Openxcell

MARCH 30, 2023

From human genome mapping to Big Data Analytics, Artificial Intelligence (AI),Machine Learning, Blockchain, Mobile digital Platforms (Digital Streets, towns and villages),Social Networks and Business, Virtual reality and so much more. We are using them for something as basic as everyday chores to something as big as running a company!

Artificial Inteligence 98

Artificial Inteligence Machine Learning IoT Internet 98

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

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

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

Capgemini

MAY 20, 2020

Retailers have long been hampered by their data infrastructures, first by structural limitations inherent in data warehouses and then the expense and lack of agility of newer big-data systems. M ost spend more than 70% of the data and analytics budget o n data warehousing, data lake s, management, and storage.

Infrastructure 64

Infrastructure Data Retail Analytics 64

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. Who needs a data lake?

Architecture 52

Architecture Data Storage Machine Learning 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