Data analytics has been one of the fastest-growing fields in the last five years. The use of major tools like Excel, SQL, and Python has elevated its importance, as these tools allow analysts to accurately and professionally uncover the story behind the data.
This course is structured to provide a step-by-step guide to you, starting from the basics of each tool and gradually building up to more advanced concepts. Through hands-on exercises and real-world examples, you will learn how to manipulate data, perform statistical analyses, and create compelling visualizations and dashboards.
In this course, we will cover :
In Excel Section:
- Excel functions for data analysis.
- Excel fundamental concepts such as Sorting, Filtering, Statistical, and text functions.
- Create PivotTable slicers for interactive filtering.
- Analyze time-based data with slicers.
- Refresh and update data connections.
- Combine data from multiple sources.
- Perform data analysis on external datasets.
- Construct various chart types (bar, line, pie, etc.).
- Customize chart elements (titles, axes, data labels).
In SQL Section:
- Working with SQL Queries to retrieve data from databases for Analysis.
- Understand the concept of Sub-Queries or Inner Queries. Joining tables and combining data from multiple sources.
- SQL- DDL, DML, and DQL commands.
- Performing data manipulation.
- Learn how to apply different conditions to datasets.
- Understand the concept of Sub-Queries or Inner Queries.
- Discovering these concepts with a Case Study.
In Power BI Section:
- Understand the Power BI ecosystem
- Install and set up Power BI Desktop
- Navigate the Power BI interface
- Transforming and cleaning data
- Data modeling basics
- Creating simple visualizations (tables, charts)
- Using filters and slicers
- Creating interactive reports and dashboards
- Combining multiple data sources
- Hands-on projects and real-world applications
Who this course is for:
- This course is particularly for those people who want to learn Data related things a student, a teacher, and Corporate sector people included.
- Data curious guy who wanted to learn how to gather hidden information by using Excel, SQL, Python, and Power BI.
- Students looking for a comprehensive, engaging, and highly interactive approach to learning Data Analysis.
- A person who wants to improve the system and change the manual routine works into automatic work.
- A Doctor, Teacher, Engineer, or even anyone who belongs to any particular domain can learn about Data Engineering.