What does filtering missing data in Tableau help to achieve?

Filtering missing data in Tableau primarily helps to achieve better data visualization clarity. When missing data is removed, the visualizations become more straightforward and easier to interpret. This ensures that the audience focuses on the relevant and complete information, leading to more accurate insights and decisions based on the visualizations.

Clarity in data visualization is essential for effectively communicating insights. By filtering out incomplete records, visual representations, such as charts and graphs, are less cluttered and highlight only the data that can be analyzed meaningfully. This approach allows viewers to grasp key trends and patterns without being distracted by gaps or inconsistencies in the dataset.

In contrast, while other options touch on different aspects of data handling and presentation, they do not directly relate to the benefits gained from filtering out missing data. Increased data security refers to protecting sensitive information, which is unrelated to handling missing data. More complex data relationships may arise from various analytical techniques but aren't achieved through the filtering process itself. Enhanced data connection integrity is concerned with the reliability of data sources rather than the clarity of visualizations. Thus, filtering missing data fundamentally improves the audience's understanding and interpretation of the provided visual insights.