Exam DP-600 topic 1 question 101 discussion

Descriptive analytics tells what happened in the past, presenting it as numbers and visuals in reports and dashboards. Diagnostic analytics gives the reason why something happened. Predictive analytics determines the potential outcomes of present and past actions and trends. Prescriptive analytics offers decision support for the best course of action. Given the scenario in the question where data is read into a Spark DataFrame and column charts are created to show the distribution of retained customers compared to lost customers based on various factors, this falls under the definition of descriptive analytics. No future predictions or prescriptions are made, nor are reasons for the past events provided. Final Answer: The type of analytics being performed in the scenario described is descriptive analytics. https://www.selecthub.com/business-intelligence/predictive-descriptive-prescriptive-analytics/

comparison = descriptive analytics

Compare retained customers vs. lost customers based on geography, the number of products purchased, age, and customer tenure cannot tell us why customer churn. Factors like time spent on customer service, customer satisfaction rate will be more ... will be more effective.

The analysis focuses on displaying data distributions, which aligns with descriptive analytics. To classify the work as diagnostic analytics, you would need to perform further analysis to find and explain the root causes of why customers are retained or lost (e.g., identifying specific correlations or using statistical tests to validate contributing factors).

The analysis is primarily descriptive because it summarizes and visualizes the distribution of retained versus lost customers based on various factors. However, it can also be considered diagnostic if you use these visualizations to identify patterns and investigate the reasons behind customer churn, such as higher churn rates in specific age groups or regions. Thus, it serves both to describe the data and to diagnose underlying issues. I believe in the exam; it is possible to dispute questions with answers that contain two possible solutions, so don't worry too much about this question.

https://azure.microsoft.com/es-es/blog/answering-whats-happening-whys-happening-and-what-will-happen-with-iot-analytics/ contains text "Examine data from multiple angles to understand why something is happening." for Diagnostic. In this case we are looking at data from multiple angles.

For me this is a diagnostic analysis, since we try to evaluate the root cause of churn (i.e. loosing customers).

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The creation of column charts to show the distribution of retained and lost customers based on various attributes is aimed at summarizing and visualizing historical data, which aligns with the principles of descriptive analytics. This is not enough to determine why something happened. It involves analyzing data to identify causes and correlations (Diagnostic Analytics).

sounds like B - descriptive analytics to me. comparing one metric against another by different categories. I cannot see that we are saying "why" did something happen, which means it would not be A

the terms as compared in the phrase tell use it is a descriptive comparaison : show the distribution. of retained customers as compared to lost customers based on geography,

I think that this chart tries to show why people are leaving, so I would go with A diagnostic

B. descriptive

Descriptive - it's just describing the customers, not saying why they stayed or left

A, diagnostic - why did it happen

A. diagnostic