Non-aggregated

Describing data, information, or items that have not been combined, grouped, or summarized into a single, unified whole. It refers to individual pieces of information remaining separate and distinct, maintaining their original form and granularity. This contrasts with aggregated data, which has been processed to provide broader summaries and trends. non-aggregated data allows for more detailed analysis and exploration of specific instances, relationships, and raw details, offering flexibility in how the data is interpreted and utilized. It emphasizes individual data points over summary-level statistics. This raw state often holds the most accurate insights.

Non-aggregated meaning with examples

• The marketing team decided to analyze the customer data in its non-aggregated form. Instead of looking at overall sales figures, they examined individual customer purchase histories. This allowed them to identify specific product preferences and tailor personalized advertising campaigns, maximizing the impact of their efforts and improving customer engagement based on granular insights.
• Researchers studying social media trends need to access the data in a non-aggregated manner. They would want to look at individual user posts and interactions rather than summarized statistics to identify specific language patterns and understand how public opinions shift. Analyzing such discrete data provides a deeper comprehension of specific behaviors and actions.
• Before constructing the report, the financial analyst requested access to the non-aggregated transaction data. This granular level of detail allowed for in-depth fraud detection, examining individual transactions for suspicious activities. By scrutinizing each entry, the analyst could uncover subtle irregularities which would be hidden by aggregated numbers and averages.
• The software's design included a feature allowing users to download the system logs in their non-aggregated state. Each individual event was available for the user to assess. This level of data access empowered the user with the ability to perform complex custom analyses and troubleshoot potential issues, ensuring system integrity and efficiency.