My friend Sasha asked me about Predictive Analytics (knowing it was my favorite subject). Like most other business people, Sasha has a lot of professional knowledge but no exposure to analytics and the concept of Predictive Analytics is frightening and foreign to her. If your business team wants to up its game and get into predictive analytics, it really isn’t that hard. You can select an augmented analytics tool that allows your business users to leverage these features without a data science or business analyst background.
There are lots of predictive analytics techniques and all of these will be at your fingertips within an easy-to-use augmented analytics environment so your team will not be intimidated. Techniques include:
- Time Series Forecasting (Holt Winters, Single, Double, Triple, Box Jenkins, ARIMA and ARIMAX)
- Regression (Simple and Multiple Linear)
- Classification (Naïve Bayes, Decision Tree, K-Nearest Neighbor, Multinomial Logistic Regression, Binary Logistic Regression and Support Vector Machine)
- Association (Frequent Pattern Mining)
- Correlation (Spearman and Karl Pearson)
- Clustering (K Means and Hierarchical)
- Hypothesis Tests (One-Way Anova, Paired T-Test, Independent T-Test, Chi-Squared Test)
- Descriptive Statistics (Mean, Median, Mode, Standard Deviation, Variance, Quartiles, Percentiles, Skewness and Kurtosis)
You can use these techniques for quality control, fraud mitigation, customer churn, demand planning, product and service cross-selling, maintenance management, customer targeting, loan approval, marketing optimization, online target marketing, analysis of external data, and student assessments, just to name a few things. If you are a business professional and you can see an application in your own role for these types of tools, you don’t have to be afraid of the idea of predictive analytics. Let the augmented analytics solution do the work for you and show you the results in a way that is meaningful to your role.
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