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Here are 25 more lessons we've learned (the hard way) about what's easy and what's hard when it comes to telling data stories: Easy: Picking a good visualization to answer a data question Hard: Discovering the core message of your data story that will move your audience to action Easy: Knowing who is your target audience Hard: Knowing what motivates (..)
Short story #2: PredictiveModeling, Quantifying Cost of Inaction. Short story #4: Multi-dimensional Slicing and Dicing! Short story #2: PredictiveModeling, Quantifying Cost of Inaction. Thank goodness for predictivemodels. Short story #1: Treemaps, Sunbursts, Packed Trees, Oh My!
PredictiveModeling to support business needs, forecast, and test theories. Assisted PredictiveModeling. Social BI Tools that allow for sharing of data, alerts, dashboards and interactivity to support decisions, enable online communication and collaboration. Real Time and Cached Cube Management.
No longer will the business user need to slice and dice the data or ask for more data to answer a business question. Figure 6: Amazon Machine Learning to build and deploy PredictiveModels.
Machine learning and predictivemodeling allowed the company to use complex historical warranty claim and cost information, previous and new product attributes, and forecasting data to create a predictive data model for future warranty costs. With a tool like Sisense, it changes the game altogether.”.
Embedded BI and Augmented Analytics includes traditional BI components like dashboards, KPIs, Reports with interactive drill-down, drill through, slice and dice and self-serve analytics capabilities. Benefits of Embedded BI. The benefits of Embedded BI and Augmented Analytics are numerous.
Businesses can analyze text to understand positive, negative and neutral sentiments, and can analyze the sentiments further with slice and dice with context variables such as persons location or demography.
Embedded BI and Augmented Analytics includes traditional BI components like dashboards, KPIs, reports with interactive drill-down, drill through, slice and dice and self-serve analytics capabilities.
Interactivity can include dropdowns and filters for users to slice and dice data. These ensure accurate visual displays, as well as compatibility with mobile device, features such as “touch input.” Predictive analytics use a combination of data sets from multiple sources to find relationships and correlations.
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