✅ 🔤 A–Z of Data Analyst 📊💼

A – Analytics
The process of analyzing data to discover insights and support decision-making.

B – Business Intelligence (BI)
Technologies and tools used to analyze business data (Power BI, Tableau).

C – Cleaning (Data Cleaning)
Removing errors, duplicates, and inconsistencies from data.

D – Dashboard
A visual display of key metrics and insights.

E – ETL (Extract, Transform, Load)
Process of collecting, cleaning, and storing data for analysis.

F – Forecasting
Predicting future trends using historical data.

G – Group By
A method to organize data into categories for analysis.

H – Hypothesis Testing
Testing assumptions using statistical methods.

I – Insight
Meaningful information derived from data analysis.

J – Join
Combining data from multiple tables (SQL concept).

K – KPI (Key Performance Indicator)
A measurable value showing business performance.

L – Linear Regression
A statistical method used to predict relationships between variables.

M – Metrics
Quantifiable measures used to track performance.

N – Normalization
Organizing data to reduce redundancy and improve efficiency.

O – Outlier
A data point significantly different from others.

P – Pivot Table
A tool used to summarize and analyze data quickly.

Q – Query
A request to retrieve data from a database.

R – Reporting
Presenting data insights through charts and summaries.

S – SQL
Language used to manage and analyze structured data.

T – Trend Analysis
Identifying patterns or changes over time.

U – Unstructured Data
Data without predefined format (text, images).

V – Visualization
Representing data using charts or graphs.

W – Warehousing (Data Warehouse)
Central storage of large structured datasets.

X – X-axis
Horizontal axis in charts representing variables.

Y – YoY (Year-over-Year)
Comparing data from one year to another.

Z – Z-Score
Statistical measure showing how far a value is from the mean.

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