diagnoosianalytiikka

Diagnosianalytiikka, often translated as diagnostic analytics, is a type of business analytics focused on understanding why certain events have occurred. It is the second step in the progression of analytics, following descriptive analytics, which describes what happened. Diagnostic analytics delves deeper to uncover the root causes of these past events by examining the data for patterns and correlations.

This process involves techniques such as data mining, drill-down capabilities, and correlation analysis. For example, if descriptive analytics reveals a sudden drop in sales, diagnostic analytics would be used to investigate potential reasons, such as a marketing campaign that failed to resonate, a competitor's new product launch, or an unexpected economic downturn. By identifying these causal factors, organizations can gain a clearer understanding of their operational performance and the underlying drivers of their successes and failures.

The insights derived from diagnostic analytics are crucial for informing decision-making. While descriptive analytics tells you *what* happened, diagnostic analytics explains *why* it happened. This understanding allows businesses to address problems more effectively, replicate successful strategies, and mitigate risks by making informed adjustments based on past performance. It serves as a bridge between understanding the past and predicting or influencing the future, paving the way for more advanced analytical approaches like predictive and prescriptive analytics.

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