CBDA Exam Dumps : Certification in Business Data Analytics (IIBA - CBDA)

The quality of the data is the most important dimension to consider when identifying research questions, as it affects the validity, reliability, and accuracy of the analysis and the results. Data quality refers to the degree to which the data meets the requirements and expectations of the stakeholders and the purpose of the analysis12. Poor data quality can lead to erroneous conclusions, ineffective decisions, and wasted resources3. References: 1: Guide to Business Data Analytics, IIBA, 2020, p. 282: Data Quality Assessment, Arkady Maydanchik, 2007, p. 33: Data Quality: The Field Guide, Thomas C. Redman, 2001, p. 1.

Unsupervised learning is a type of study that involves finding patterns or clusters in data without any predefined labels or outcomes. It is useful for exploring data and discovering hidden structures or groups of customers. For example, the professional association can use unsupervised learning to identify the characteristics of customers who are likely to cancel their subscription after their first 5-year term ends, and then design strategies to retain them12 References: 1: What is Unsupervised Learning? - IBM 2: Unsupervised Learning - IIBA BABOK Guide v3

Ensuring the result set is statistically significant is important to the team because it means that the difference or relationship observed in the data is unlikely to be due to chance or sampling error. Statistical significance helps the team to assess the validity and reliability of their findings, and to draw meaningful conclusions and recommendations from the data. Statistical significance also helps the team to communicate their results with confidence and credibility to the stakeholders and decision makers12 References: 1: An Easy Introduction to Statistical Significance (With Examples) - Scribbr 2: Statistical Significance in Experimentation and Data Analysis - All About Circuits