Data Analysis Using Excel & Power BI

Training Hours: 36
Sessions: 12

Data helps in making informed decisions, allowing organizations to measure, monitor, and evaluate performance across all aspects and take corrective actions. Accordingly, data analysis can be considered the main tool for business excellence and acceleration.

What is the goal of studying data analysis using Excel and Power BI?

This course is the perfect practical way to enhance your data analysis skills. It combines the concept of data visualization with the technical skills to build a career in one of the most important fields worldwide. Most global and innovative companies use data analysis to help make data-driven decisions using business intelligence solutions. The AI-based data analysis course will equip you with the latest techniques to extract valuable insights from your data, suitable for making business decisions. This diploma prepares trainees for the following careers: Data Analyst, Business Intelligence Specialist, Performance and Reporting Analyst, Data Visualization Specialist, Marketing Analyst, Reporting Specialist, and Program Analyst.

 

What are the benefits of studying the principles of data analysis using Excel and Power BI at Asas?

  • Practical study: Hands-on training with a variety of data analysis and business intelligence tools, making it an ideal choice for anyone looking to leverage the latest technologies in data analysis efforts.
  • Intensive study: The program is delivered over one and a half months, with 3 lectures per week, each lecture lasting 3 hours.
  • Certificates: A certificate of expertise from Asas for Training and Human Resources Development.
  • Trainers: Experts and specialists provide technical advice and guidance to help deepen the understanding of how to use Excel to obtain accurate data and then analyze it using Power BI.

Program Modules

Excel

  • Professional use of Pivot Tables.
  • Using Power Query Editor to import data or connect to it for large datasets that cannot be imported into Excel, then processing, cleaning, and preparing it for analysis.
  • Using Power Pivot to create relationships between different tables to make data interrelated.

Power BI

  • What is Power BI?
  • Introduction to the program interface.
  • Importing, processing, cleaning, and formatting data using Power Query Editor.
  • Managing relationships between tables, linking them, and creating calculated measures and fields using Power Pivot.
  • Analyzing data using various chart types and understanding their properties and formatting (tables, line chart, pie chart, donut chart, column chart, bar chart, maps chart, KPI visualization, gauge chart, card visualizations, matrix).
  • Data filtering options.
  • Explanation of the Tool Tips feature.
  • Explanation of conditional formatting.
  • Designing interactive reports and dashboards and storytelling with data.
  • Implementing a comprehensive project.

This course is designed for:

  • Professionals seeking to build a career in one of the most in-demand fields.
  • Professionals who want to understand the benefits and uses of data analysis and techniques applied using Excel and Power BI and the latest innovative AI-driven techniques when analyzing business data, to enhance their analytical skills and data understanding.
  • Professionals seeking to enhance their analytical capabilities and pursue a career related to data visualization/development.
  • Data analysts looking to expand their skills and learn how to use AI-driven technologies to extract insights from data.
  • Business professionals, business analysts, data analysts, financial specialists, marketing and sales professionals, HR specialists, IT professionals, administrative staff, supervisors, general business
  • professionals, and employees from any role who need to learn and apply data analysis techniques to their daily business reports and decision-making.

Program Requirements

  • Laptop Requirements: Use a laptop and ensure Office 2019 and Office 365 are installed.
  • Technical Requirements: No prior knowledge of data, statistics, or Power BI is required.
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