📊 Exploratory Data Analysis (EDA) EDA = Understanding your data before modeling it.

Exploratory Data Analysis (EDA) is the crucial first step in any data analysis or machine learning workflow. It involves summarizing, visualizing, and understanding the structure and relationships in your data before moving to modeling or deeper analysis.

🚀 Steps Involved in EDA 1️⃣ Database Exploration Understand the structure of the database

Identify tables, relationships, keys, and constraints

2️⃣ Dimensions Exploration Analyze categorical fields

Understand unique values, frequency distribution, and cardinality

3️⃣ Date Exploration Explore date/time columns

Analyze trends, seasonality, and time-based patterns

4️⃣ Measures Exploration Explore numeric fields

Analyze distributions, outliers, and statistical summaries

5️⃣ Magnitude Analysis Understand the scale and magnitude of measures

Identify high/low values, percentiles, and variability

6️⃣ Ranking Analysis Rank data based on key measures

Identify top-N and bottom-N entities (e.g., top customers, highest sales)

🛠️ Tools Used SQL → Data extraction and manipulation