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Go to Course: https://www.udemy.com/course/professional-course-for-data-analysis-using-excel/
I recently explored the course "Advanced Excel for Data Analysis: Techniques and Application" available on Coursera, and I highly recommend it for anyone interested in enhancing their data analysis skills, regardless of their prior experience with Excel. This course is designed to be accessible to beginners, with no previous background in data analysis required. It offers a comprehensive overview of advanced Excel techniques tailored specifically for data analysis tasks. Throughout the course, you will learn a wide array of powerful features and tools that are essential for analyzing and visualizing data effectively. Key Highlights: - Power Query Editor: Master data cleaning and transformation techniques such as removing or merging columns and rows, splitting columns, creating conditional and custom columns, and combining queries. It also covers data types, statistics, data rounding, and grouping. - Pivot Tables: Learn how to create and manipulate pivot tables for quick data summarization and analysis. - Data Relationships: Understand how to establish relationships between tables using primary and foreign keys, an essential skill for relational database analysis. - DAX (Data Analysis Expressions): Develop the ability to create measures and calculated columns to identify key performance indicators (KPIs) using functions like Calculate, SUM, SUMX, AVERAGEX, and Divide. - Calendar Table: Create calendar tables to analyze data across various date ranges, including days, months, quarters, and years, enabling deep temporal analysis. - Advanced Data Analysis: Perform detailed data breakdowns by specific days, months, and quarters, and compare data across different time periods. - Visualizations and Dashboards: Build professional dashboards using diverse pivot charts including pie charts, column charts, line charts, area charts, and pareto charts, to visualize insights clearly and effectively. Why I Recommend It: This course offers a blend of theoretical knowledge and practical application, making it suitable for beginners and experienced analysts alike. Its hands-on approach ensures that you can directly apply what you learn to real-world data sets. Whether you are looking to improve your data analysis capabilities for your job or personal projects, this course provides valuable skills that can significantly boost your productivity and analytical thinking. In summary, "Advanced Excel for Data Analysis" on Coursera is an excellent investment for anyone wanting to become proficient in modern data analysis techniques using Excel. Its detailed content, combined with practical exercises, makes it a standout course for expanding your data skills. Happy learning!
This Course for any one want to learn data analysis field there is no need to any background for this course ,, in this course you will learn in details many things 1-Power Query Editor in Excel To Clean and Transform Data(Remove Columns , Remove Rows , Merge Columns , Split Columns , Conditional Columns , Custom Columns ,Append Queries , Merge Queries, Select Data From Folder, Data Types ,Statistics , Standard, Rounding, Group by)2-Pivot Table3-Relationships between tables using Primary Key and Foreign Key ( Explain Primary Key and Foreign Key Concept )4-Create Measures and Columns using DAX(Data Analysis Expression) to Know KPI'S in Data(Using Calculate Function , SUM Function , SUMX Function , AVERAGEX Function , Divide Function)5-Create Calendar Table to Analyze Data Based in Many Different Dates (Day , Month , Year , Quarter)Analyzing Data by Using Day of Month or Day of Year or Day of Quarter ,, Analyzing Data by Using Month of Specific Year or Month of Specific Quarter ,, Analyzing Data By Specific Quarter or For All Quarters of all Year ,, Analyzing Data for Specific Year or all Years of Data 6-Analysisng Data Using Pivot Table Using Rows , Columns Filter , Value on Pivot Table7-Making Professional Dashboard By using Different Pivot ChartsUsing Par Chart , Pie Chart , Column Chart , Line Chart , Area Chart