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For example, at a company providing manufacturing technology services, the priority was predicting sales opportunities, while at a company that designs and manufactures automatic test equipment (ATE), it was developing a platform for equipment production automation that relied heavily on forecasting. And guess what?
The value of Big Data is not solely dependent on the volume of data available, but on how it is utilized. The Big Data ecosystem is rapidly evolving, offering various analytical approaches to support different functions within a business. DescriptiveAnalytics is used to determine “what happened and why.”
Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios. Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptiveanalytics: Assessing historical trends, such as sales and revenue.
Revisiting the foundation: Data trust and governance in enterprise analytics Despite broad adoption of analytics tools, the impact of these platforms remains tied to dataquality and governance. times more likely to report successful analytics initiatives compared to those with ad hoc approaches.
Descriptiveanalytics: Where most organizations begin and linger Descriptiveanalytics answers the question: What happened? These are your standard reports and dashboard visualizations of historical data showing sales last quarter, NPS trends, operational thoughts or marketing campaign performance.
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