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- Automated analysis: Important changes are automatically detected by Yellowfin Signals and sent directly to you as soon as they’re discovered. This aims to reduce human bias, and analysis fatigue.
- Configurable & scalable: The Signals analysis is easily configurable. Let the system know what data trends and insights are important to you. Creating a Signals analysis schedule is a one-time task, but can be updated as your data changes. You can schedule the analysis to run as frequently as you like.
- Personalized: The system knows the data and content you have access to, and will only send Signals based on your data permissions. It also personalizes the Signals it sends to you based on how you interact with all Signals (by rating or watching it).
- Interactive & collaborative: Users that receive a signal can collaborate with other users on it. The system offers other forms of interaction as well, including exploring other related signals, providing a natural language explanation of the generated Signal, tweaking the main Signals chart to compare with similar data, etc.
- Self-improving: The system continuously learns about user’s preferences based on their feedback and interaction. Users can rate Signals, which lets Yellowfin know about the type of Signals of interest to them. Yellowfin aims then avoid sending irrelevant insights to users by matching the Signals that receive low ratings.
- Relevance: Understand Understands how relevant and importance important a signal is in relation to your data.
- Explanation: Yellowfin provides additional automated analysis to get to the root cause of the signal using the Assisted Insights functionality.
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Signal type | Related analysis group | Description |
Spikes & drops | Detected using the Outliers analysis | Sudden increases or decreases in the metric. For example, a lot of extra visits occurred on the product page of your website yesterday. |
Step changesBreakouts | OutliersThe | trend direction stays the same but there has been a jump up or down in valueSuccessive increases (called Prolonged Spikes) or successive decreases (Prolonged Drops) in metric. For example, although the trend line direction is the same, sales jumped 25% last weekchocolate sales going up the entire week before Valentine’s day is a prolonged spike. |
Change in trend | Trend change | A trend line changes from up to down, or vice versa. For example, PC sales were growing but then started to decline last month. |
Change in volatility | Trend change | Volatility describes how much the value changes from one period to another. For example, the share price becomes very volatile after news that the trade deal was cancelled. |
Change in Total (one period to another) | Period comparison | Compares the total this week, month, quarter with another similar period - last week, month, this quarter last year. |
New lost attributes | Period comparison | Significant attributes that entered or left the data this period. For example, a customer that bought every month stopped buying this month. |
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