In the era of technological development and various prevalent means of storing and exchanging information; That is, the transmission of information on networks and from one site to another, it has become important to consider and monitor information and data security. Information security is the science applied to provide significant and adequate protection of information against any risks that may threaten or damage it through the necessary tools and means to protect information from internal or external risks. All standards and measures taken to prevent access to information by persons who are not permitted to access it through communications are used to ensure the correctness and authenticity of such communications.

Who should attend? 

• Managers and business owners.
• Managers of administrative departments in companies.
• Managers of information systems centers in companies.
• Managers of information security and authentication departments in companies.
• Developers of computer security systems in the company.

How attendees will benefit? 

After completion of the course, delegates will be able to: 

• Enhance Business Intelligence (BI) expertise in slicing, segmenting, masking and modeling data.
• Processing, integrating and using data in preparing reports and analysis processes.
• Developing business intelligence models, control panels, score cards, and managing reports by linking Excel with text programs or other Excel files.
• Create advanced reports based on dynamic display methods and techniques.

• Introduction to data analysis and business management:
  • The concept of data analysis and its importance in business management processes.
  • Data types and sources in a business context.
  • The role of data analysis in making strategic decisions.
• Basics of data analysis:
  • Explore data, clean it, and convert it into analyzable formats.
  • Apply summarization and graphical visualization techniques to understand data.
• Advanced data analysis techniques:
  • Regression analysis and forecasting of data.
  • Classification and grouping techniques in data analysis.
  • Using machine learning and artificial intelligence techniques to analyze data.
• Big Data analysis:
  • Analyze and process big data using special tools and techniques.
  • Using cloud computing technologies to manage and analyze big data.
• Applications of data analysis in business administration:
  • Using data analysis to analyze the market and understand customer needs.
  • Use data analysis to improve production and supply processes.
  • Analyze data to improve financial performance and guide growth strategies.
• Data security and privacy:
  • Principles of data security and privacy protection.
  • Challenges and risks related to data security and how to deal with them.
• Case studies and practical applications:
  • Analyze practical case studies of data analysis applications in various industries.
  • Apply the tools and techniques taught during the course to a range of real problems in business administration.
• Communication and reporting skills:
  • How to effectively present results and reports to better understand data and make strategic decisions.