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

Altexsoft

MARCH 16, 2021

In this article, we will explain the concept and usage of Big Data in the healthcare industry and talk about its sources, applications, and implementation challenges. What is Big Data and its sources in healthcare? So, what is Big Data, and what actually makes it Big? Let’s see where it can come from.

Big Data 116

Big Data Healthcare Applications Data 116

Altexsoft

AUGUST 29, 2023

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. This article explains what a data lake is, its architecture, and diverse use cases. Watch our video explaining how data engineering works.

Architecture 52

Architecture Data Storage Machine Learning 52

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 Machine Learning 52

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

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. Scalability.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

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

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

Existek

JANUARY 11, 2022

And companies that have completed it emphasize gained advantages like accessibility, scalability, cost-effectiveness, etc. . Along with meeting customer needs for computing and storage, they continued extending services by presenting products dealing with analytics, Big Data, and IoT. Read the article.

Azure 52

Azure AWS Cloud How To 52

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? scalability.

Big Data 98

Big Data Tools Data Storage 98

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

ParkMyCloud

JANUARY 17, 2020

Individuals in an associate solutions architect role have 1+ years of experience designing available, fault-tolerant, scalable, and most importantly cost-efficient, distributed systems on AWS. Must prove knowledge of deploying, operating and managing highly available, scalable and fault-tolerant systems on AWS.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

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. Scalability. Data availability.

Tools 52

Tools Software Review Systems Review Testing 52

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

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. Still, it’s the number one choice for data-driven companies, and here’re some reasons why.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

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. Tupras had no unified/scalable way to discover the (sliced content) on open TSDB and no framework for data science and no way to operationalize data science.

Healthcare 61

Healthcare Tourism Systems Review Energy 61

Altexsoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. For this task, you need a dedicated specialist — a data engineer or ETL developer.

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

Altexsoft

NOVEMBER 10, 2021

A data lake is a repository to store huge amounts of raw data in its native formats ( structured, unstructured, and semi-structured ) and in open file formats such as Apache Parquet for further big data processing, analysis, and machine learning purposes. Open formats support. Decoupled storage and compute. websites, etc.

Architecture 52

Architecture Data Storage Machine Learning 52

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

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

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. Cloudera Data Platform capabilities.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Altexsoft

OCTOBER 24, 2019

An enterprise data warehouse is a unified repository for all corporate business data ever occurring in the organization. Reflects the source data. EDW sources data from its original storages like Google Analytics, CRMs, IoT devices, whatever these can be. Subject-oriented data. IBM Db2 / Pricing page.

Architecture 50

Architecture Enterprise Data Technical Review 50

Agile Engine

DECEMBER 27, 2023

From emerging trends to hiring a data consultancy, this article has everything you need to navigate the data analytics landscape in 2024. What is a data analytics consultancy? Big data consulting services 5. 4 types of data analysis 6. Data analytics use cases by industry 7. Table of contents 1.

Big Data 52

Big Data Analytics Data Analysis 52

Cloudera

MAY 18, 2021

The intent of this article is to articulate and quantify the value proposition of CDP Public Cloud versus legacy IaaS deployments and illustrate why Cloudera technology is the ideal cloud platform to migrate big data workloads off of IaaS deployments. data streaming, data engineering, data warehousing etc.),

Cloud 84

Cloud Technical Review Storage Backup 84

Altexsoft

MARCH 14, 2023

In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support. This development has paved the way for a suite of cloud-native data tools that are user-friendly, scalable, and affordable. What is a modern data stack?

Data 59

Data Technical Review Software Review Artificial Inteligence 59

Datavail

SEPTEMBER 8, 2022

Big data presents challenges in terms of volume, velocity, and variety—but that doesn’t mean you have to suffer from a bloated IT ecosystem to address these challenges. In fact, many businesses can realize significant advantages from streamlining their data integration pipelines, trimming away unnecessary tools and services.

Data 40

Data Nonprofit Quality Assurance Education 40