Analytics Vidhya

FEBRUARY 4, 2023

Introduction This article will explain the difference between ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) when data transformation occurs. In ETL, data is extracted from multiple locations to meet the requirements of the target data file and then placed into the file.

ETL 298

ETL Explainability Data Integration Data Analysis 298

Pickl AI

OCTOBER 17, 2024

Summary: The ETL process, which consists of data extraction, transformation, and loading, is vital for effective data management. Following best practices and using suitable tools enhances data integrity and quality, supporting informed decision-making. What is ETL? ETL stands for Extract, Transform, Load.

ETL 52

ETL Explainability Data Integration Data Extraction 52

Marktechpost

MARCH 22, 2024

Users can take advantage of DATALORE’s data governance, data integration, and machine learning services, among others, on cloud computing platforms like Amazon Web Services, Microsoft Azure, and Google Cloud. This improves DATALORE’s efficiency by avoiding the costly investigation of search spaces.

Machine Learning 136

Machine Learning Explainability Categorization ETL 136

IBM Journey to AI blog

AUGUST 4, 2023

Then, it applies these insights to automate and orchestrate the data lifecycle. Instead of handling extract, transform and load (ETL) operations within a data lake, a data mesh defines the data as a product in multiple repositories, each given its own domain for managing its data pipeline.

Machine Learning 183

Machine Learning Metadata Automation AI 183

ODSC - Open Data Science

JUNE 19, 2023

With the advent of big data in the modern world, RTOS is becoming increasingly important. As software expert Tim Mangan explains, a purpose-built real-time OS is more suitable for apps that involve tons of data processing. The Big Data and RTOS connection IoT and embedded devices are among the biggest sources of big data.

Big Data 96

Big Data ETL Data Science Artificial Intelligence 96

AWS Machine Learning Blog

AUGUST 2, 2024

In this post, we explain how Cepsa Química and partner Keepler have implemented a generative AI assistant to increase the efficiency of the product stewardship team when answering compliance queries related to the chemical products they market. The following diagram illustrates this architecture.

Generative AI 121

Generative AI LLM Machine Learning Data Scientist 121

Pickl AI

DECEMBER 10, 2024

Summary : Data Analytics trends like generative AI, edge computing, and Explainable AI redefine insights and decision-making. Businesses harness these innovations for real-time analytics, operational efficiency, and data democratisation, ensuring competitiveness in 2025.

Explainable AI 52

Explainable AI Explainability ETL Automation 52