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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.
PredictiveModeling to support business needs, forecast, and test theories. Assisted PredictiveModeling. Data Discovery including self-serve data preparation, smart data visualization with charts, graphs and other visualizations for clarity and decisions. Real Time and Cached Cube Management.
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No longer will the business user need to slice and dice the data or ask for more data to answer a business question. For example, a false positive or false negative for cancer diagnosis can result in tremendous emotional distress, additional unnecessary tests, and even death.
Interactivity can include dropdowns and filters for users to slice and dice data. Later on, you’ll appreciate being able to test ideas and leverage best practices as your needs evolve. Predictive analytics use a combination of data sets from multiple sources to find relationships and correlations.
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