, SAP was working on a new feature for the SAP Analytics Cloud: Just Ask, which applies gen AI to search-driven analytics.

Artificial Inteligence 347

Artificial Inteligence B2C Machine Learning Artificial Intelligence 347

TechCrunch

JUNE 17, 2021

Without people, you don’t have a product,” says Joseph Ifiegbu, who is Snap’s former head of human resources technology and also previous lead of WeWork’s People Analytics team. Ifiegbu joined WeWork’s People Analytics team in 2017, when the company had a total of about 2,000 employees. This prompted them to start working on eqtble. “It

Analytics 237

Analytics Data Resources Recruiting 237

Dzone - DevOps

NOVEMBER 7, 2023

Databricks is a cloud-based platform designed to simplify the process of building data engineering pipelines and developing machine learning models.

Data Engineering 76

Data Engineering Engineering Machine Learning Artificial Inteligence 76

TechCrunch

JUNE 8, 2022

“To better support advanced users, we’re adding support for machine learning engineers to extend Continual’s automated machine learning engine with custom models and then expose these new capabilities to all users in their organization,” the company’s CEO and co-founder Tristan Zajonc explained.

Artificial Inteligence 216

Artificial Inteligence Machine Learning AWS Engineering 216