Kaggle

JULY 29, 2020

David: My technical background is in ETL, data extraction, data engineering and data analytics. An ETL process was built to take the CSV, find the corresponding text articles and load the data into a SQLite database. cord19q has the logic for ETL, building the embeddings index and running the custom BERT QA model.

ETL 71

ETL Data Scientist Data Science Machine Learning 71

Pickl AI

JULY 25, 2023

They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Exploratory Data Analysis (EDA) EDA is a crucial step where Data Scientists visually explore and analyze the data to identify patterns, trends, and potential correlations. ETL Tools: Apache NiFi, Talend, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Dataconomy

JULY 28, 2023

Exploratory data analysis (EDA) Before preprocessing data, conducting exploratory data analysis is crucial to understand the dataset’s characteristics, identify patterns, detect outliers, and validate missing values. EDA provides insights into the data distribution and informs the selection of appropriate preprocessing techniques.

Power BI 91

Power BI Data Preparation Exploratory Data Analysis Machine Learning 91

Mlearning.ai

AUGUST 10, 2023

The project I did to land my business intelligence internship — CAR BRAND SEARCH ETL PROCESS WITH PYTHON, POSTGRESQL & POWER BI 1. Section 2: Explanation of the ETL diagram for the project. ETL ARCHITECTURE DIAGRAM ETL stands for Extract, Transform, Load. ETL ensures data quality and enables analysis and reporting.

Business Intelligence 52

Business Intelligence Business Intelligence ETL Power BI 52

The MLOps Blog

MAY 31, 2023

This is the ETL (Extract, Transform, and Load) layer that combines data from multiple sources, cleans noise from the data, organizes raw data, and prepares for model training. Exploratory data analysis The purpose of having an EDA layer is to find out any obvious error or outlier in the data.

ML 59

ML ML Algorithm Machine Learning 59

AWS Machine Learning Blog

OCTOBER 11, 2024

It can be extended to incorporate additional types of operational events—from AWS or non-AWS sources—by following an event-driven architecture (EDA) approach. Solution overview The solution uses AWS Health and AWS Security Hub findings as sources of operational events to demonstrate the workflow. The chatbot handles chat sessions and context.

AWS 98

AWS AI AI Data Lakes 98