http://www.epistemypress.com

Order Review Copy& Classroom Materials at

PRACTICAL ANALYTICS

Comprehensive and self-contained overview of modern analytics concepts and tools

real-world skill building that reinforces fundamental concepts

theory, applications, and hands-on experience using the latest industry tools

topics: data provisioning, reporting & analysis, data visualization, knowledge discovery, prediction, decision making

Tools: Microsoft excel, sap business objects, sap netweaver business warehouse, sap hana, sap lumira, SAP Predictive Analytics, and more.

Applied analytics concepts using market-leading software tools

AuthorsNitin Kale

Univ. Of Southern California

Nancy JonesSan Diego State

Prerequisites: • An introductory course in information technology covering information systems, internet,

technology enabled business, spreadsheets, databases, digital representation of data, • Basics of hardware and software, and business processes. • Basic skills in Microsoft Excel – working with tables, formula, sorting and filtering and charting

Introductory course on statistics Suggested Course Duration: The book is designed to be the basis for a 15 week long semester covering 45 contact hours. Each chapter would be covered in approximately one 3 hour lecture followed by take home/lab assignments. These assignments include exercises and projects using SAP and other common Analytics applications. Students are expected to spend between 2-4 hours a week on the assignments. Sample syllabi for various courses will be available on the textbook website. Section 2 is intended for a more technical audience. It can be bypassed in a purely business oriented class. Such a class can spend more time on case studies in the remaining 10 chapters.

Audience: This book is intended for students who are interested in a career as a data analyst or business user/executive. This book is written from a business/engineering point of view.

Engineering: Information Technology Industrial Engineering Computer Science

Business: Accounting Finance Marketing Supply Chain/ Logistics MIS/CIS Operations Management

Section 1 - Basics1. Introduction to data analyticsSection 2 - Data Provisioning2. Data acquisition3. Data harmonization4. Data stagingSection 3 - Reporting and analysis5. Slicing and dicing6. ReportingSection 4 - Data Visualization7. Charts and Dashboards

8. Advanced visualizationSection 5 – Knowledge discovery, prediction & decision making9. Data mining10. Descriptive models for data mining11. Predictive models for data mining12. Big data analytics13. Decision making

Table Of contents