I1 Basics of Business Analytics Bangalore University B.Com 5th Semester NEP Notes

16/11/2023 1 By indiafreenotes
Unit 1 [Book]
Data, Types of Data, Forms of Data, Evolution of Big Data VIEW
Business Analytics, Need for Analytics, Types of Analytics VIEW
Importance of Business Analytics in Decision Making VIEW
Analytics Process Model VIEW
Spreadsheet analysis VIEW
Internet of Things VIEW


Unit 2 [Book]
Overview of DBMS VIEW
Data Warehousing Concepts, Need, Objectives VIEW
Relevance of Data Warehousing in Business Analytics VIEW
Data Mining, Application of Data Mining, Data Mining Technique, Data Classification VIEW
Hadoop Distributed File System, Features of HDFS VIEW
Map Reduce, Features of Map Reduce VIEW


Unit 3 [Book]
Data Scientists, New Era of Data Scientists, Data Scientist model, Sources of Data Scientists VIEW
Horizontal Data Scientists Versus Vertical Data Scientists VIEW
Retention of Data Scientists VIEW
Data Visualization, Types, Issues, Tools in Data Visualization VIEW
Data Collection, Sampling and Pre-processing, Types of Data Sources VIEW
Types of Data, Elements, Visual Data VIEW
Exploration and Exploratory Statistical Analysis VIEW
Missing Values, Standardizing Data, Data Categorization, Weights of Evidence Coding, Variable Selection, Data Segmentation VIEW


Unit 4 [Book]
Predictive Analytics VIEW
Linear Regression VIEW
Logistic Regression VIEW
Decision Trees VIEW
Neural Networks VIEW
Support Vector Machines VIEW
Ensemble Methods VIEW
Multiclass Classification Techniques VIEW
Evaluating Predictive Models VIEW
Descriptive Analytics VIEW
Association Rules VIEW
Sequence Rules Segmentation VIEW
Survival Analysis, Measurements VIEW
Kaplan Meier Analysis VIEW
Parametric Survival Analysis VIEW
Proportional Hazards Regression VIEW
Extensions of Survival Analysis Models VIEW
Evaluating Survival Analysis Models VIEW


Unit 5 [Book]
Social Network Analytics VIEW
Social Network Metrics VIEW
Social Network Learning VIEW
Relational Neighbor Classifier, Probabilistic Relational Neighbor Classifier VIEW
Relational Logistic Regression VIEW
Collective Inference VIEW
Egonets VIEW
Mobile Analytics VIEW
Practices of analytics in Google VIEW
Practices of analytics in General Electric VIEW
Practices of analytics in Microsoft VIEW
Practices of analytics in Kaggle VIEW
Practices of analytics in Facebook VIEW
Practices of analytics in Amazon VIEW
Google Analytics VIEW
Practical Approach VIEW