• No results found

Integrating analytics into the Graduate DEGREE curriculum

N/A
N/A
Protected

Academic year: 2021

Share "Integrating analytics into the Graduate DEGREE curriculum"

Copied!
11
0
0

Loading.... (view fulltext now)

Full text

(1)

Integrating analytics into

the Graduate DEGREE

curriculum

IBM Workshop: Smarter Analytics

August 15, 2013

Amit Deokar

Associate Professor

(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

(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 2011 - 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

(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)

(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

(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

(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

in-motion/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

(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

(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)

(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)

(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

References

Related documents

The company deployed IBM® SPSS® Modeler and IBM SPSS Modeler Server software in-house – replacing third-party analytics services and enabling the company to develop more advanced

• SPSS Modeler Premium extends the functionality of SPSS Modeler Professional by including a powerful text mining workbench for extracting key concepts, sentiments and

• Access SPSS Statistics graphs and reporting tools directly from the SPSS Modeler Professional interface Data preparation • Access operational data from Cognos

IBM® SPSS® Modeler Server supports integration with data mining and modeling tools that are available from database vendors, including IBM Netezza, IBM DB2 InfoSphere Warehouse,

IBM® SPSS® Modeler Server supports integration with data mining and modeling tools that are available from database vendors, including Oracle Data Miner, IBM DB2 InfoSphere

With the English-language version of IBM SPSS Text Analytics for Surveys, you can choose to create categories using a semantic network. The software uses this method in

By leveraging the IBM Loss Analysis and Warning System (LAWS), SPSS predictive analytics software and big data analytics solutions, insurance companies can discover these

IBM Netezza In-Database Analytics Transformations Geospatial Predictive Statistics Data Mining More Tools In-Database Analytics SAS R Fuzzy Logix Zementis IBM SPSS BI Tools