Data Analytics

Tasks in Excel:
 

• Data Cleaning and Preparation:
• Remove duplicates, blank rows, and errors.
• Standardize formats (dates, text, numbers).
• Fill in missing values or delete incomplete records.

Data Manipulation:

• Sort and filter data to focus on specific subsets.
• Use functions (SUM, AVERAGE, COUNTIF) to perform calculations.
• Merge or split datasets based on common keys or criteria.
• Apply conditional formatting to highlight important insights.

Data Analysis:

• Calculate basic statistics (mean, median, mode, standard deviation).
• Create pivot tables to summarize and analyze data.
• Generate charts and graphs to visualize trends and patterns.
• Conduct what-if analysis using scenarios and data tables.

Data Visualization:

• Design dashboards with interactive charts and slicers.
• Customize chart styles and formats to enhance readability.
• Create dynamic reports that update automatically with new data.
• Utilize Excel's built-in templates for quick visualization solutions.

Tasks in Power BI:
 

• Data Import and Transformation:
• Connect to various data sources (Excel, databases, web).
• Transform and clean data using Power Query Editor.
• Merge multiple datasets and shape them for analysis.

Data Modeling:

• Create relationships between different data tables.
• Define calculated columns and measures for analysis.
• Build hierarchies and categories to organize data.

Data Analysis and Insights:

• Analyze data using DAX (Data Analysis Expressions) for complex calculations.
• Implement advanced analytics features like forecasting and clustering.
• Identify trends and outliers to derive actionable insights.
• Utilize Q&A functionality for natural language querying of your data.

Data Visualization:

• Design interactive reports and dashboards with drag-and-drop ease.
• Utilize a wide range of visualization types (bar charts, line charts, maps, etc.).
• Implement slicers and filters for dynamic data exploration.
• Incorporate custom visuals from the Power BI marketplace for advanced visualization options.

Tasks with MySQL:

Database Management:

• Define data types, constraints, and indexes for efficient storage and retrieval.

Data Manipulation:

• Update, insert, or delete records to modify data.
• Transform data using SQL functions (DATE_FORMAT, CONCAT, etc.).
• Perform data cleansing and validation checks.

Data Retrieval and Querying:

• Write SQL queries to extract data based on specific criteria.
• Join multiple tables to retrieve related information.
• Aggregate data using functions like SUM, AVG, COUNT, etc.

Data Analysis:

• Conduct basic statistical analysis using SQL functions.
• Group and summarize data using GROUP BY and aggregate functions.
• Filter and sort data to focus on relevant insights.
• Export query results to external tools for further analysis.