Trigent

AUGUST 26, 2022

Trigent offers end-to-end consulting services, design, development, and managed services across Infrastructure, Cloud, Mobility, BI, Analytics, Product Engineering, Quality Engineering, IoT, Data Engineering, and Artificial Intelligence. Transform your business with Trigent Software.

Software Review 52

Software Review Software Technical Review Artificial Intelligence 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

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. What is a data lake?

Architecture 52

Architecture Data Storage Machine Learning 52

CTOvision

JUNE 15, 2015

They also launched a plan to train over a million data scientists and data engineers on Spark. ARMONK, NY - 15 Jun 2015: IBM (NYSE:IBM) today announced a major commitment to Apache®Spark™, potentially the most important new open source project in a decade that is being defined by data.

Open Source 117

Open Source Big Data Machine Learning Artificial Inteligence 117

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

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

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. CIO 100, Digital Transformation, Healthcare Industry, Predictive Analytics

Artificial Inteligence 334

Artificial Inteligence Analytics Artificial Intelligence Machine Learning 334

DataRobot

MARCH 10, 2022

This “revolution” stems from breakthrough advancements in artificial intelligence, robotics, and the Internet of Things (IoT). Python is unarguably the most broadly used programming language throughout the data science community. IoT Empowered Assembly Lines: Predictive Maintenance. Native Python Support for Snowpark.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning IoT 52

Existek

JANUARY 11, 2022

The cloud computing market covers many areas like business processes, infrastructure, platform, security, management, analytics supported by cloud providers. And companies that have completed it emphasize gained advantages like accessibility, scalability, cost-effectiveness, etc. . Data and analytics. Internet of Things.

Azure 52

Azure AWS Cloud How To 52

Altexsoft

AUGUST 25, 2020

That’s why a data specialist with big data skills is one of the most sought-after IT candidates. Data Engineering positions have grown by half and they typically require big data skills. Data engineering vs big data engineering. Big data processing. maintaining data pipeline.

Big Data 75

Big Data Data Engineering Engineering Data 75

Agile Engine

DECEMBER 2, 2019

Rankings of this kind seem even more meaningful and important when they come from analytics firms focused on technology and software. The market analytics hub TechReviewer named AgileEngine among the leading providers of software development services. In November, AgileEngine appeared in one of the rankings of this kind.

Software 19

Software Company Blockchain Software Development 19

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

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

MAY 14, 2021

And that’s the most important thing: Big Data analytics helps companies deal with business problems that couldn’t be solved with the help of traditional approaches and tools. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics.

Big Data 78

Big Data Analytics Tools Applications 78

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

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.

Tools 52

Tools Software Review Systems Review Testing 52

Altexsoft

MARCH 16, 2021

In general, a data infrastructure is a system of hardware and software tools used to collect, store, transfer, prepare, analyze, and visualize data. Check our article on data engineering to get a detailed understanding of the data pipeline and its components. Big data infrastructure in a nutshell.

Big Data 116

Big Data Healthcare Applications Data 116

Altexsoft

JULY 18, 2023

Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics. Its flexibility allows it to operate on single-node machines and large clusters, serving as a multi-language platform for executing data engineering , data science , and machine learning tasks.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Altexsoft

JULY 19, 2022

She formulated the thesis in 2018 and published her first article “How to Move Beyond a Monolithic Data Lake to a Distributed Data Mesh” in 2019. So, to avoid any confusion, please be aware that data mesh is NOT. Some organizational approaches to analytics ownership are explained in our article about data science teams.

Architecture 52

Architecture Data Analytics Data Engineering 52

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. They used a time series data base (TSDB) which is optimized for measuring change over time and makes time series data very different than other data workloads.

Healthcare 61

Healthcare Tourism Systems Review Energy 61

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. process data in real time and run streaming analytics. Scalability.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

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

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. There are two main approaches to data integration.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Altexsoft

JUNE 7, 2021

As a result, a Big Data analytics task is split up, with each machine performing its own little part in parallel. scalability. Map operations deal with data filtering, sorting, and splitting while Reduce stage takes care of aggregating and summarizing results. No real-time data processing.

Big Data 98

Big Data Tools Data Storage 98

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.

Virtualization 69

Virtualization Tools Data Architecture 69

Altexsoft

OCTOBER 24, 2019

Enterprise data warehouse vs usual data warehouse: what’s the difference? Any data warehouse is a database which is always connected with raw-data sources via data integration tools on one end and analytical interfaces on the other. Reflects the source data. Subject-oriented data.

Architecture 50

Architecture Enterprise Data Technical Review 50

Altexsoft

NOVEMBER 10, 2021

Better data management: Not only can lakehouses keep large volumes of diverse data, but they also allow multiple use cases for it, including advanced analytics, reporting, and machine learning. Key features of a data lakehouse. Moreover, they support real-time data, e.g., streams from IoT devices.

Architecture 52

Architecture Data Storage Machine Learning 52

Kentik

DECEMBER 15, 2016

Needless to say, this call-out by analysts Nolan Greene and Rohit Mehra reflects well on what we’ve been doing to advance the state of the art in areas such as DDoS protection, infrastructure visibility, performance monitoring, and peering analytics. Why Kentik? That’s cloud-washing, a phenomenon that should be approached with wariness.

UI/UX 40

UI/UX Innovation Big Data Network 40

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.

Big Data 52

Big Data Analytics Data Analysis 52

CIO

AUGUST 3, 2022

In today’s data economy, in which software and analytics have emerged as the key drivers of business, CEOs must rethink the silos and hierarchies that fueled the businesses of the past. They can no longer have “technology people” who work independently from “data people” who work independently from “sales” people or from “finance.”

SDLC 350

SDLC IoT Machine Learning Artificial Inteligence 350

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

According to an IDG survey , companies now use an average of more than 400 different data sources for their business intelligence and analytics processes. What’s more, 20 percent of these companies are using 1,000 or more sources, far too many to be properly managed by human data engineers. Conclusion.

Data 40

Data Nonprofit Quality Assurance Education 40