PROGRAM SCHEDULE

Ref No: FI 144 Program Name: Business Intelligence & Analytics for Finance Professionals

Starts Ends Venue Fees Join Now
21 Jul 2025 25 Jul 2025 Dubai, UAE $ 4,750Registration Closed
29 Sep 2025 03 Oct 2025 Istanbul, TR $ 5,750Registration Closed
08 Dec 2025 12 Dec 2025 Houston, US $ 6,750
02 Feb 2026 06 Feb 2026 London, UK $ 5,750
20 Jul 2026 24 Jul 2026 Dubai, UAE $ 4,750
28 Sep 2026 02 Oct 2026 Istanbul, TR $ 5,750
07 Dec 2026 11 Dec 2026 Houston, US $ 6,750

PROGRAM DETAILS



Introduction

The training program will cover a wide range of topics, including risk identification, risk analysis, risk mitigation, risk monitoring, and risk reporting. Participants will also learn about the latest regulatory requirements related to risk management and how to ensure compliance. By the end of the training program, participants will be equipped with the knowledge and skills required to implement advanced risk management practices within their organizations, helping to safeguard their organizations from a wide range of risks.

The Business Intelligence & Analytics for Finance Professionals training program is designed to equip finance professionals with the necessary skills and knowledge to leverage business intelligence and analytics tools for data-driven decision-making. The program will cover topics such as data analysis, data visualization, and data management. Through a combination of lectures, hands-on exercises, and case studies, participants will develop the skills and knowledge needed to become effective data analysts.

Learning Objectives:

  • Understand the role of business intelligence and analytics in finance
  • Learn how to analyze and interpret financial data
  • Develop skills for data visualization and presentation
  • Gain knowledge of data management and governance
  • Learn how to use business intelligence and analytics tools for data-driven decision-making

Training Methodology:

The training program will be conducted through a combination of lectures, hands-on exercises, and case studies. Participants will use business intelligence and analytics tools to analyze financial data, visualize data, and prepare reports. The program will also include group discussions and problem-solving exercises to encourage active participation and engagement.

Target Audience: 

This training program is designed for finance professionals who are interested in using business intelligence and analytics tools for data-driven decision-making. It is suitable for financial analysts, finance managers, accountants, and other professionals who are responsible for financial analysis and reporting. 

Program Contents:

Day 1: Introduction to Business Intelligence and Analytics

  • Overview of the program objectives and agenda
  • Introduction to business intelligence and analytics
  • Role of business intelligence and analytics in finance
  • Key concepts and principles of data analysis
  • Case study: Using business intelligence and analytics to optimize financial performance

Day 2: Data Analysis Techniques

  • Techniques for data analysis and interpretation
  • Analyzing financial statements using business intelligence and analytics tools
  • Data modeling and forecasting techniques
  • Case study: Analyzing financial data to improve cash flow management

Day 3: Data Visualization and Presentation

  • Principles of data visualization and presentation
  • Techniques for creating effective data visualizations
  • Creating dashboards for financial reporting and analysis
  • Case study: Creating data visualizations to monitor key financial metrics

Day 4: Data Management and Governance

  • Principles of data management and governance
  • Best practices for data quality and integrity
  • Understanding data privacy and security regulations
  • Case study: Managing data for effective financial analysis and reporting

Day 5: Business Intelligence and Analytics for Data-Driven Decision-Making

  • Using business intelligence and analytics tools for data-driven decision-making
  • Incorporating data analysis into financial planning and forecasting
  • Developing recommendations based on data analysis
  • Case study: Making data-driven decisions to optimize financial performance

 

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