CIO

JULY 18, 2023

CIO.com’s 2023 State of the CIO survey recently zeroed in on the technology roles that IT leaders find the most difficult to fill, with cybersecurity, data science and analytics, and AI topping the list. As a result, many enterprise IT leaders find themselves in bidding wars they’re unable to win. “The

Technical Advisors 246

Technical Advisors Artificial Inteligence Generative AI How To 246

O'Reilly Media - Ideas

JANUARY 8, 2019

In a recent O’Reilly survey , we found that the skills gap remains one of the key challenges holding back the adoption of machine learning. The demand for data skills (“the sexiest job of the 21st century”) hasn’t dissipated. Continuing investments in (emerging) data technologies. Burgeoning IoT technologies.

Trends 83

Trends Data Machine Learning Artificial Inteligence 83

Apiumhub

FEBRUARY 6, 2023

We are excited to announce that for the second year in a row , Apiumhub will support the Data Innovation Summit , which will take place on May 11th and 12th in Kistamässan, Stockholm. It’s a fantastic opportunity to network and learn from case studies and outstanding industry leaders.

Innovation 82

Innovation Data Artificial Inteligence Machine Learning 82

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 Artificial Inteligence Machine Learning Technical Review 81

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

Cloudera

JANUARY 20, 2021

Reporting – delivering business enterprise insight (sales analysis and forecasting, market research, budgeting as examples). Predictive Analytics – predictive analytics based upon AI and machine learning (Fraud detection, predictive maintenance, demand based inventory optimization as examples).

Data 112

Data Artificial Inteligence Analytics Machine Learning 112

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 83

Innovation Data Technical Review Artificial Inteligence 83

Mobilunity

MAY 8, 2023

An Enterprise Data Lake is a large, centralized repository that stores structured and unstructured data at scale. 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.

Engineering 52

Engineering Data Storage AWS 52

Cloudera

JANUARY 19, 2018

Machine Learning in the Age of Big Data. Sean Anderson provides a tutorial on machine learning. From its origins in the 1950’s to today, the age of big data. Sean ascertains that larger data sets and increased access to compute power is propelling the adoption of machine learning.

Artificial Inteligence 46

Artificial Inteligence Machine Learning Big Data IoT 46

Altexsoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Architecture 52

Architecture Data Storage Artificial Inteligence 52

DataRobot

MARCH 10, 2022

DataRobot and Snowflake Jointly Unleash Human and Machine Intelligence Across the Industrial Enterprise Landscape. This “revolution” stems from breakthrough advancements in artificial intelligence, robotics, and the Internet of Things (IoT). High-level example of a common machine learning lifecycle.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning IoT 52

Hu's Place - HitachiVantara

NOVEMBER 11, 2018

Private clouds are not simply existing data centers running virtualized, legacy workloads. They require highly modernized digital application and service environments running on true cloud platforms like Hitachi Enterprise Cloud. We are all thrilled to welcome them to our own team of talented professionals.

Cloud 78

Cloud Google Cloud Azure AWS 78

CTOvision

JUNE 15, 2015

You know Spark, the free and open source complement to Apache Hadoop that gives enterprises better ability to field fast, unified applications that combine multiple workloads, including streaming over all your data. They also launched a plan to train over a million data scientists and data engineers on Spark.

Open Source 117

Open Source Big Data Artificial Inteligence Machine Learning 117

Cloudera

MAY 10, 2018

Click to tweet : Nominations are now open for the sixth annual Cloudera Data Impact Awards! With advancements in exploratory data science, machine learning, predictive analytics, AI, and data engineering, the world is increasingly driven by data. Enterprise machine learning.

Data 41

Data Artificial Inteligence Machine Learning Data Engineering 41

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 44

Course Training Artificial Inteligence Machine Learning 44

Altexsoft

AUGUST 25, 2020

Big data fosters the development of new tools for transporting, storing, and analyzing vast amounts of unstructured data. Prominent enterprises in numerous sectors including sales, marketing, research, and healthcare are actively collecting big data. Data engineering vs big data engineering.

Big Data 75

Big Data Data Engineering Engineering Data 75

Altexsoft

APRIL 13, 2023

Due to extensive usage of connected IoT devices and advanced processing technologies, SCCTs not only gather data and build operational reports but also create predictions, define the impact of various macro- and microeconomic factors on the supply chain, and run “what-if” scenarios to find the best course of action.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

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?

Artificial Inteligence 52

Artificial Inteligence Machine Learning Data Systems Review 52

CIO

NOVEMBER 29, 2022

For data warehouses, it can be a wide column analytical table. Many companies reach a point where the rate of complexity exceeds the ability of data engineers and architects to support the data change management speed required for the business. Data or derivatives of the data can also flow back into the data ecosystem.

Organization 274

Organization Technical Review Data Artificial Inteligence 274

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

OCTOBER 29, 2020

With the massive explosion of data across the enterprise — both structured and unstructured from existing sources and new innovations such as streaming and IoT — businesses have needed to find creative ways of managing their increasingly complex data lifecycle to speed time to insight.

Data 113

Data Artificial Inteligence Machine Learning Analytics 113

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. The Data 2030 Summit tech conference serves as a yearly roundtable gathering, uniting the Data Management community within a single forum.

Conference 96

Conference Artificial Inteligence UI/UX Machine Learning 96

Cloudera

FEBRUARY 19, 2018

But when companies are looking towards new technologies such as data lakes, machine learning or predictive analytics, SAP alone is just not enough. To keep up with tech trends, businesses have to face the challenges of integrating SAP with non-SAP technologies and embark on a crusade against data silos.

Data 47

Data Government Big Data Compliance 47

Existek

JANUARY 11, 2022

They quickly met the full range of enterprise needs starting from SaaS to PaaS and IaaS. Along with meeting customer needs for computing and storage, they continued extending services by presenting products dealing with analytics, Big Data, and IoT. Machine learning. Development Operations Engineer $122 000.

Azure 52

Azure AWS Cloud How To 52

Altexsoft

JANUARY 22, 2020

With the uprise of internet-of-things (IoT) devices, overall data volume increase, and engineering advancements in this field led to new ways of collecting, processing, and analysing data. As a result, it became possible to provide real-time analytics by processing streamed data. Oracle Stream Analytics.

Analytics 20

Analytics Data IoT Analysis 20

O'Reilly Media - Ideas

MARCH 6, 2019

Get hands-on training in machine learning, AWS, Kubernetes, Python, Java, and many other topics. Learn new topics and refine your skills with more than 170 new live online training courses we opened up for March and April on the O'Reilly online learning platform. AI and machine learning.

Course 10

Course Artificial Inteligence Training Machine Learning 10

ParkMyCloud

JANUARY 17, 2020

AWS Certified Machine Learning – Speciality. Intended for individuals in a development or data science role. Ability to design, implement, deploy and maintain machine learning solutions for specific business problems. . Azure Data Scientist Associate. Azure Data Engineer Associate.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

Altexsoft

FEBRUARY 8, 2021

To support the planning process, predictive analytics and machine learning (ML) techniques can be implemented. We have previously described demand forecasting methods and the role of machine learning solutions in a dedicated article. Comparison between traditional and machine learning approaches to demand forecasting.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

ParkMyCloud

MAY 29, 2019

As more and more enterprises drive value from container platforms, infrastructure-as-code solutions, software-defined networking, storage, continuous integration/delivery, and AI, they need people and skills on board with ever more niche expertise and deep technological understanding. IoT Engineer. Cloud Consultants.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

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. Enterprises must consider where and when to apply RPA, to achieve the expected value returns. Denis Gagne Trisotech [link]. Steven Stanton FCB Partners [link].

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

Altexsoft

OCTOBER 24, 2019

While our brain is both the processor and the storage, companies need multiple tools to work with data. And one of the most important ones is a data warehouse. In this article, we will discuss what an enterprise data warehouse is, its types and functions, and how it’s used in data processing.

Architecture 50

Architecture Enterprise Data Technical Review 50

Apiumhub

APRIL 5, 2022

M2- Data Engineering Stage: Technical track focusing on agile approaches to designing, implementing and maintaining a distributed data architecture to support a wide range of tools and frameworks in production. Presentations by some of the leading experts, researchers and practitioners in the area.

Innovation 52

Innovation Data Case Study Artificial Inteligence 52

DataRobot

APRIL 1, 2018

Today’s data management and analytics products have infused artificial intelligence (AI) and machine learning (ML) algorithms into their core capabilities. These modern tools will auto-profile the data, detect joins and overlaps, and offer recommendations. This paradigm has shifted and will continue to shift.

Analytics 40

Analytics Artificial Inteligence Data Machine Learning 40

Altexsoft

MARCH 31, 2020

These can be data science teams , data analysts, BI engineers, chief product officers , marketers, or any other specialists that rely on data in their work. The simplest illustration for a data pipeline. Data pipeline components. Data pipeline components. When do you need a data pipeline?

Data 76

Data Storage Analytics Data Center 76

Datavail

JUNE 15, 2023

It unifies the business model across all the different types of analytics workloads, whether they’re SQL, machine learning – whatever job you want, you can use the same compute infrastructure. Data Factory : A data integration tool with 150+ connectors to cloud and on-premises data sources.

Azure 52

Azure Analytics Storage Generative AI 52

Altexsoft

OCTOBER 26, 2022

To enable this conversion, a CDO uses digital information and modern technologies such as the cloud, the Internet of Things , mobile apps, social media, machine learning-based products, and digital marketing. This can be anything from CRMs to AI-powered chatbots to IoT systems. Attract talent. Business acumen.

CTO 52

CTO Organization Technical Review Culture 52

Cloudera

MARCH 6, 2018

The real power in machine learning and analytics is when multiple analytics disciplines are able to work together in concert, sharing data in service of solving more complex and more valuable questions. Nimbly run many distinct applications against shared data. Soon we’ll have Altus Data Science, too!

Analytics 40

Analytics Cloud Big Data AWS 40