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Businesses of all sizes are no longer asking if they need increased access to business intelligence analytics but what is the best BI solution for their specific business. Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story.
Predictive & PrescriptiveAnalytics. Predictive Analytics: What could happen? We mentioned predictive analytics in our business intelligence trends article and we will stress it here as well since we find it extremely important for 2020. The commercial use of predictive analytics is a relatively new thing.
Consider these questions: Do you have a platform that combines statistical analyses, prescriptiveanalytics and optimization algorithms? Generative AI has the potential to deliver powerful support in key data areas: Master data cleansing to reduce duplications and flag outliers.
Data analysts leverage four key types of analytics in their work: Prescriptiveanalytics: Advising on optimal actions in specific scenarios. Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. SQL manages and retrieves data from databases, handling larger datasets.
If we dig deeper, we find that two factors are really at work: Causal data versus correlated dataData maturity as it relates to business outcomes. One of the most fundamental tenets of statistical methods in the last century has focused on correlation to determine causation.
But we are seeing increasing data suggesting that broad and bland data literacy programs, for example statistics certifying all employees of a firm, do not actually lead to the desired change. New data suggests that pinpoint or targeted efforts are likely to be more effective. We do have good examples and bad examples.
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