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Diagnostic Analytics

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Diagnostic Analytics

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Diagnostic Analytics

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big
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diagnostic
Recommended age: 16 years old
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Created by

Ray Larkin
Ray Larkin
United Kingdom

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Diagnostic Analytics Online version

Diagnostic Analytics

by Ray Larkin
1

Hidden Why expertise AI Diagnostic anomalies machine identify three KPIs

analytics : did it happen ?
In descriptive analytics , the importance of Key Performance Indicators were highlighted . These establish common data and identify trends , thresholds , anomalies , and other metrics that lead to the question of why something happened . The functions of diagnostic analytics fall broadly into categories :
Identify : Based on the results of descriptive analysis , analysts must identify areas that require further study .
Drill into the analytics ( discovery ) : Analysts must the data sources that will help them explain anomalies .
Determine the cause of relationships : relationships are uncovered by looking at events that might have resulted in the identified data anomalies . Probability theory , regression analysis , filtering , and time - series data analytics can be useful .
Modern solutions for diagnostic analytics employ learning techniques to help data analysts . Machines are more capable at recognising patterns , detecting anomalies , surfacing ? unusual' events , and identifying drivers of KPIs .
Diagnostic analytics are generally based on the combination of software and the of people to help answer the question Why did it happen ?