CIO

AUGUST 7, 2023

And, in fact, McKinsey research argues the future could indeed be dazzling, with gen AI improving productivity in customer support by up to 40%, in software engineering by 20% to 30%, and in marketing by 10%. Shapers want to develop proprietary capabilities and have higher security or compliance needs.

Generative AI 208

Generative AI Off-The-Shelf Architecture Infrastructure 208

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. DevOps 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. DevOps engineer.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

CIO

FEBRUARY 13, 2023

CIOs anticipate an increased focus on cybersecurity (70%), data analysis (55%), data privacy (55%), AI/machine learning (55%), and customer experience (53%). Dental company SmileDirectClub has invested in an AI and machine learning team to help transform the business and the customer experience, says CIO Justin Skinner.

Budget 363

Budget Artificial Inteligence Technical Review VR 363

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 89

Data Data Engineering Machine Learning Artificial Inteligence 89

Altexsoft

FEBRUARY 11, 2023

The 11th annual survey of Chief Data Officers (CDOs) and Chief Data and Analytics Officers reveals 82 percent of organizations are planning to increase their investments in data modernization in 2023. What’s more, investing in data products, as well as in AI and machine learning was clearly indicated as a priority.

Data 87

Data Data Engineering Big Data Architecture 87

O'Reilly Media - Ideas

JULY 28, 2020

In this article, we turn our attention to the process itself: how do you bring a product to market? It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Nonetheless, building a superior feature pipeline or model architecture will always be worthwhile.

Marketing 145

Marketing Weak Development Team Metrics UI/UX 145

Cloudera

OCTOBER 4, 2023

We can get to faster root-cause analysis and become proactive instead of reactive to changes in markets, business operations, and customer behavior. And all of this should ideally be delivered in an easy to deploy and administer data platform available to work in any cloud.

Analytics 84

Analytics Machine Learning Artificial Inteligence Telecommunications 84

Cloudera

JANUARY 19, 2022

Our position as a Visionary in the Gartner Magic Quadrant for Cloud DBMS market speaks to our product excellence and market-leading-vision of a hybrid, multifunction integrated platform with built-in security and governance. . We were named a Visionary having a strong market understanding and a robust roadmap for the cloud DBMS market.

Report 87

Report Technical Advisors Cloud Analytics 87

Mobilunity

MAY 8, 2023

It is designed to store vast amounts of data from a variety of sources. Moreover an Enterprise Data Lake makes it accessible to data scientists, analysts, and other users across the enterprise. Ingestion zone is where data is collected from various sources and ingested into the data lake.

Engineering 52

Engineering Data Storage AWS 52

Mobilunity

MAY 3, 2024

When it comes to financial technology, data engineers are the most important architects. As fintech continues to change the way standard financial services are done, the data engineer’s job becomes more and more important in shaping the future of the industry.

Data Engineering 52

Data Engineering Fintech Engineering Data 52

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. Building an AI or machine learning model is not a one-time effort.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Capgemini

JANUARY 17, 2023

Facebook Twitter Linkedin As the year winds down, this is a good time to assess personal resolutions you have for the new year and, as a data leader, it’s also an opportunity to take a fresh look at your data and AI strategy. Here are four resolutions to make your data strategy pay off this year. Reassess your data architecture.

Strategy 52

Strategy Technical Review Data Artificial Inteligence 52

O'Reilly Media - Ideas

FEBRUARY 11, 2019

Highlights and use cases from companies that are building the technologies needed to sustain their use of analytics and machine learning. In a forthcoming survey, “Evolving Data Infrastructure,” we found strong interest in machine learning (ML) among respondents across geographic regions. Deep Learning.

Big Data 87

Big Data Technology Tools Cloud 87

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.

Data Engineering 98

Data Engineering Engineering Data Machine Learning 98

Mobilunity

DECEMBER 21, 2022

Data can enhance products and services. Data scientists can source essential insights from data that can be used to effectively enhance products and services to reach a bigger target market. Data creates better customer experiences. Build and Deploy Machine Learning Models. Agriculture.

Data 52

Data How To Machine Learning Artificial Inteligence 52

Cloudera

DECEMBER 21, 2020

Company data exists in the data lake. Data Catalog profilers have been run on existing databases in the Data Lake. A Cloudera Machine Learning Workspace exists . A Cloudera Data Warehouse virtual warehouse with Cloudera Data Visualisation enabled exists. The Data Scientist.

Data 97

Data Virtualization Banking Data Engineering 97

Existek

SEPTEMBER 28, 2023

AI-related skills are highly valued in the market and adopted in various industries. In this article, we’ve focused on the AI developer job and some efficient approaches to engage with the best specialists on the market. Developers often work with data acquisition, data cleaning, data transformation, and data augmentation.

Artificial Inteligence 52

Artificial Inteligence Development How To Artificial Intelligence 52

Apiumhub

APRIL 1, 2021

Learning data science through books will help you get a holistic view of Data Science as data science is not just about computing, it also includes mathematics, probability, statistics, programming, machine learning, and much more. Top Data science books you should definitely read. Berry, Gordon S.

Artificial Inteligence 52

Artificial Inteligence Data Handbook Machine Learning 52

Altexsoft

AUGUST 25, 2020

Prominent enterprises in numerous sectors including sales, marketing, research, and healthcare are actively collecting big data. 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.

Big Data 75

Big Data Data Engineering Engineering Data 75

Erik Bernhardsson

OCTOBER 27, 2015

I really think showcasing cool stuff on Github and helping out other projects is a great way to learn and also to demonstrate market validation of your code. If you want to understand the business and generate actionable insights, then in my experience you need pretty much no knowledge of statistics and machine learning.

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Erik Bernhardsson

OCTOBER 27, 2015

I really think showcasing cool stuff on Github and helping out other projects is a great way to learn and also to demonstrate market validation of your code. If you want to understand the business and generate actionable insights, then in my experience you need pretty much no knowledge of statistics and machine learning.

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Altexsoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

Mobilunity

DECEMBER 28, 2022

Machine Learning is a rapidly-growing field that is revolutionizing the way businesses work and collect data. The process of machine learning involves teaching computers to learn from data without being explicitly programmed. The Services That Machine Learning Engineers Can Offer.

Machine Learning 52

Machine Learning Artificial Inteligence Engineering How To 52

Altexsoft

APRIL 13, 2023

Supply chain control tower architecture: main components, integrations, and data sources As we mentioned, an SCCT is typically comprised of multiple components that handle various aspects of supply chain management. Let’s look closer at what’s there under the hood and list the main components, integrations, and data sources.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

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

APRIL 14, 2021

What is Cloudera Data Engineering (CDE) ? Cloudera Data Engineering is a serverless service for Cloudera Data Platform (CDP) that allows you to submit jobs to auto-scaling virtual clusters. Refer to the following cloudera blog to understand the full potential of Cloudera Data Engineering. .

Data Engineering 79

Data Engineering Engineering Data Serverless 79

CIO

NOVEMBER 29, 2022

A sea of complexity For years, data ecosystems have gotten more complex due to discrete (and not necessarily strategic) data-platform decisions aimed at addressing new projects, use cases, or initiatives. Layering technology on the overall data architecture introduces more complexity. Data and cloud strategy must align.

Organization 246

Organization Technical Review Data Artificial Inteligence 246

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. Register here to get yours.

Conference 96

Conference Artificial Inteligence UI/UX Machine Learning 96

Apiumhub

AUGUST 12, 2021

Gema Parreño Piqueras – Lead Data Science @Apiumhub Gema Parreno is currently a Lead Data Scientist at Apiumhub, passionate about machine learning and video games, with three years of experience at BBVA and later at Google in ML Prototype. Twitter: [link] Linkedin: [link]. Twitter: ??

Industry 59

Industry Technical Advisors CTO Coach Azure 59

Cloudera

DECEMBER 10, 2020

Why worry about costs with cloud-native data warehousing? Have you been burned by the unexpected costs of a cloud data warehouse? If so, you know about the failed economics of some cloud-native solutions on the market today. If not, before adopting a cloud data warehouse, consider the true costs of a cloud-native data warehouse.

Data 98

Data Technical Review Storage Systems Review 98

Altexsoft

JUNE 6, 2019

Forecasting demand with machine learning in Walmart. Systems that rely on machine learning are capable of analyzing a multitude of data points, finding subtle patterns (indicating changes in customer preferences, behavior, or satisfaction) which can be non-obvious for a human. data is analyzed. “We

Artificial Inteligence 89

Artificial Inteligence Artificial Intelligence Retail Innovation 89

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

Abhishek Tiwari

FEBRUARY 26, 2020

The evolution of your technology architecture should depend on the size, culture, and skill set of your engineering organization. There are no hard-and-fast rules to figure out interdependency between technology architecture and engineering organization but below is what I think can really work well for product startup.

Architecture 81

Architecture MVC Engineering Technology 81

O'Reilly Media - Ideas

FEBRUARY 18, 2020

This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. Software architecture, infrastructure, and operations are each changing rapidly. Trends in software architecture, infrastructure, and operations.

Technical Review 140

Technical Review Microservices Data Engineering Architecture 140

Cloudera

OCTOBER 19, 2023

While navigating so many simultaneous data-dependent transformations, they must balance the need to level up their data management practices—accelerating the rate at which they ingest, manage, prepare, and analyze data—with that of governing this data.

Data 73

Data Compliance Architecture Data Engineering 73

Altexsoft

JUNE 11, 2021

an also be described as a part of business process management (BPM) that applies data science (with its data mining and machine learning techniques) to dig into the records of the company’s software, get the understanding of its processes performance, and support optimization activities. Process mining ?an

Applications 69

Applications Weak Development Team Systems Review Software Review 69