Final answer:
Data analytics applied to employee data can conclude employees' performance and trends by examining productivity, attendance, and performance appraisals. Other conclusions like customer purchasing patterns and market share trends are drawn from different datasets not related to employee data.
Step-by-step explanation:
When applying data analytics to employee data, the conclusion can be drawn about employees' performance and trends. This is because employee data encompasses a range of information directly related to the workforce, such as productivity metrics, attendance records, and performance appraisals. By analyzing this data, patterns can be identified that help in understanding employee behavior, identifying areas for improvement, and predicting future trends within the workforce.
In contexts like marketing analysis, customer data is used to ascertain facts like who purchases which products (customer preferences), customer satisfaction levels, and market share trends. However, these outcomes are not directly related to employee data analytics. Different datasets serve different purposes and thus, lead to varied conclusions based on the nature of the data collected and analyzed.
That being said, by analyzing employee data with proper statistical tools, a business can significantly enhance its internal operations and better manage its human resources, leading to potential indirect impacts on customer satisfaction and market share through improved employee performance.