TechCrunch

APRIL 12, 2022

While companies find AI’s predictive power alluring, particularly on the data analytics side of the organization, achieving meaningful results with AI often proves to be a challenge. That’s where Flyte comes in — a platform for programming and processing concurrent AI and data analytics workflows.

Artificial Inteligence 202

Artificial Inteligence Machine Learning Open Source Biotech 202

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

Cloudera

DECEMBER 20, 2022

In this respect, several studies project that a proper use of advanced analytics implies savings of between 5% and 7.5%. 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 81

Energy Analytics Data Machine Learning 81

Altexsoft

DECEMBER 9, 2020

In the era of global digital transformation , the role of data analysis in decision-making increases greatly. Still, today, according to Deloitte research, insight-driven companies are fewer than those not using an analytical approach to decision-making, even though the majority agrees on its importance. Stages of analytics maturity.

Analytics 102

Analytics Technical Review Technology Applications 102

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 174

Sport Artificial Inteligence Coaching Games 174

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. But there is more room to go.

Analytics 305

Analytics KPI IoT Azure 305

CIO

DECEMBER 16, 2022

The top-earning skills were big data analytics and Ethereum, with a pay premium of 20% of base salary, both up 5.3% Other non-certified skills attracting a pay premium of 19% included data engineering , the Zachman Framework , Azure Key Vault and site reliability engineering (SRE). in the previous six months.

Technical Review 208

Technical Review Analytics AWS SCRUM 208

Agile Engine

DECEMBER 27, 2023

From emerging trends to hiring a data consultancy, this article has everything you need to navigate the data analytics landscape in 2024. What is a data analytics consultancy? Big data consulting services 5. 4 types of data analysis 6. Data analytics use cases by industry 7.

Big Data 52

Big Data Analytics Data Analysis 52

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

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 205

Technical Review Analytics Innovation Artificial Intelligence 205

Altexsoft

FEBRUARY 10, 2021

Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. DataOps is a relatively new methodology that knits together data engineering, data analytics, and DevOps to deliver high-quality data products as fast as possible.

Analytics 75

Analytics DevOps Development Software Review 75

Cloudera

OCTOBER 29, 2020

From our release of advanced production machine learning features in Cloudera Machine Learning, to releasing CDP Data Engineering for accelerating data pipeline curation and automation; our mission has been to constantly innovate at the leading edge of enterprise data and analytics.

Data 111

Data Machine Learning Artificial Inteligence Analytics 111

CIO

JUNE 3, 2024

Data engineering, prompt engineering, and coding will be the IT skills most in demand, but critical thinking, creativity, flexibility, and the ability to work in teams will also be highly valued, according to the survey. Agility is very important, because this is so new, and technological advances are going to come fast.”

Generative AI 297

Generative AI Technical Review Technical Advisors Software Review 297

Apiumhub

SEPTEMBER 20, 2023

From software architecture to artificial intelligence and machine learning, ​​these conferences offer unparalleled insights, networking opportunities, and a glimpse into the future of technology. Learn more about the speakers and check out their schedule by visiting their site here. Interested in attending?

Conference 96

Conference Artificial Inteligence UI/UX Machine Learning 96

Cloudera

NOVEMBER 28, 2023

With its rise in popularity generative AI has emerged as a top CEO priority, and the importance of performant, seamless, and secure data management and analytics solutions to power those AI applications is essential. This means you can expect simpler data management and drastically improved productivity for your business users.

Data 84

Data Scalability Analytics Quality Assurance 84

Apiumhub

JUNE 22, 2021

We are super excited to participate in the biggest and the most influential Data, AI and Advanced Analytics event in the Nordics! Data Innovation Summit ! There our Gema Parreño – Data Science expert at Apiumhub gives a talk about Alignment of Language Agents for serious video games.

Innovation 83

Innovation Data Technical Review Artificial Inteligence 83

Altexsoft

FEBRUARY 8, 2021

These challenges can be addressed by intelligent management supported by data analytics and business intelligence (BI) that allow for getting insights from available data and making data-informed decisions to support company development. Optimization opportunities offered by analytics.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

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 133

Agile Innovation Culture Business Intelligence 133

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. But that turns IT and analytics teams into the bottleneck.

Agile 52

Agile Technical Review Systems Review Artificial Intelligence 52

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 330

Artificial Inteligence Analytics Artificial Intelligence Machine Learning 330

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

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

Cloudera

OCTOBER 1, 2022

These companies face a unique set of data governance challenges regarding infrastructure and compliance on local, national, and international levels. Some organizations are choosing to confront these challenges with the help of tools like machine learning (ML) and artificial intelligence (AI) to automate, streamline, and scale compliance. .

Government 75

Government Artificial Inteligence Enterprise Strategy 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 314

Analytics Data Engineering Machine Learning Artificial Inteligence 314

CIO

AUGUST 2, 2023

A data and analytics capability cannot emerge from an IT or business strategy alone. With both technology and business organization deeply involved in the what, why, and how of data, companies need to create cross-functional data teams to get the most out of it. It’s given us agility.

Data 201

Data Architecture Government Strategy 201

Cloudera

OCTOBER 13, 2021

These companies have instead opted to leverage their existing data centre investment. Turning the data center into a private cloud would bring all the agility and flexibility of public cloud to the control of an on-premises infrastructure. Next stop: hybrid data cloud. Breaking down the on-prem monolith.

Data Center 98

Data Center Cloud Data How To 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

Apiumhub

APRIL 5, 2022

Apiumhub has become a Media partner of the Data Innovation Summit – the most influential data, AI and advanced analytics event in the Nordics and beyond. . Data Innovation Summit 2022 edition at glance. Save the dates: 5th & 6th May, 2022. .

Innovation 52

Innovation Data Artificial Inteligence Case Study 52

Xebia

MARCH 10, 2021

Therefore these organisations introduce a new capability: Data & Analytics. This blog elaborates on how adopting DevOps principles can enhance business value creation for the world of Data & Analytics. Data & Analytics as a separate business domain. a data & analytics platform).

DevOps 130

DevOps Data Analytics Policies 130

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

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

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

SEPTEMBER 10, 2018

Your raw material is data instead of wood, and you use multidisciplinary analytics rather than woodworking tools like a hammer, saw, and sander. Just like the tools, your analytic functions need to work in concert although the results are insights rather than sanded rough cuts left by the saw.

Analytics 40

Analytics Machine Learning Artificial Inteligence Data Engineering 40

Cloudera

MAY 17, 2021

Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform. When you migrate to the cloud, you want to gain agility through real measurable improvements in your analytics development projects .

Cloud 90

Cloud Data Agile Analytics 90

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Introduction. CRM platforms).

Scalability 94

Scalability Technical Review Data Analytics 94

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

BPM

JANUARY 18, 2019

The current Artificial Intelligence (AI) fascination is unfortunately completely biased on Deep Neural Networks (DNN) and Machine Learning (ML) for everything. Continuing the journey toward true business agility initiated in the software realm. Denis Gagne Trisotech [link]. Max Pucher Isis Papyrus [link].

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111