PRIYA KUSHWAHA
Data Analyst
Data Analyst
▪ Basic to Intermediate (Data Handling): Sorting, filtering, tables, conditional formatting, data validation
▪ Advanced (Power Query / Power Pivot / Automation): Data transformation, model building, automated refresh, DAX calculations
▪ Date & Time Functions: TODAY, NOW, DATEDIF, NETWORKDAYS, EOMONTH
▪ Text Functions: CONCAT, TEXTJOIN, LEFT, RIGHT, MID, TRIM, LEN
▪ Math & Aggregation Functions: SUM, AVERAGE, COUNTIF, SUMIFS, ROUND
▪ Logical & Conditional Functions: IF, IFS, AND, OR, IFERROR, SWITCH
▪ Lookup & Reference Functions: VLOOKUP, XLOOKUP, INDEX-MATCH, INDIRECT, OFFSET
▪ Data modeling
▪ Dax (data analysis expressions)
▪ Power query
▪ Interactive dashboards
▪ Data visualization
▪ Data transformation
▪ Kpi development
▪ Report automation
▪ Drill-down reports
▪ DDL (Data Definition Language)
▪ DML (Data Manipulation Language)
▪ DCL (Data Control Language)
▪ TCL (Transaction Control Language)
▪ DQL (Data Query Language)
1. Data Manipulation & Analysis
▪ pandas – Data cleaning, transformation, aggregation
▪ NumPy – Numerical computing, array operations
2. Data Visualization
▪ matplotlib – Basic plotting (line, bar, scatter)
▪ seaborn – Statistical data visualization (heatmaps, boxplots)
▪ Plotly – Interactive and web-based visualizations
3. Data Cleaning & Automation
4. Statistical Analysis & Modeling
5. Workflow & Reporting
Jupyter Notebook – For exploratory data analysis and visual reporting
🔹STATISTICS-
▪ Data Collection
▪ Data Cleaning
▪ Exploratory Data Analysis ( EDA )
▪ Data Transformation
▪ Hypothesis Formulation
▪ Statistical testing
▪ Draw Conclusions
▪ Document the Analysis Process/ Report Making