Altexsoft

FEBRUARY 8, 2021

Here’s also a video for an overview of demand forecasting and predictive analytics. There are two main approaches to demand planning: Traditional statistical methods make forecasts based on historical data and assume the continuation of existing trends. Cost control. Shipment tracking and vehicle maintenance.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Apiumhub

APRIL 8, 2021

Ronald van Loon has been recognized among the top 10 global influencers in Big Data, analytics, IoT, BI, and data science. As the director of Advertisement, he works to help data-driven businesses be more successful. Schloss’s areas of expertise include Big Data, analytics, BI, IoT, and data warehousing.

Artificial Inteligence 109

Artificial Inteligence Technical Advisors Data Machine Learning 109

Mobilunity

DECEMBER 28, 2022

Neural networks are composed of interconnected processing nodes called neurons, which can learn to recognize patterns of input data. Computer vision involves using software to interpret digital images and videos so they can be processed by a computer system. IoT development. Computer vision. Business intelligence. ML support.

Artificial Inteligence 52

Artificial Inteligence Machine Learning Engineering How To 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. Collecting data from connected sensors and external sources.

Software Review 52

Software Review Technical Review Software Technology 52

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

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 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

DECEMBER 9, 2020

Sometimes, a data or business analyst is employed to interpret available data, or a part-time data engineer is involved to manage the data architecture and customize the purchased software. At this stage, data is siloed, not accessible for most employees, and decisions are mostly not data-driven.

Analytics 102

Analytics Technical Review Technology Applications 102

Kentik

JUNE 4, 2019

By correlating an ever-wider set of traffic data into a single, instantly-queryable dataset (the Kentik Data Engine, aka KDE), we’re able to generate technical and business insights with direct, powerful relevance to your network operations. Understanding Our Video Traffic. How True Origin Works.

Video 56

Video Network Internet Groups 56

Coforge

AUGUST 31, 2020

According to a recent research by EY Insurance Consumer Research, more than 80% of customers are willing to use digital and remote contact channels (including web chat, email, mobile apps, video or phone) in place of interacting with insurers via agents or brokers.

Insurance 40

Insurance Technology Artificial Inteligence Policies 40

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

Confluent

JUNE 7, 2019

The Confluent Platform is an amazing toolbox, which every architect and data engineer should know of and utilize. Why does on-chain data matter? Any event, from IoT-supported delivery, trade, real estate transfer, to a bet in a prediction market is timestamped, censorship-resistant, and provable.

Blockchain 90

Blockchain Data Technical Review Software Review 90

Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. In other words, Kafka can serve as a messaging system, commit log, data integration tool, and stream processing platform. By the way, you can watch our video to understand how APIs work in general.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Altexsoft

JUNE 26, 2023

Both data integration and ingestion require building data pipelines — series of automated operations to move data from one system to another. For this task, you need a dedicated specialist — a data engineer or ETL developer. Data engineering explained in 14 minutes. How systems exchange data.

Artificial Inteligence 52

Artificial Inteligence Machine Learning Data Systems Review 52

Altexsoft

MAY 14, 2021

To understand Big Data, you need to get acquainted with its attributes known as the four V’s: Volume is what hides in the “big” part of Big Data. This relates to terabytes to petabytes of information coming from a range of sources such as IoT devices, social media, text files, business transactions, etc.

Big Data 78

Big Data Analytics Tools Applications 78

Altexsoft

JULY 18, 2023

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. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. Stream processing.

Weak Development Team 52

Weak Development Team Big Data Data Artificial Inteligence 52

Altexsoft

SEPTEMBER 10, 2021

These systems can be hosted on-premises, in the cloud, and on IoT devices, etc. With the right data integration strategy, companies can consolidate the needed data into a single place and ensure its integrity and quality for better and more reliable insights. Learn more on how data engineering works from our video.

Tools 52

Tools Data Software Review Technical Review 52

Altexsoft

NOVEMBER 10, 2021

Key data warehouse limitations: Inefficiency and high costs of traditional data warehouses in terms of continuously growing data volumes. Inability to handle unstructured data such as audio, video, text documents, and social media posts. Moreover, they support real-time data, e.g., streams from IoT devices.

Architecture 52

Architecture Data Storage Artificial Inteligence 52

Altexsoft

NOVEMBER 23, 2021

If the transformation step comes after loading (for example, when data is consolidated in a data lake or a data lakehouse ), the process is known as ELT. You can learn more about how such data pipelines are built in our video about data engineering. Identify your consumers.

Virtualization 69

Virtualization Tools Data Architecture 69

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. No real-time data processing. Complex programming environment.

Big Data 98

Big Data Tools Data Storage 98

CIO

JULY 5, 2023

To this end, it will promote the use of disruptive AI technologies such as large language models or those that allow the generation of images, video, audio, or code, among others. At the technological forefront To reach its goal, Casado will rely on a strategic package of cutting-edge technologies.

Artificial Inteligence 231

Artificial Inteligence Generative AI Energy Strategic Planning 231

Altexsoft

MARCH 14, 2023

That’s why some MDS tools are commercial distributions designed to be low-code or even no-code, making them accessible to data practitioners with minimal technical expertise. This means that companies don’t necessarily need a large data engineering team. Data democratization. Data sources component in a modern data stack.

Data 59

Data Technical Review Software Review Artificial Inteligence 59