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To impart basic knowledge on regulatory authorities and agencies governing the manufacture and sale of pharmaceuticals.
To recognize, understand and apply the language, theory and models of the field of business analytics
Module:I Overview of Business Analytics:
Module 2: Descriptive Analytics, Predictive Analytics and Prescriptive Analytics:
Module 3: Data Issues:
Module 4: Data Mining and Testing: Definition, Concepts, Applications and Methods.
Module 5: Security: Security requirements, User Access, Data classification, User Classification, Data Movement, And Impact of security on design.
Module 6: Decision Modelling and Forecasting:
Module 7: Fundamentals of R Language:
Text Books Recommended
Effective Predictive Analytics, Integrating Analytics in Business Processes, Unstructured Data Analytics, Balanced Scorecard, Dashboards, KPI based on Dashboard and Scorecard
Organization/sources of data, Importance of data quality, Dealing with missing or incomplete data, Data Classification Data Warehouse: Definition, Features, Applications, Types of data warehouse
Architecture: Business Analysis framework, 3-tier data warehouse framework. Data Warehouse Models: Virtual Warehouse, Data Mart and Enterprise warehouse.
Metadata: Meaning and Categories, Role of metadata, Metadata respiratory, Challenges for metadata management, Data Cube
Online Analytical Processing Server (OLAP): Types, OLAP operations, OLAP Vs Operational Database (OLTP) SCHEMA: Star Schema, Snowflake schema, Fact Constellation schema
Security: Security requirements, User Access, Data classification, User Classification, Data Movement, And Impact of security on design.
Linear Programming: Introduction, Types of Linear programming problems/Models, Linear programming Model elements, Model formulation procedure, Computer based solutions for linear programming using Simplex method
Integer Programming: Introduction, Solving IP problems/Models Forecasting: Introduction, Types of Variation in Time series data, Simple Regression Model, Multiple Regression Models
Decision Theory: Introduction, Decision theory model elements, types of decision environments, decision theory formulation, decision making under uncertainty and risk, Decision trees.