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An insurance company has seen an upward trend in winter-related accidents over the past three years. The company has just completed an analytics study to better understand the primary reasons for these accidents and assess how many of the drivers were using winter tires. This analysis will help the company decide how to move forward with drivers not taking precautionary measures during winter. What type of analysis will help in determining the primary reasons and percentage of those drivers with winter tires?
Descriptive analytics is a type of analytics that summarizes and visualizes the data to provide an overview of what has happened or is happening, such as the trend of winter-related accidents over the past three years, or the percentage of drivers using winter tires12. Diagnostic analytics is a type of analytics that explores and analyzes the data to understand why something has happened or is happening, such as the primary reasons for these accidents, or the factors that influence the drivers' decisions13. To answer the question, both descriptive and diagnostic analytics would be needed to provide the relevant information and insights for the company. Reference: 1: Guide to Business Data Analytics, IIBA, 2020, p. 182: Business Analytics: Data Analysis & Decision Making, S. Christian Albright and Wayne L. Winston, 2015, p. 53: Data Science for Business, Foster Provost and Tom Fawcett, 2013, p. 13.
To support their recommendation, the analytics team has identified investment and resources required to implement. The team has also identified key activities and events that are required to transition the organization through various stages to the future state. This information is clearly articulated in the:
A food and beverage company would like to administer a survey to obtain customer insights about a new cookie product recently launched. A data team is asked to build the survey paying careful attention to reduce the degree of sampling error. Which criteria would help the team meet this objective?
While sourcing data, an analyst runs into a situation where different business units are using different names to refer to the same data element. This lack of standardization is resulting in confusion and additional time required to properly prepare data for analysis. Which practice, if implemented would address this situation and mature the organization's business analytics practice?
Meta data management is the practice that, if implemented, would address the situation and mature the organization's business analytics practice, because it is a technique that involves defining, documenting, and maintaining the information about the data elements, such as their names, definitions, formats, sources, and relationships. Meta data management can help the analyst resolve the inconsistencies and ambiguities in the data element names, and ensure that the data is standardized, consistent, and understandable across different business units. Meta data management can also help the analyst improve the data quality, accessibility, and usability for the analysis. Reference:
* Business Analysis Certification in Data Analytics, CBDA | IIBA, CBDA Competencies, Domain 2: Source Data
* Guide to Business Data Analytics - Iiba - Google Books, page 14
* Business Data Analytics (IIBA-CBDA Exam preparation) | Udemy, Section 2: Source Data, Lecture 8: Meta Data Management
A grocery store chain has requested help in determining how customer preferences are changing with regards to home delivery. An analytics team has completed researching the number of online orders received requesting home delivery versus in-store pickup. The business analyst has selected a model to enable a quick comparison between curbside pick-up, in-store pickup, and home delivery for the last 3 years. Which model has the business analyst chosen?
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