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

The chart visualizes monthly sales data for two teams over a year, divided into quarters. By analyzing the data, it is evident that November (part of Q4) had the lowest monthly sales in the year, making option C correct. There isn’t enough information to verify the performance of individual teams in each quarter as per Business Data Analytics (IIBA®- CBDA) objectives and resources. References:

•[Business Analysis Certification in Data Analytics, CBDA | IIBA®], CBDA Competencies, Domain 4: Interpret and Report Results

•[Understanding the Guide to Business Data Analytics], page 9

•[CERTIFICATION IN BUSINESS DATA ANALYTICS HANDBOOK - IIBA®], page 8, CBDA Exam Sample Questions and Self-Assessment, Question 7

A logical database model is a data model of a specific problem domain expressed independently of a particular database management product or storage technology. It describes data using notation that corresponds to a data organization used by a database management system, such as relational tables and columns. It also includes rules of normalization, which are the process of converting complex data structures into simple, stable data structures12 References: 1: Logical schema - Wikipedia 2: What Is a Data Model? | Coursera

Before investing in an enterprise analytics practice, the decision makers should have a clear understanding of the expected value and benefits of such a practice. This requires conducting an up-front analysis that identifies the business problems or opportunities that can be addressed by analytics, the data sources and technologies that are needed, the analytical models and methods that are appropriate, and the metrics and indicators that will measure the impact and outcomes of the analytics solutions12. This analysis will help to define the scope, objectives, and requirements of the enterprise analytics practice, as well as the resources, roles, and governance structures that are necessary to support it34. An up-front analysis will also help to prioritize the analytics initiatives based on their feasibility, alignment with the business strategy, and potential value creation