CIO

APRIL 23, 2025

Modern AI models, particularly large language models, frequently require real-time data processing capabilities. The machine learning models would target and solve for one use case, but Gen AI has the capability to learn and address multiple use cases at scale.

Insurance 164

Insurance Artificial Inteligence Data Architecture 164

CIO

APRIL 1, 2025

Job titles like data engineer, machine learning engineer, and AI product manager have supplanted traditional software developers near the top of the heap as companies rush to adopt AI and cybersecurity professionals remain in high demand.

Marketing 152

Marketing Software Development Software Development 152

CIO

SEPTEMBER 12, 2022

Data engine on wheels’. To mine more data out of a dated infrastructure, Fazal first had to modernize NJ Transit’s stack from the ground up to be geared for business benefit. Today, NJ Transit is a “data engine on wheels,” says the CIDO. We have shown out value,” Fazal says of the transformation. “We

Data Engineering 174

Data Engineering Engineering Data Transportation 174

TechCrunch

JULY 12, 2022

Machine learning can provide companies with a competitive advantage by using the data they’re collecting — for example, purchasing patterns — to generate predictions that power revenue-generating products (e.g. At a high level, Tecton automates the process of building features using real-time data sources.

Artificial Inteligence 249

Artificial Inteligence Machine Learning Marketing Data Engineering 249

Altexsoft

JULY 23, 2020

When speaking of machine learning, we typically discuss data preparation or model building. Living in the shadow, this stage, according to the recent study , eats up 25 percent of data scientists time. MLOps lies at the confluence of ML, data engineering, and DevOps. More time for development of new models.

Artificial Inteligence 145

Artificial Inteligence Machine Learning DevOps Tools 145

CIO

MARCH 13, 2025

Gen AI-related job listings were particularly common in roles such as data scientists and data engineers, and in software development. Were building a department of AI engineering, mostly by bringing in people from data engineering and training them to work with gen AI and AI in general, says Daniel Avancini, Indiciums CDO.

Part-Time VPE 205

Part-Time VPE Weak Development Team Fractional VPE Fractional CTO 205

The Crazy Programmer

NOVEMBER 6, 2021

Currently, the demand for data scientists has increased 344% compared to 2013. hence, if you want to interpret and analyze big data using a fundamental understanding of machine learning and data structure. Because the salary for a data scientist can be over Rs5,50,000 to Rs17,50,000 per annum.

Artificial Inteligence 290

Artificial Inteligence Blockchain Software Review Artificial Intelligence 290

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.

Artificial Inteligence 107

Artificial Inteligence Machine Learning Scalability Data Engineering 107

TechCrunch

OCTOBER 19, 2021

While collaborating with product developers, Dang and Wang saw that while product developers wanted to use AI, they didn’t have the right tools in which to do it without relying on data scientists. “We They didn’t work with machine learning extensively, so we decided to build tools for technical non-experts.

Artificial Inteligence 248

Artificial Inteligence Machine Learning Tools Technical Review 248

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

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 Cloud 202

CIO

DECEMBER 10, 2024

Choreographing data, AI, and enterprise workflows While vertical AI solves for the accuracy, speed, and cost-related challenges associated with large-scale GenAI implementation, it still does not solve for building an end-to-end workflow on its own.

Artificial Inteligence 174

Artificial Inteligence Off-The-Shelf Insurance Analytics 174

CIO

JUNE 11, 2024

The company is offering eight free courses , leading up to this certification, including Fundamentals of Machine Learning and Artificial Intelligence, Exploring Artificial Intelligence Use Cases and Application, and Essentials of Prompt Engineering. AWS has been adding new certifications to its offering.

Artificial Inteligence 173

Artificial Inteligence AWS Artificial Intelligence Machine Learning 173

TechCrunch

JUNE 2, 2021

The core idea behind Iterative is to provide data scientists and data engineers with a platform that closely resembles a modern GitOps-driven development stack. After spending time in academia, Iterative co-founder and CEO Dmitry Petrov joined Microsoft as a data scientist on the Bing team in 2013.

Artificial Inteligence 249

Artificial Inteligence Machine Learning Open Source Data Engineering 249

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

TechCrunch

MAY 10, 2022

“The major challenges we see today in the industry are that machine learning projects tend to have elongated time-to-value and very low access across an organization. “Given these challenges, organizations today need to choose between two flawed approaches when it comes to developing machine learning. .

Artificial Inteligence 235

Artificial Inteligence Machine Learning Off-The-Shelf Training 235

CIO

DECEMBER 4, 2024

We’ve had folks working with machine learning and AI algorithms for decades,” says Sam Gobrail, the company’s senior director for product and technology. But for practical learning of the same technologies, we rely on the internal learning academy we’ve established.”

Recruiting 202

Recruiting Artificial Inteligence Programming Technology 202

TechCrunch

MAY 3, 2022

“There were no purpose-built machine learning data tools in the market, so [we] started Galileo to build the machine learning data tooling stack, beginning with a [specialization in] unstructured data,” Chatterji told TechCrunch via email.

Artificial Inteligence 223

Artificial Inteligence Machine Learning Development Software Review 223

Cloudera

FEBRUARY 14, 2022

When we introduced Cloudera Data Engineering (CDE) in the Public Cloud in 2020 it was a culmination of many years of working alongside companies as they deployed Apache Spark based ETL workloads at scale. The same key tenants powering DE in the public clouds are now available in the data center.

Data Engineering 113

Data Engineering Engineering Data Storage 113

Cloudera

OCTOBER 11, 2021

Modak, a leading provider of modern data engineering solutions, is now a certified solution partner with Cloudera. Customers can now seamlessly automate migration to Cloudera’s Hybrid Data Platform — Cloudera Data Platform (CDP) to dynamically auto-scale cloud services with Cloudera Data Engineering (CDE) integration with Modak Nabu.

Data Engineering 95

Data Engineering Engineering Data Cloud 95

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. We will learn what it is, why it is important and how Cloudera Machine Learning (CML) is helping organisations tackle this challenge as part of the broader objective of achieving Ethical AI.

Artificial Inteligence 85

Artificial Inteligence Machine Learning Weak Development Team Construction 85

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

Xebia

MARCH 13, 2025

This becomes more important when a company scales and runs more machine learning models in production. This is a common issue, especially when working in cloud environments. Features are computed in a feature engineering pipeline that writes features to the data store. This drives computation costs.

Training 130

Training Artificial Inteligence Machine Learning Data 130

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 Artificial Inteligence 98

CIO

AUGUST 3, 2022

The target architecture of the data economy is platform-based , cloud-enabled, uses APIs to connect to an external ecosystem, and breaks down monolithic applications into microservices. The cloud. The cloud is about more than managing costs. The cloud is an enabler for all that will come.

Leadership 218

Leadership Artificial Inteligence Machine Learning IoT 218

CIO

APRIL 12, 2023

Real-time AI involves processing data for making decisions within a given time frame. Real-time AI brings together streaming data and machine learning algorithms to make fast and automated decisions; examples include recommendations, fraud detection, security monitoring, and chatbots. It isn’t easy.

Artificial Inteligence 218

Artificial Inteligence Artificial Intelligence Machine Learning Agile 218

AWS Machine Learning - AI

APRIL 23, 2025

Serverless on AWS AWS GovCloud (US) Generative AI on AWS About the Authors Nick Biso is a Machine Learning Engineer at AWS Professional Services. He solves complex organizational and technical challenges using data science and engineering. In addition, he builds and deploys AI/ML models on the AWS Cloud.

Artificial Inteligence 65

Artificial Inteligence Open Source AWS Serverless 65

AWS Machine Learning - AI

NOVEMBER 15, 2024

The flexible, scalable nature of AWS services makes it straightforward to continually refine the platform through improvements to the machine learning models and addition of new features. Dr. Nicki Susman is a Senior Machine Learning Engineer and the Technical Lead of the Principal AI Enablement team.

Generative AI 113

Generative AI AWS Groups Artificial Inteligence 113

Apiumhub

DECEMBER 9, 2024

Azure Key Vault is a cloud service that provides secure storage and access to confidential information such as passwords, API keys, and connection strings. This is a single, integrated location that allows for a data warehouse, and large data processing. Also combines data integration with machine learning.

Azure 91

Azure Analytics Storage Artificial Inteligence 91

TechCrunch

APRIL 25, 2022

“Feature stores sit at the intersection of data and machine learning,” Michael Del Balso, the CEO of Tecton.ai , a startup developing feature store software for businesses, told TechCrunch in an email. They serve as the interface between data and [AI] models.”

Artificial Inteligence 225

Artificial Inteligence Machine Learning Data Engineering Enterprise 225

Cloudera

SEPTEMBER 17, 2020

With growing disparate data across everything from edge devices to individual lines of business needing to be consolidated, curated, and delivered for downstream consumption, it’s no wonder that data engineering has become the most in-demand role across businesses — growing at an estimated rate of 50% year over year.

Data Engineering 104

Data Engineering Engineering Data Tools 104

CIO

JUNE 7, 2022

Data scientists are the core of any AI team. They process and analyze data, build machine learning (ML) models, and draw conclusions to improve ML models already in production. Data engineer. Data engineers build and maintain the systems that make up an organization’s data infrastructure.

Artificial Inteligence 218

Artificial Inteligence Technical Review Fractional CTO Data Engineering 218

CIO

OCTOBER 13, 2023

Analytics/data science architect: These data architects design and implement data architecture supporting advanced analytics and data science applications, including machine learning and artificial intelligence. Data architect vs. data engineer The data architect and data engineer roles are closely related.

Data 199

Data Data Engineering Database Administration Artificial Inteligence 199

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.

Artificial Inteligence 83

Artificial Inteligence Machine Learning Open Source Windows 83

Cloudera

OCTOBER 13, 2020

On September 24, 2019, Cloudera launched CDP Public Cloud (CDP-PC) as the first step in delivering the industry’s first Enterprise Data Cloud. CDP Machine Learning: a kubernetes-based service that allows data scientists to deploy collaborative workspaces with secure, self-service access to enterprise data.

Cloud 97

Cloud Artificial Inteligence Machine Learning Data Engineering 97

CIO

JUNE 10, 2024

Moreover, many need deeper AI-related skills, too, such as for building machine learning models to serve niche business requirements. He wants data scientists who can build, train, and validate models for use cases, and who can perform exploratory analysis and hypothesis testing. Here’s how IT leaders are coping.

Artificial Inteligence 204

Artificial Inteligence Strategy Machine Learning Training 204

O'Reilly Media - Ideas

AUGUST 18, 2020

That is, products that are laser-focused on one aspect of the data science and machine learning workflows, in contrast to all-in-one platforms that attempt to solve the entire space of data workflows. Lessons Learned from Data Warehouse and Data Engineering Platforms. A little of both?

Artificial Inteligence 145

Artificial Inteligence Machine Learning Data Data Engineering 145