Integrating analytics into the Graduate DEGREE curriculum

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1 Dakota State University 1 Integrating analytics into the Graduate DEGREE curriculum IBM Workshop: Smarter Analytics August 15, 2013 Amit Deokar Associate Professor Dakota State University Madison, South Dakota amit.deokar@dsu.edu

2 Dakota State University 2 Brief Background Dakota State University Small, Midwest university with about 250 graduate students On-campus and distance learning offerings IS/Analytics-related graduate programs M.S. in Information Systems D.Sc. in Information Systems Certificate Program in Business Analytics started Fall 2012 M.S. in Analytics expected to start Fall 2014

3 Dakota State University 3 Partnership with IBM IBM Academic Initiative Curriculum guides, training materials, and software IBM SPSS Mining in Academia Program (MAP) No-cost use of IBM SPSS Modeler Premium data mining and text analytics software (formerly SPSS Clementine) for classroom teaching and research IBM Academic Skills Cloud Spring Midwest member One of 20 pilot schools across US Opportunity to use IBM software for classroom teaching, delivered through cloud computing, at no charge without having to install and maintain it at the university IBM Rational and WebSphere tools + Analytics-related software Cognos, InfoSphere BigInsights, Infosphere Streams Attractive for distance learning program offerings

4 Dakota State University 4 Certificate Program in Business Analytics Target Audience IT professionals (regardless of industry) who aim to augment their skill set needed to manipulate and analyze large amounts of data to solve business problems Students who want to use the Certificate as a pathway to other graduate offerings (e.g., MSIS, and DSc) Current graduate students (particularly working professionals ), who want to get a specialized certificate focused on analytics Program Requirement 12 credit hours (4 graduate courses) 3 required courses + 1 elective course

5 Dakota State University 5 Certificate Program in Business Analytics Curriculum Design INFS 762 Data Warehousing & NoSQL Databases (updated) Prerequisite INFS 760 (Enterprise Modeling and Data Management) MSIS data management specialization course Updated from original course Data Warehousing & Data Mining INFS 768 Predictive Analytics for Decision Making (new) INFS 770 Advanced Data Mining Applications (new) Select 1 elective among 3 INFS 792 Big Data Analytics (new) INFS 764 Information Retrieval MSIS data management specialization course INFS 766 Advanced Database MSIS data management specialization course

6 Dakota State University 6 Certificate Program in Business Analytics Curriculum design INFS 762 Data Warehousing & NoSQL Databases (updated) Review relational database technologies Data warehousing and OLAP fundamentals Introduction to new paradigms of data systems, including document stores (e.g., MongoDB), extensible record stores (e.g., HBase and Facebook s Cassandra), big data warehouse systems (e.g., Apache Hive) INFS 768 Predictive Analytics for Decision Making (new) Introduction to predictive analytics lifecycle and encompassing technologies Application of select predictive analytics techniques through example scenarios, case studies, and hands-on exercises INFS 770 Advanced Data Mining Applications (new) Data mining methodology and applications focused on pattern recognition Advanced data mining applications e.g., text mining, sentiment analysis, social network analysis, recommender systems, and web usage mining

7 Dakota State University 7 Certificate Program in Business Analytics Elective courses (1 required) INFS 792 Big Data Analytics (new) Principles of Big Data Analytics e.g., Hadoop, MapReduce, HDFS, NoSQL Analyzing Big Data at-rest (IBM BigInsights) and inmotion/streaming (IBM InfoSphere Streams) hands-on labs Data visualization and communication of analytical findings INFS 764 Information Retrieval Information retrieval fundamentals INFS 766 Advanced Database Distributed databases, concurrency control, and specialized data models

8 Dakota State University 8 Upcoming MS in Analytics Target Audience Students who aim to gain knowledge and skillset necessary to solve crucial data-driven business problems and assist with analytics-driven decision making Joint Program MS (Analytics) collaborative program between DSU (Information Systems) and SDSU (Department of Mathematics and Statistics) Program Requirement 30 credit hours (10 graduate courses)

9 Dakota State University 9 Upcoming MS in Analytics Knowledge (Prerequisite) Courses Enterprise Modeling, and Data Management Applied Statistics Core Courses (15 credit hrs) Data Warehousing & NoSQL Databases (updated) Big Data Analytics (new DSU) Programming for Data Analytics (new - DSU) Modern Applied Statistics I (new - SDSU) Modern Applied Statisitics II (new SDSU)

10 Dakota State University 10 Upcoming MS in Analytics Information Systems Specialization (12 credit hrs) Predictive Analytics for Decision Making Advanced Data Mining Applications Information Retrieval Advanced Databases Statistics Specialization (12 credit hrs) Predictive Analytics I Predictive Analytics II Nonparametric Statistics Time Series Analysis Practicum (3 credit hrs) Project with real-world case and data

11 Dakota State University 11 Summary Given the industry demand for analytics-driven decision making, Business Analytics can either be integrated into existing programs as a specialization or developed into independent programs (e.g., certificate or Masters) IBM s Academic Initiative and Academic Skills Cloud offering are valuable resources that can help with technology access hurdle and courseware nuggets that can be customized and used innovatively.