✅ 🔤 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.
Double Tap ♥️ For More
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.
Double Tap ♥️ For More