Key Drivers and Explainability
Private Beta Feature
Interested in trying this feature? The functionality detailed in this article is in private beta testing. To request exclusive access, please sign up for the waitlist.
While visual analytics like charts and graphs provide an immediate, visual understanding of data trends and patterns, they can sometimes lack the specificity and context needed for thorough comprehension. Additionally, stakeholders, especially those without a background in data analytics, might find it challenging to interpret raw data or visualizations accurately, leading to potential misunderstandings or missed opportunities.
GoodData introduces a way to generate an analysis of the key drivers behind a set of data, and an explenation to go with it, as a bridge between raw data and actionable insights. The key driver analysis employ advanced algorithms to convert intricate data patterns into comprehensible narratives. These auto-generated textual descriptions not only break down complex data visualizations but also provide nuanced context, ensuring that insights are accessible, relatable, and actionable for a broader audience.
Key driver analysis interprets charts and graphs to provide contextual explanations. Whether it’s a sudden spike in sales or an unexpected dip in user engagement, key driver analysis provides a coherent story that underpins the visualization.
Customize the depth and detail of the generated narratives. Whether you want a concise summary or an in-depth analysis, key driver analysis adjusts its outputs based on user preferences.
Seamless Integration with Visual Analytics:
Key driver analysis is seamlessly integrated within GoodData’s analytics environment. With a single click, convert any chart or graph into a structured narrative, ensuring that your insights are both visually appealing and textually comprehensive.
As your data evolves, so do the narratives. Key driver analysis ensures that the generated descriptions remain in sync with the underlying data, providing real-time and relevant insights.
Expand your analytical reach across linguistic boundaries. Key driver analysis supports multiple languages, ensuring that your insights are accessible to a global audience.
Make the Most of Key Driver Analysis
To enhance the accuracy and relevancy of the narratives, it’s recommended to maintain clean and well-structured datasets. Ensure that your visual analytics are labeled correctly, as key driver analysis uses these labels to generate contextual narratives.
Usage in the Demo Environment
To test this feature you need to integrate your demo environment with OpenAI using your own OpenAI API token, see Start Using the Demo Environment.