Vasantkumar Burud

Data Preparation: You'll often start by importing raw data into Excel from various sources such as databases, spreadsheets, or CSV files. This may involve cleaning and organizing the data to make it suitable for analysis.

Data Manipulation: Excel provides a wide range of functions and tools for manipulating data. You'll use formulas, pivot tables, filters, and other features to aggregate, sort, filter, and transform data according to your analysis requirements.

Data Analysis: Excel allows you to perform various types of analysis, including descriptive statistics, trend analysis, regression analysis, and more. You'll use functions and tools like charts, graphs, and statistical functions to gain insights into the data and identify patterns, trends, and relationships.

Reporting: Excel is commonly used for creating reports and visualizations to communicate your findings effectively. You'll design and format reports, dashboards, and charts to present your analysis results in a clear and understandable manner to stakeholders.

Automation: Excel offers features like macros and VBA (Visual Basic for Applications) for automating repetitive tasks and enhancing productivity. You may write scripts or use built-in automation features to streamline data analysis processes and workflows.

Quality Assurance: As a data analyst, ensuring the accuracy and reliability of your analysis is crucial. You'll perform data validation, error checking, and quality assurance procedures to detect and correct any inaccuracies or inconsistencies in the data and analysis results.

Collaboration: Excel facilitates collaboration by allowing you to share workbooks, collaborate in real-time, and track changes made by multiple users. You may work with other team members or stakeholders to gather requirements, share insights, and iterate on analysis.

Continuous Learning: Excel is a versatile tool with a wide range of features and capabilities. As a data analyst, you'll continuously learn and explore new Excel functions, techniques, and best practices to improve your skills and stay updated with the latest trends in data analysis.

Detail-Oriented data analyst with a strong background in statistical analysis, data visualization and data driven decision making, proficient in using tools like Excel and Power BI and data visualization software to extract actionable insights from complex datasets.

Warehousing: Inventory accuracy, cycle counts, storage conditions, security, picking and packing procedures.
Transportation: Routing optimization, carrier selection, freight agreements, fuel efficiency, delivery performance.
Inventory management: Forecasting, demand planning, safety stock levels, stock turnover, obsolete inventory.

Updating employee leave/time card(Manually)
Taking responsible for preparing long absenteeism list and confirm with shop in charge
Preparing discharge letter for long absenteeism
solving salary related issues
Recruitment of trainee and operators