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

Altexsoft

APRIL 13, 2023

Leading executives focus on building resilient and intelligent supply chains that can withstand the turmoil due to data-based proactive decisions. According to the PwC 2023 Digital Trends in Supply Chain Survey , 86 percent of respondents believe they should invest more in technology to identify, track, and measure supply chain risk.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Altexsoft

JULY 23, 2020

As a logical reaction to this problem, a new trend — MLOps — has emerged. 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.

Artificial Inteligence 145

Artificial Inteligence Machine Learning DevOps Tools 145

ParkMyCloud

MAY 29, 2019

Trends in cloud jobs can be overall indicators into trends in the cloud computing space. Here are some trends we’re seeing. Cloud Talent Demand Trends. BI Analyst can also be described as BI Developers, BI Managers, and Big Data Engineer or Data Scientist. IoT Engineer.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

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

Cloudera

FEBRUARY 19, 2018

But when companies are looking towards new technologies such as data lakes, machine learning or predictive analytics, SAP alone is just not enough. To keep up with tech trends, businesses have to face the challenges of integrating SAP with non-SAP technologies and embark on a crusade against data silos. SAP as a must-have.

Data 46

Data Government Big Data Compliance 46

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

Existek

JANUARY 11, 2022

Being a market leader, AWS continues bringing new trends and approaches. Along with meeting customer needs for computing and storage, they continued extending services by presenting products dealing with analytics, Big Data, and IoT. Want to find more on current market trends in cloud app development?

Azure 52

Azure AWS Cloud How To 52

Altexsoft

FEBRUARY 8, 2021

And planning, in turn, relies on understanding of current performance, past trends, existing risks, and possible future scenarios. 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.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Altexsoft

FEBRUARY 22, 2022

Predictive maintenance (PdM) involves constant monitoring of your equipment condition and conducting repairs only when bad trends are detected – but before breakdowns occur. Reporting and analytics is essential to obtain a bird eye view of your fleet and make data-based decisions. Processing data.

Software Review 52

Software Review Technical Review Software Technology 52

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

O'Reilly Media - Ideas

MARCH 6, 2019

Spotlight on Innovation: AI Trends with Roger Chen , March 13. Artificial Intelligence for Big Data , April 15-16. Data science and data tools. Practical Linux Command Line for Data Engineers and Analysts , March 13. Data Modelling with Qlik Sense , March 19-20. IoT Fundamentals , April 4-5.

Course 10

Course Artificial Inteligence Training Microservices 10

Altexsoft

OCTOBER 26, 2022

This can be anything from CRMs to AI-powered chatbots to IoT systems. Things like business knowledge, in-depth understanding of digital structures, experience in project management, and comprehensive know-how in areas such as big data, blockchain, AI, IoT, etc. Attract talent. CDO hard skills and qualifications.

CTO 52

CTO Organization Technical Review Culture 52

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. I can see two major trends in this development: Simplification. This requires a new architecture capable of true scale and speed. Lloyd Dugan BPM.com [link].

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

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

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. The term “ML” is No.

Conference 8

Conference Data Data Engineering Artificial Inteligence 8

Altexsoft

AUGUST 22, 2022

Gartner claims that there is such a solution capable of enabling companies to have advanced, flexible, and reusable data management across all environments. The solution is called a data fabric. to provide a unified view of all enterprise data. In the data fabric vs data lake dilemma, everything is simple.

Architecture 52

Architecture Artificial Inteligence Technical Review Data 52

Apiumhub

APRIL 8, 2021

With the Data Science industry continually evolving, there can be a lot to keep up with. New trends are coming up quite frequently, and if you want to do a good job and improve your skills, you must keep yourself up-to-date. He also manages the LinkedIn group Awesome Ways Big Data Is Used to Improve Our World. Kirk Borne.

Artificial Inteligence 110

Artificial Inteligence Technical Advisors Data Machine Learning 110

Altexsoft

DECEMBER 9, 2020

Diagnostic analytics identifies patterns and dependencies in available data, explaining why something happened. Predictive analytics creates probable forecasts of what will happen in the future, using machine learning techniques to operate big data volumes. Often, no technologies are involved in data analysis.

Analytics 102

Analytics Technical Review Technology Applications 102

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. Emerging trends 9.

Big Data 52

Big Data Analytics Data Analysis 52

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