Altexsoft

AUGUST 25, 2020

Big data can be quite a confusing concept to grasp. What to consider big data and what is not so big data? Big data is still data, of course. Big data is tons of mixed, unstructured information that keeps piling up at high speed. Data engineering vs big data engineering.

Big Data 75

Big Data Data Engineering Engineering Data 75

Xicom

FEBRUARY 21, 2020

It includes three essential questions when you want an app for your business: What technology do you want to use for app development? So you need to make sure that you find an application developer with the capabilities to choose the right technology that perfectly fits your needs and budget. 20,000 to $25,000.

Software Development 76

Software Development Software Review Weak Development Team Software 76

Existek

JANUARY 11, 2022

Game tech – Epic Games, PlayStation. For example, they considerably revised the cloud strategy due to the need to transform the delivery model from PaaS to IaaS, thus renaming Windows Azure to Microsoft Azure in 2014. . For example, Amazon started to divide separate data units for goods, orders, and customers. Game tech

Azure 52

Azure AWS Cloud How To 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. Big data processing.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

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

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

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

JUNE 20, 2019

In relational DBMS, the data appears as tables of rows and columns with a strict structure and clear dependencies. Due to the integrated structure and data storage system, SQL databases don’t require much engineering effort to make them well-protected. For example, when building a local eCommerce store, MySQL may come in handy.

Systems Review 85

Systems Review System Software Review Open Source 85

Altexsoft

JANUARY 11, 2019

A data science pipeline is a set of processes for automating data collection, preparation, visualization, modeling, and interpretation (review) to answer business questions or get informed conclusions. That means that data scientists should be more of programmers,” concludes the data scientist.

Artificial Inteligence 94

Artificial Inteligence Artificial Intelligence Trends Data 94

Altexsoft

OCTOBER 2, 2020

Key disciplines and roles in data management. Data architecture: aligning technologies with business goals. Specialist responsible for the area: data architect. Data architecture is a starting point for any data management model. Database administration: maintaining data availability.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Altexsoft

OCTOBER 17, 2019

For now, we need to find out what specialists would define metrics and standards to get data so good that it deserves a spot in perfectionist heaven, who would assess data, train other employees best practices, or who will be in charge of the strategy’s technical side. . Data quality team: roles and responsibilities.

Tools 16

Tools Data Technical Advisors Technical Review 16

Altexsoft

MARCH 14, 2023

This development has paved the way for a suite of cloud-native data tools that are user-friendly, scalable, and affordable. Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. Data democratization.

Data 59

Data Technical Review Software Review Artificial Inteligence 59