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If you don’t have the ability (or desire) to ask your end-user what KPIs are valuable to them, our KPI examples and templates will give you a pretty good idea of what metrics you can use. e) How are they currently viewing these KPIs? However, even though we love data, we can’t (and shouldn’t) display all of these types.
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This phase also involves conducting holistic performance testing (individual queries, batch loads, consumption reports and dashboards in BI tools, datamining applications, ML algorithms, and other relevant use cases) in addition to functional testing to make sure the converted code meets the required performance expectations.
Other challenges include communicating results to non-technical stakeholders, ensuring data security, enabling efficient collaboration between data scientists and data engineers, and determining appropriate key performance indicator (KPI) metrics.
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