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

The demand for data skills (“the sexiest job of the 21st century”) hasn’t dissipated. LinkedIn recently found that demand for data scientists in the US is “off the charts,” and our survey indicated that the demand for data scientists and data engineers is strong not just in the US but globally.

Trends 91

Trends Data Machine Learning Artificial Inteligence 91

Trigent

AUGUST 26, 2022

The company holds decades of technical experience, immense knowledge of different domains, and technology expertise to deliver transformation solutions for small, medium, and large-level enterprises. Transform your business with Trigent Software.

Software Review 52

Software Review Software Technical Review Artificial Intelligence 52

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 81

Innovation Data Artificial Inteligence Machine Learning 81

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

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

TIBCO - Connected Intelligence

OCTOBER 11, 2021

One example of an incredible solution fueled by TIBCO Partner-to-Partner is a new IoT solution developed by TIBCO, iSteer, and u-blox. iSteer provides enterprise business solutions to build next-generation organizations by empowering fresh ideas and a strategic perspective to every engagement. Meet the Partners. The Solution in Action.

IoT 49

IoT Wireless Healthcare Technical Review 49

Cloudera

JANUARY 20, 2021

The six steps are: Data Collection – data ingestion and monitoring at the edge (whether the edge be industrial sensors or people in a brick and mortar retail store). Data Enrichment – data pipeline processing, aggregation & management to ready the data for further refinement.

Data 112

Data Artificial Inteligence Analytics Machine Learning 112

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

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 82

Innovation Data Technical Review Artificial Inteligence 82

TIBCO - Connected Intelligence

DECEMBER 16, 2020

Imagine you’re a data engineer at a Fortune 1000 company. You use data virtualization to create data views, configure security, and share data. One: Streaming Data Virtualization. All this data is in motion. But first-generation data virtualization tools are designed for data at rest.

Virtualization 64

Virtualization Data Data Engineering Quality Assurance 64

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). IoT Empowered Assembly Lines: Predictive Maintenance.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning IoT 52

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 Machine Learning 52

Confluent

FEBRUARY 6, 2019

This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. Impedance mismatch between data scientists, data engineers and production engineers. For now, we’ll focus on Kafka.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

Cloudera

JANUARY 19, 2018

Sean ascertains that larger data sets and increased access to compute power is propelling the adoption of machine learning. General Data Protection Regulation (GDPR) and Data Science. Last January we launched Apache Kudu, as part of Cloudera Enterprise 5.10. Apache Kudu: Top Use Cases for Real-Time Analytics.

Artificial Inteligence 46

Artificial Inteligence Machine Learning Big Data IoT 46

Hu's Place - HitachiVantara

JANUARY 3, 2019

In order to utilize the wealth of data that they already have, companies will be looking for solutions that will give comprehensive access to data from many sources. More focus will be on the operational aspects of data rather than the fundamentals of capturing, storing and protecting data.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

CTOvision

FEBRUARY 23, 2017

Attending is a great way to track the latest in the community, learn (and share) lessons learned and find the most capable technologies ready for enterprise use. This is the place to dive deep into the latest on Big Data, Analytics, Artificial Intelligence, IoT, and the massive cybersecurity issues in all those topics.

Big Data 61

Big Data Artificial Intelligence Artificial Inteligence Case Study 61

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

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

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

JULY 23, 2020

It facilitates collaboration between a data science team and IT professionals, and thus combines skills, techniques, and tools used in data engineering, machine learning, and DevOps — a predecessor of MLOps in the world of software development. MLOps lies at the confluence of ML, data engineering, and DevOps.

Artificial Inteligence 145

Artificial Inteligence Machine Learning DevOps Tools 145

Altexsoft

JUNE 25, 2019

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. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

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. Modern data warehousing.

Data 41

Data Machine Learning Artificial Inteligence Data Engineering 41

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 Management

Organization 278

Organization Technical Review Data Artificial Inteligence 278

O'Reilly Media - Ideas

MAY 1, 2019

Spotlight on Data: Caching Big Data for Machine Learning at Uber with Zhenxiao Luo , June 17. Introduction to Distributed Ledger Technology for Enterprise , July 10. Spotlight on Data: Data as an Asset with Friederike Schüür and Jen van der Meer , May 20. Data science and data tools.

Course 46

Course Training Artificial Inteligence Machine Learning 46

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. Source: www.oracle.com.

Analytics 20

Analytics Data IoT Analysis 20

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. Both small businesses and enterprises shift computing tasks to the cloud.

Azure 52

Azure AWS Cloud How To 52

Cloudera

FEBRUARY 19, 2018

Breaking down data silos is on a to-do list of every CIO aiming to sharpen their competitive edge. As a critical enterprise application, there is no room to just tinker around with it in a way that would invalidate SAP’s terms around approved data exchange and mechanisms.

Data 48

Data Government Big Data Compliance 48

Apiumhub

SEPTEMBER 20, 2023

Tech Conferences Compass Tech Summit – October 5-6 Compass Tech Summit is a remarkable 5-in-1 tech conference, encompassing topics such as engineering leadership, AI, product management, UX, and data engineering that will take place on October 5-6 at the Hungarian Railway Museum in Budapest, Hungary.

Conference 95

Conference Artificial Inteligence UI/UX Machine Learning 95

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

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

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

Altexsoft

FEBRUARY 8, 2021

Manufacturing is typically characterized by producing a lot of various disparate data that is hard to organize and analyze, especially with the spread of Internet of Things (IoT) devices. Data can be obtained from both inside your organization across different departments and outside it. Cost control.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

ParkMyCloud

JANUARY 17, 2020

Azure Data Engineer Associate. For individuals that design and implement the management, security, monitoring, and privacy of data – using the full stack of Azure data services – to satisfy business needs. . Azure IoT Developer Specialty. Available certifications include : Associate Cloud Engineer.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

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 Artificial Inteligence Case Study 52

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

Kentik

MAY 31, 2023

Reliability is a massive burden for network operators While DevOps teams and their SREs focus on the reliability of the application environment, an enterprise’s network concerns often extend well beyond the uptime of a suite of customer-facing web and mobile apps.

Network 52

Network Cloud Load Balancer Firewall 52