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How do we track value enabled through better decision support such as a data science model or a diagnostic visualization versus an experienced manager making decisions? Align on keyindicators of success during the initiation phase of a data science project. How to create clear, concise metrics to set clearer expectations.
Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios. Diagnosticanalytics: Uncovering the reasons behind specific occurrences through pattern analysis.
Section 2: Embedded Analytics: No Longer a Want but a Need Section 3: How to be Successful with Embedded Analytics Section 4: Embedded Analytics: Build versus Buy Section 5: Evaluating an Embedded Analytics Solution Section 6: Go-to-Market Best Practices Section 7: The Future of Embedded Analytics Section 1: What are Embedded Analytics?
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