Unite.AI

DECEMBER 5, 2023

In this digital economy, data is paramount. Today, all sectors, from private enterprises to public entities, use big data to make critical business decisions. However, the data ecosystem faces numerous challenges regarding large data volume, variety, and velocity. Enter data warehousing!

Metadata 162

Metadata Big Data ETL Data Mining 162

Becoming Human

JANUARY 23, 2023

Nowadays most businesses use data science, whether a business is product-based or service-based they use data science for their growth. Data Science and Big Data There is an Umbrella of Big data and what is Big Data?

Data Science 105

Data Science Big Data Data Mining Deep Learning 105

Artificial Corner

JUNE 6, 2023

Timeline of data engineering — Created by the author using canva In this post, I will cover everything from the early days of data storage and relational databases to the emergence of big data, NoSQL databases, and distributed computing frameworks.

Data Mining 52

Data Mining Big Data ETL Machine Learning 52

Marktechpost

JULY 17, 2023

Predictive analytics uses methods from data mining, statistics, machine learning, mathematical modeling, and artificial intelligence to make future predictions about unknowable events. It creates forecasts using historical data. Predictive analytics is a standard tool that we utilize without much thought.

Machine Learning 98

Machine Learning Data Mining Data Scientist Data Science 98

Pickl AI

JANUARY 15, 2025

As businesses increasingly rely on data-driven strategies, the global BI market is projected to reach US$36.35 The rise of big data, along with advancements in technology, has led to a surge in the adoption of BI tools across various sectors.

Business Intelligence 52

Business Intelligence ETL Data Mining Data Analysis 52

ODSC - Open Data Science

APRIL 3, 2023

Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis. Competence in data quality, databases, and ETL (Extract, Transform, Load) are essential.

Data Science 52

Data Science Big Data ETL Deep Learning 52

Pickl AI

JUNE 11, 2024

Let’s delve into the key components that form the backbone of a data warehouse: Source Systems These are the operational databases, CRM systems, and other applications that generate the raw data feeding the data warehouse. Data Extraction, Transformation, and Loading (ETL) This is the workhorse of architecture.

ETL 52

ETL Data Mining Data Integration Actionable Intelligence 52