Kentik

JANUARY 3, 2018

Looking into Network Monitoring in an IoT enabled network. Whether financial, healthcare, energy, manufacturing, or web enterprises, across all industries, a common goal is digitizing the organization as fast as possible. As part of the movement, organizations are also looking to benefit from the Internet of Things (IoT).

IoT 40

IoT Network Tools Big Data 40

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 87

Trends Data Machine Learning Artificial Inteligence 87

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

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. Transform your business with Trigent Software.

Software Review 52

Software Review Software Technical Review Artificial Intelligence 52

Cloudera

JANUARY 20, 2021

Most of what is written though has to do with the enabling technology platforms (cloud or edge or point solutions like data warehouses) or use cases that are driving these benefits (predictive analytics applied to preventive maintenance, financial institution’s fraud detection, or predictive health monitoring as examples) not the underlying data.

Data 106

Data Artificial Inteligence Analytics Machine Learning 106

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 84

Innovation Data Technical Review Artificial Inteligence 84

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

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

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

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.

Cloud 78

Cloud Google Cloud Azure AWS 78

Confluent

FEBRUARY 6, 2019

It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

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 Machine Learning Artificial Inteligence 117

Altexsoft

APRIL 13, 2023

The annual IHS Markit Supply Chain Survey Report found that 63 percent of companies don’t have sufficient technology to approach their top priority optimization strategy, i.e., spend analytics (the situation within other strategic areas is similar). It also often includes analytics, reporting, and forecasting capabilities.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

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. Happy New Year and welcome to 2019, a year full of possibilities.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

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

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.

Analytics 20

Analytics Data IoT Analysis 20

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. Apache Kudu: Top Use Cases for Real-Time Analytics. Last January we launched Apache Kudu, as part of Cloudera Enterprise 5.10.

Artificial Inteligence 45

Artificial Inteligence Machine Learning Big Data IoT 45

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

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

CIO

NOVEMBER 29, 2022

Here, I’ll highlight the where and why of these important “data integration points” that are key determinants of success in an organization’s data and analytics strategy. For data warehouses, it can be a wide column analytical table. Data and cloud strategy must align.

Organization 268

Organization Technical Review Data Artificial Inteligence 268

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

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

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

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

Existek

JANUARY 11, 2022

The cloud computing market covers many areas like business processes, infrastructure, platform, security, management, analytics supported by cloud providers. They quickly met the full range of enterprise needs starting from SaaS to PaaS and IaaS. Data and analytics. Cloud migration and modernization. Internet of Things.

Azure 52

Azure AWS Cloud How To 52

O'Reilly Media - Ideas

MAY 1, 2019

Real-Time Streaming Analytics and Algorithms for AI Applications , May 15. 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. Data science and data tools. First Steps in Data Analysis , May 20.

Course 45

Course Training Artificial Inteligence Machine Learning 45

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

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 46

Data Government Big Data Compliance 46

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 108

Data Machine Learning Artificial Inteligence Analytics 108

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 97

Conference Artificial Inteligence UI/UX Machine Learning 97

DataRobot

APRIL 1, 2018

Paxata was a Silver Sponsor at the recent Gartner Data and Analytics Summit in Grapevine Texas. Although some product solutions disrupted the operational reporting market, they require users to know the questions they need to ask their data. 2) Line of business is taking a more active role in data projects.

Analytics 40

Analytics Artificial Inteligence Data Machine Learning 40

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. Instead, they have separate data stores and inconsistent (if any) frameworks for data governance, management, and security.

Analytics 40

Analytics Cloud Big Data AWS 40

Altexsoft

MARCH 31, 2020

It means you must collect transactional data and move it from the database that supports transactions to another system that can handle large volumes of data. Only after these actions can you analyze data with dedicated software (a so-called online analytical processing or OLAP system). But how do you move data?

Data 76

Data Storage Analytics Data Center 76

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

Datavail

JUNE 15, 2023

The Microsoft Fabric announcement at Microsoft Build 2023 has caused quite a stir in the data and analytics world. Microsoft Fabric is an all-in-one analytics solution that brings together seven Azure services on a shared SaaS foundation, in a unified experience combined with AI.

Azure 52

Azure Analytics Storage Generative AI 52

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