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  • 2 days ago
Organizations are moving beyond traditional reporting and dashboards to adopt a data-as-a-product approach that enables real-time, data-driven decision-making. Dashboards alone are not enough; treating data as a product helps build reliable, reusable, and user-focused data assets. Here are the key concepts of data as a product: data products, analytics as a value ladder, and data democratization through data mesh. Automation also improves insight generation, let’s read further to know the importance of data quality and governance, and the challenges organizations face during this transition. Overall, I promise a clear understanding of how businesses can transform data into a decision engine to drive faster, smarter, and more effective outcomes.

To know more click here: https://www.nitorinfotech.com/blog/data-as-a-product-how-organizations-can-turn-data-into-decision-engines/

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00:00the four levels of data analytics that transforms raw data into a real decision engine level one
00:06is descriptive analytics it simply answers what happened for example sales in the last month
00:14level two is diagnostic analytics it answers why did it happen you're now identifying root causes
00:22for example sales dropped because delivery delays increased level three is predictive analytics
00:30it answers what is likely to happen models anticipate demand churn and risk in advance
00:36for example sales will drop next week if delays continue and the level four is prescriptive
00:43analytics it answers what should we do your data starts recommending solutions for example switch
00:51suppliers to prevent delays read the entire blog to learn more about how to turn your data into a
00:58real-time decision engine
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