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Business Intelligence & Data Mining SAS


Units: 6


With the proliferation of Web 2.0 making inroads into the enterprises and industries, the ability to understand, analyze and interpret businesses from Big Data has become increasingly more important today. This class aims to equip you with highly demanded business analytics skills in the current job market. The course will focus on extracting business intelligence by leveraging firm's business data as well as online social media content for various applications, including (but not limited to) search engine marketing, social media analytics, crowd-sourcing management, market analysis and demand estimation, social network analysis, customer segmentation, customer relationship management (CRM), web mining and health care management.

The class will be hands-on and the emphasis will be placed on the "know-how" aspect - how to extract and apply business intelligence to improve business decision making and marketing strategies. We will analyze real-world business data from Fortune 500 companies using various business intelligence tools, primarily SAS Enterprise Miner. Time permits, we will also introduce some advanced economic and predictive models in analyzing digital markets. Prior programming skill is not required. Throughout the class business insights from several market leaders such as Google, Microsoft, Amazon, Travelocity, Netflix, Uber, Yelp and Facebook will be revealed.

Learning Outcomes

Class Objectives
• Differentiate, design and assess various business intelligence (BI) and data mining models.
• Identify and translate real-world business problems into BI and data mining problems.
• Exhibit ability in pre-preparing and visualizing the right data towards these problems.
• Implement efficient BI strategies to solve these problems.
• Develop proficiency in BI software (SAS Enterprise Miner).
• Enhance knowledge and skills in the current trends in the management and use of BI.

Prerequisites Description

No official prerequisite, preferably some knowledge in statistics, economics and database.