A data analyst has identified the root cause of recent application slowdowns, tracing the issue to inefficient database queries and a need for index optimization. The analyst is scheduled to present these findings in two separate meetings: one with the database administration (DBA) team and another with the product management team. Which of the following approaches is most appropriate for the presentation to the product management team?
Presenting a mock-up of a new dashboard that tracks query performance metrics like CPU time and logical reads in real-time.
Providing a detailed walkthrough of the SQL queries, execution plans, and server I/O statistics that pinpoint the bottleneck.
Summarizing the findings in terms of business impact, such as the percentage of users affected and the potential effect on customer satisfaction, using simplified visuals and non-technical language.
Detailing the data validation and cleansing steps that were performed on the server logs before the analysis began.
The correct answer is to summarize the findings in terms of business impact. A non-technical audience, such as a product management team, is primarily concerned with the 'so what' of the analysis. They need to understand how the technical issue affects business goals, such as user experience and customer satisfaction. Presenting data in simplified, non-technical terms with a focus on business metrics is the most effective way to communicate with this group.
A detailed technical walkthrough of SQL queries and server statistics is appropriate for a technical audience like the DBA team, who need that information to fix the problem, but it would be overly complex and irrelevant for product managers. Presenting a mock-up of a technical dashboard is still too focused on the technical details rather than the business outcomes. While data validation is a critical part of the analysis process, it is not the key finding that the product management team needs to hear about in this context.
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How do SQL query inefficiencies impact business outcomes like customer satisfaction?
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