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 84

Innovation Data Technical Review Artificial Inteligence 84

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.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Hu's Place - HitachiVantara

APRIL 11, 2019

Few Data Management Frameworks are Business Focused Data management has been around since the beginning of IT, and a lot of technology has been focused on big data deployments, governance, best practices, tools, etc. However, large data hubs over the last 25 years (e.g., What has changed since then?

Data Engineering 81

Data Engineering Machine Learning Artificial Inteligence Technical Review 81

CTOvision

JUNE 15, 2015

They also launched a plan to train over a million data scientists and data engineers on Spark. As data and analytics are embedded into the fabric of business and society –from popular apps to the Internet of Things (IoT) –Spark brings essential advances to large-scale data processing.

Open Source 117

Open Source Big Data Machine Learning Artificial Inteligence 117

Cloudera

JANUARY 20, 2021

The missing chapter is not about point solutions or the maturity journey of use cases, the missing chapter is about the data, it’s always been about the data, and most importantly the journey data weaves from edge to artificial intelligence insight. .

Data 106

Data Artificial Inteligence Analytics Machine Learning 106

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

ParkMyCloud

DECEMBER 11, 2020

As another free Google Cloud training option, Google has also teamed up with Coursera , an online learning platform founded by Stanford professors, to offer courses online so you can “skill up from anywhere.”. Here you’ll learn new skills in a GCP environment and earn cloud badges along the way. Plural Sight.

Google Cloud 97

Google Cloud Training Resources Cloud 97

Hu's Place - HitachiVantara

NOVEMBER 11, 2018

REAN Cloud is a global cloud systems integrator, managed services provider and solutions developer of cloud-native applications across big data, machine learning and emerging internet of things (IoT) spaces. We are all thrilled to welcome them to our own team of talented professionals.

Cloud 78

Cloud Google Cloud Azure AWS 78

Altexsoft

AUGUST 25, 2020

Big data can be quite a confusing concept to grasp. What to consider big data and what is not so big data? Big data is still data, of course. But it requires a different engineering approach and not just because of its amount. Data engineering vs big data engineering.

Big Data 75

Big Data Data Engineering Engineering Data 75

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

Mobilunity

MAY 8, 2023

Key zones of an Enterprise Data Lake Architecture typically include ingestion zone, storage zone, processing zone, analytics zone, and governance zone. Ingestion zone is where data is collected from various sources and ingested into the data lake. Storage zone is where the raw data is stored in its original format.

Engineering 52

Engineering Data Storage AWS 52

Altexsoft

JUNE 14, 2021

Lemonade uses Natural Action Synthesis and Natural Language Processing to ensure that Maya gets smarter the more it chats. This is possible because their machine learning model is retrained almost daily. Your vision on personalization may not work for every business model. Personalization isn’t a one-time project.

Insurance 88

Insurance Machine Learning Artificial Inteligence Policies 88

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 45

Course Training Artificial Inteligence Machine Learning 45

CIO

OCTOBER 18, 2023

German healthcare company Fresenius Medical Care, which specializes in providing kidney dialysis services, is using a combination of near real-time IoT data and clinical data to predict one of the most common complications of the procedure.

Artificial Inteligence 334

Artificial Inteligence Analytics Artificial Intelligence Machine Learning 334

Trigent

NOVEMBER 3, 2022

Thankfully, it’s now a game for new technologies and leveraging structured and unstructured data like no other. The future of the global supply chain market lies in IoT, integrated solutions, data, and mobility. Connected logistics devices generate a massive amount of data. Delivering value in connected logistics.

Analytics 52

Analytics Data IoT Trends 52

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

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 Machine Learning Artificial Inteligence Data Engineering 41

Altexsoft

APRIL 13, 2023

“Control towers are the artificial intelligence (AI) of supply chain. The readings from IoT sensors and other connected devices (e.g., External data sources To deliver comprehensive visibility and make accurate forecasts, your SCCT must collect data from external sources.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Altexsoft

JULY 18, 2023

On the other hand, the term spark often brings to mind a tiny particle that, despite its size, can start a large fire. These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Big data processing.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

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

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

Cloudera

FEBRUARY 19, 2018

Running a large company is impossible without having an ERP system in place, and SAP business software remains at the forefront in this category. But when companies are looking towards new technologies such as data lakes, machine learning or predictive analytics, SAP alone is just not enough.

Data 46

Data Government Big Data Compliance 46

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 Microservices 10

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: slideshare.net/SparkSummit.

Analytics 20

Analytics Data IoT Analysis 20

Altexsoft

MAY 14, 2021

Big Data enjoys the hype around it and for a reason. But the understanding of the essence of Big Data and ways to analyze it is still blurred. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics. Key Big Data characteristics.

Big Data 78

Big Data Analytics Tools Applications 78

Altexsoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Which Big Data tasks does Spark solve most effectively? How does it work?

Big Data 98

Big Data Tools Data Storage 98

ParkMyCloud

JANUARY 17, 2020

AWS Certified Big Data – Speciality. For individuals who perform complex Big Data analyses and have at least two years of experience using AWS. Implement core AWS Big Data services according to basic architecture best practices. Design and maintain Big Data. Azure Data Engineer Associate.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

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. As we move into a world that is more and more dominated by technologies such as big data, IoT, and ML, more and more processes will be started by external events.

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

Existek

JANUARY 11, 2022

For example, they considerably revised the cloud strategy due to the need to transform the delivery model from PaaS to IaaS, thus renaming Windows Azure to Microsoft Azure in 2014. . Along with meeting customer needs for computing and storage, they continued extending services by presenting products dealing with analytics, Big Data, and IoT.

Azure 52

Azure AWS Cloud How To 52

ParkMyCloud

MAY 29, 2019

BI Analyst can also be described as BI Developers, BI Managers, and Big Data Engineer or Data Scientist. IoT Engineer. The main responsibility of IoT engineers is to help businesses keep up with IoT technology trends. Data Detective. Man-Machine Teaming Manager.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

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

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

Altexsoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. Data availability.

Tools 52

Tools Software Review Systems Review Testing 52

Altexsoft

FEBRUARY 22, 2022

Such an approach requires a great deal of investment since a whole ecosystem has to be created, including IoT sensors installation, acquiring specialized software, creating and maintaining machine learning (ML) models, engaging IT and data science specialists , and so on. Processing data.

Software Review 52

Software Review Technical Review Software Technology 52

Altexsoft

AUGUST 22, 2022

A data fabric is an architecture design presented as an integration and orchestration layer built on top of multiple disjointed data sources like relational databases , data warehouses , data lakes, data marts , IoT , legacy systems, etc., to provide a unified view of all enterprise data.

Architecture 52

Architecture Artificial Inteligence Technical Review Data 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

Altexsoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Inability to handle unstructured data such as audio, video, text documents, and social media posts. Key features of a data lakehouse.

Architecture 52

Architecture Data Storage Machine Learning 52