BUSINESS DATA ANALYTICS //KASNEB //AUGUST SITTING 2024

The BUSINESS DATA ANALYTICS exam offered by KASNEB (Kenya Accountants and Secretaries National Examination Board) for the August sitting of 2024 is likely to cover a range of topics related to data analysis in a business context. Here's a brief description of what you might expect:

Data Analysis Fundamentals: This section may cover the basics of data analysis, including understanding data types, data cleaning, data transformation, and data visualization techniques.

Statistical Analysis: Expect questions on statistical methods commonly used in business analytics, such as descriptive statistics, probability theory, hypothesis testing, regression analysis, and time series analysis.

Predictive Analytics: This part might delve into predictive modeling techniques used to forecast future trends and outcomes based on historical data. Topics could include regression analysis, decision trees, and machine learning algorithms.

Data Mining and Machine Learning: Questions in this area might focus on extracting insights and patterns from large datasets using advanced techniques like clustering, classification, and association rule mining.

Data Visualization: Expect questions on effective data visualization methods for communicating insights and findings to stakeholders, including the use of charts, graphs, and dashboards.

Ethical and Legal Considerations: There may be questions related to the ethical and legal aspects of data analysis, including privacy concerns, data security, and compliance with regulations such as GDPR.

Business Applications: You might encounter questions that apply data analysis techniques to real-world business problems, such as marketing analytics, financial forecasting, supply chain optimization, and customer segmentation.

Overall, the exam is likely designed to assess your ability to apply data analysis techniques to solve business problems, interpret and communicate analytical findings, and demonstrate an understanding of the ethical and legal implications of working with data. It may include a mix of multiple-choice, short-answer, and practical questions to evaluate your knowledge and skills comprehensively.



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