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

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 Artificial Inteligence Machine Learning 117

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 200

Artificial Inteligence Analytics Machine Learning Artificial Intelligence 200

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 Artificial Inteligence Machine Learning Technical Review 81

Capgemini

MARCH 16, 2022

technologies (AI & analytics, cloud and edge computing, cybersecurity, 5G, IoT, and data engineering) are converging at speed. Big data management and analytics : The implementation of AI and predictive analytics, enables the automation of routine tasks allowing humans to focus on making higher-level decisions.

Industry 98

Industry IoT Technical Review Automotive 98

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

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics.

Weak Development Team 52

Weak Development Team Big Data Data Artificial Inteligence 52

Kentik

JANUARY 3, 2018

Looking into Network Monitoring in an IoT enabled network. As part of the movement, organizations are also looking to benefit from the Internet of Things (IoT). IoT infrastructure represents a broad diversity of technology. So, how can digital businesses cope with these challenges without giving up on IoT?

IoT 40

IoT Network Tools Big Data 40

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. This April, 47Lining, announced its Amazon Web Services (AWS) Industrial Time Series Data Connector Quick Start.

Cloud 78

Cloud Google Cloud Azure AWS 78

CIO

FEBRUARY 14, 2023

Titanium Intelligent Solutions, a global SaaS IoT organization, even saved one customer over 15% in energy costs across 50 distribution centers , thanks in large part to AI. report they have established a data culture 26.5% report they have a data-driven organization 39.7% report they are managing data as a business asset 47.4%

Artificial Inteligence 174

Artificial Inteligence Strategy Data Machine Learning 174

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. The Future of Cloud Computing Jobs.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

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.

Artificial Inteligence 107

Artificial Inteligence Machine Learning Scalability Data Engineering 107

CTOvision

FEBRUARY 23, 2017

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. If you want to tap into the opportunity that big data presents, you want to be there. Data scientists. Data engineers. Product managers.

Big Data 61

Big Data Case Study Artificial Inteligence Artificial Intelligence 61

Apiumhub

FEBRUARY 6, 2023

In this event, hundreds of innovative minds, enterprise practitioners, technology providers, startup founders, and innovators come together to discuss ideas on data science, big data, ML, AI, data management, data engineering, IoT, and analytics.

Innovation 82

Innovation Data Artificial Inteligence Machine Learning 82

ParkMyCloud

DECEMBER 11, 2020

Coursera includes a number of free courses including topics in Machine Learning, Architecting, Data Engineering, Developing Applications, and the list goes on. . In conjunction with Coursera, Google Cloud offers hands-on training with specialized labs available via Qwiklabs , a learning lab environment for developers. Plural Sight.

Google Cloud 97

Google Cloud Training Resources Cloud 97

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

Cloudera

JANUARY 20, 2021

Managing the collection of all the data from all factories in the manufacturing process is a significant undertaking that presents a few challenges: Difficulty assessing the volume and variety of IoT data: Many factories utilize both modern and legacy manufacturing assets and devices from multiple vendors, with various protocols and data formats.

Data 111

Data Artificial Inteligence Analytics Machine Learning 111

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

TIBCO - Connected Intelligence

AUGUST 10, 2020

Taking action to leverage your data is a multi-step journey, outlined below: First, you have to recognize that sticking to the status quo is not an option. Your data demands, like your data itself, are outpacing your data engineering methods and teams.

Virtualization 69

Virtualization Data How To Data Engineering 69

Cloudera

JANUARY 19, 2018

There’s more data coming, and there are plenty of impossible things to work on. Machine Learning in the Age of Big Data. 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

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

Altexsoft

FEBRUARY 8, 2021

Machine learning techniques analyze big data from various sources, identify hidden patterns and unobvious relationships between variables, and create complex models that can be retrained to automatically adapt to changing conditions. Today, consumers’ preferences are changing momentarily and often chaotically. Cost control.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Hu's Place - HitachiVantara

MARCH 18, 2019

City of Istanbul Governorship: Safe, Smart Campus The challenge was to secure the governorship campus and include multiple existing video and IoT systems. Pentaho unlocked mapR to enable data science and enabled business users to operationalize data through self-service.

Healthcare 61

Healthcare Tourism Systems Review Energy 61

Altexsoft

JUNE 14, 2021

On top of that, the company uses big data analytics to quantify losses and predict risks by placing the client into a risk group and quoting a relevant premium. You can start investing in data infrastructure and analytical pipelines to automate data collection and analysis mechanisms.

Insurance 88

Insurance Artificial Inteligence Machine Learning Policies 88

O'Reilly Media - Ideas

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena.

Conference 8

Conference Data Data Engineering Big Data 8

Altexsoft

OCTOBER 21, 2022

It offers high throughput, low latency, and scalability that meets the requirements of Big Data. The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

Cloudera

MARCH 6, 2018

Altus SDX enables companies to more easily build and deploy high-value applications for customer analytics, IoT, cyber-security, and more. Nimbly run many distinct applications against shared data. Facilitates productivity and development efficiency by making all data safely accessible in one place.

Analytics 40

Analytics Cloud Big Data AWS 40

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

Mobilunity

DECEMBER 27, 2024

Data Handling and Big Data Technologies Since AI systems rely heavily on data, engineers must ensure that data is clean, well-organized, and accessible. Do AI-specialized experts need to understand big data technologies? Are AI Engineers and Data Scientists the same?

Artificial Inteligence 52

Artificial Inteligence Technical Review Engineering Artificial Intelligence 52

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

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 Data Engineering 52

Altexsoft

NOVEMBER 23, 2021

But this data is all over the place: It lives in the cloud, on social media platforms, in operational systems, and on websites, to name a few. Not to mention that additional sources are constantly being added through new initiatives like big data analytics , cloud-first, and legacy app modernization. Identify your consumers.

Virtualization 69

Virtualization Tools Data Architecture 69

Kentik

DECEMBER 15, 2016

IDC’s recognition of Kentik was two-fold, based not only on the fact that we’re SaaS/cloud-based (in fact, we also can deploy our big data solution on an on-premises cluster) but also on the deep capabilities of our Kentik Detect product. The rise of IoT is evidence of that, with normal/offline lifestyles becoming digitally connected.

UI/UX 40

UI/UX Innovation Big Data Network 40

BPM

JANUARY 18, 2019

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. AI-enabled data engines will provide insight about what processes can be redesigned and/or automated. Lloyd Dugan BPM.com [link]. 2019, oh my!

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

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. Please note!

Tools 52

Tools Software Review Systems Review Testing 52

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. Enhance transparency.

Analytics 52

Analytics Data IoT Trends 52

Altexsoft

OCTOBER 2, 2020

Data integration and interoperability: consolidating data into a single view. Specialist responsible for the area: data architect, data engineer, ETL developer. Scattered across different storages in various formats, data values don’t talk to each other. Snowflake data management processes.

Strategy 64

Strategy Database Administration Data Technical Review 64