Business Operations Excellence through Advanced Analytics, AI & Decision Intelligence | Enabling the shift from Data-Driven to Knowledge-Powered Organizations | Cognitive Transformation beyond Digital
In #DataDriven #DecisionMaking, it's important that users understand the different types of #DataAnalytics and how to interact with the data at each stage. 📊 #DescriptiveAnalytics provides clean, normalized, and aggregated data in a way that is convenient for users to analyze. It shows the actual state of play and can be based on historical or immediate streamed data. At this stage, real analysis must be done by users; they need to figure out what these results mean and what to do with this information. 🔎 #DiagnosticAnalytics is the next step, aiming to understand why we have these results. It significantly aids users by executing the main part of the analysis, so users already know what happened and why. At this stage, users can focus on simulating future scenarios to choose the best one. 🔮 #PredictiveAnalytics helps the user with forecasting by providing different scenarios that are likely to happen depending on actuals, trends, historical data, and possible future events. At this stage, users need to evaluate forecasts and decide on future actions. 📋 #PrescriptiveAnalytics goes further and recommends possible actions that users could take, so users just need to pick the best one. 🙂🧠 For all four types of data analytics, the final decision is made by users. Data analytics helps make this decision more precise, data-informed, and minimizes human effort and errors.
