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

Pickl AI

APRIL 3, 2025

Exploratory Data Analysis (EDA): Using statistical summaries and initial visualisations (yes, visualisation plays a role within analysis!) EDA: Calculate overall churn rate. It involves handling missing values, correcting errors, removing duplicates, standardizing formats, and structuring data for analysis.

Data Analysis 52

Data Analysis Data Analysis Data Visualization EDA 52

Pickl AI

JULY 25, 2023

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. Data Visualization: Matplotlib, Seaborn, Tableau, etc. Excel, Tableau, Power BI, SQL Server, MySQL, Google Analytics, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Mlearning.ai

JULY 11, 2023

For instance, feature engineering and exploratory data analysis (EDA) often require the use of visualization libraries like Matplotlib and Seaborn. Moreover, tools like Power BI and Tableau can produce remarkable results.

Data Science 40

Data Science Exploratory Data Analysis Azure Power BI 40