Data Stories

Question and objective

How can an analysis result remain understandable to others when the next shift or another team takes over? A data story connects the observation with context and a specific next step.

Implementation in Bytefabrik

Data Stories are a Bytefabrik feature. They are composed of content building blocks, including Situation, Text, Question, Image, Chart, PDF, and Solution. This allows for the technical documentation of findings. The Manufacturing Analytics Copilot can also prepare Data Stories for prioritized anomalies; this feature is part of the Manufacturing Insights context.

Best Practices for a Medical Report

1. Situation: Describe the facility, time period, and occasion.
2. Observation: Show a key figure or pattern with supporting documentation.
3. Classification: Record explanations and open questions separately from verified data.
4. Next step: Identify the person in charge and the planned audit.
5. Result: After implementing the measure, document what has changed and under what conditions.

Example: A recurring outage is documented along with the affected time period and a chart. The maintenance team adds its findings, and the team records the comparison after the corrective action is taken.

What You Should Keep in Mind

A screenshot without a filter or time range is difficult to verify later. Therefore, be sure to include the source and the scope of the screenshot in the text as well. For embedded content, check whether it will be updated in the future or whether it captures the state at the time.

AI-generated explanations should be reviewed based on their supporting evidence. The benefit is a clear handover and a reduction in the need to recreate the same analysis, not a collection of charts that is as long as possible.