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Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. Suddenly advanced analytics wasn’t just for the analysts. 4) Predictive And PrescriptiveAnalytics Tools.
Decades (at least) of business analytics writings have focused on the power, perspicacity, value, and validity in deploying predictive and prescriptiveanalytics for business forecasting and optimization, respectively. How do predictive and prescriptiveanalytics fit into this statistical framework?
Accompanying the massive growth in sensor data (from ubiquitous IoT devices, including location-based and time-based streaming data), there have emerged some special analytics products that are growing in significance, especially in the context of innovation and insights discovery from on-prem enterprise data sources.
When data science was in its “early days” within businesses, the data scientists mostly worked offline with static sources (like databases or web-based reports) to build and test analytics models for potential deployment in the enterprise. These may not be high risk. They might actually be high-reward discoveries.
According to a recent Forbes article, “the prescriptiveanalytics software market is estimated to grow from approximately $415M in 2014 to $1.1B This way when you reach out to a customer, you can see all customer notes so make your interaction more personalized. in 2019, attaining a 22 percent compound annual growth rate.”
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