Week 2 8/29/19 Operations Management What is Business Analytics - Many terms are often used interchangeably IE Big Data, Data Science, Machine Learning, Artificial Intelligence, Deep learning Draws upon multiple disciplines – Business, data management, statistics, math, programming The process of Business Analytics - Business Understanding – Data Understanding – Data preparation Modeling Evaluation Deployment Core Ideas - Data Exploration Visualization Classification Prediction Association Rules and Recommender Systems Data Reduction Business Intelligence vs Business Analytics - BI refers to data visualization and reporting for understanding “what happened and what is happening.” BA now typically includes BI as well as sophisticated data analysis methods, such as statistical models and data mining algorithms used for exploring data, quantifying and explaining relationships between measurements, and predicting new records. Examples of BA - Credit Scoring – long established use of predictive modeling techniques for business prediction is credit scoring. Future Purchases – The business Analytics toolkit also includes statistical experiments the common of which is known to marketers as A-B testing. These are often used for pricing decisions Orbitz, found that it could price hotel options higher for mac user than Windows users. Steps in BA Process Data Preparation, Exploration, and Data Reduction – Visualize the data, make sure data is correct, take care of outliers, remove dummy variables ect… step 1 Prediction, Classification, Time Series Forecasting, what goes together, Segmentation - Machine learning also called modeling, step 2 Model Evaluation and Selection – run algorithm to determine who is providing the correct result step 3 Model Deployment – send results to the real world. Step 4 Data Exploration - Data sets are large, complex and messy. Review data to help refine task, employ reduction and Visualization techniques Data Visualization - Helps to clean the data, Interactive graphs and plots of data Supervised learning - - The process of providing and algorithm with records in which an output variable of interest is known and the algorithm “learns” how to predict this value with new records where the output in unknown. Prediction and Classification steps Unsupervised learning - An analysis in which one attempts to learn patterns in the data other than predicting an output value of interest. Deep learning - learning from the present What Goes together and Segmentation Steps, no target variable Robot takes decision based on what occurred or occurs Association Rules and Collaborative Filtering - Exercised by Netflix, if X was purchase, Y was also purchased, this produces results that define “what goes with what”, unsupervised learning Data Reduction and Dimension Reduction - Taking complex/large data into simpler/smaller data is called data reduction Reducing the number of variables/columns is called Dimension Reduction Reducing the number of records/rows SEMMA - The forging steps encompass the steps, a methodology developed By the software company SAS:, Sample Take a sample from the dataset, partition into training, validation and test datasets. - Classification and Prediction Classification comes into picure when you are trying to identify the customer will buy product or not. Target variable.