Normal view MARC view ISBD view

Fundamentals of business analytics (Record no. 4673)

MARC details
000 -LEADER
fixed length control field	05042nam a22002177a 4500
005 - DATE & TIME
control field	20190813110610.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field	190813b xxu\|\|\|\|\| \|\|\|\| 00\| 0 eng d
020 ## - ISBN
International Standard Book Number	9788126563791
Price	769
040 ## - CATALOGING SOURCE
Original cataloging agency	S.X.U.K
041 ## - Language
Language	English
082 ## - DDC NUMBER
Classification number	658.4 PRA(FUN)Ed2
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name	Prasad, R.N
245 ## - TITLE STATEMENT
Title	Fundamentals of business analytics
Statement of responsibility	R.N Prasad; Seema Acharya
250 ## - EDITION STATEMENT
Edition statement	2nd ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc	New Delhi
Name of publisher, distributor, etc	Wiley
Date of publication, distribution, etc	c2016
300 ## - PHYSICAL DESCRIPTION
Pages	xxiii;403
Other Details	P.B
500 ## - GENERAL NOTE
General note	1 Business View of Information Technology Applications<br/><br/>1.1 Business Enterprise Organization, Its Functions, and Core Business Processes<br/><br/>1.2 Baldrige Business Excellence Frameworks (Optional Reading)<br/><br/>1.3 Key Purpose of using IT in Business<br/><br/>1.4 The Connected World: Characteristics of Internet-Ready IT Applications<br/><br/>1.5 Enterprise Applications (ERP/CRM, etc.) and Bespoke IT Applications<br/><br/>1.6 Information Users and Their Requirements<br/><br/> <br/><br/>2 Types of Digital Data<br/><br/>2.1 Introduction<br/><br/>2.2 Getting into “GoodLife” Database<br/><br/>2.3 Getting to Know Structured Data<br/><br/>2.4 Getting to Know Unstructured Data<br/><br/>2.5 Getting to Know Semi-Structured Data<br/><br/>2.6 Difference between Semi-Structured and Structured Data<br/><br/> <br/><br/>3 Introduction to OLTP and OLAP<br/><br/>3.1 OLTP (On-Line Transaction Processing)<br/><br/>3.2 OLAP (On-Line Analytical Processing)<br/><br/>3.3 Different OLAP Architectures<br/><br/>3.4 OLTP and OLAP<br/><br/>3.5 Data Models for OLTP and OLAP<br/><br/>3.6 Role of OLAP Tools in the BI Architecture<br/><br/>3.7 Should OLAP be Performed Directly on Operational Databases?<br/><br/>3.8 A Peek into the OLAP Operations on Multidimensional Data<br/><br/>3.9 Leveraging ERP Data Using Analytics<br/><br/> <br/><br/>4 Getting Started with Business Intelligence<br/><br/>4.1 Using Analytical Information for Decision Support<br/><br/>4.2 Information Sources Before Dawn of BI?<br/><br/>4.3 Definitions and Examples in Business Intelligence, Data Mining, Analytics, Machine Learning, Data Science<br/><br/>4.4 Looking at “Data” from Many Perspectives<br/><br/>4.5 Business Intelligence (BI) Defined<br/><br/>4.6 Why BI? How Can You Achieve Your Stated Objectives?<br/><br/>4.7 Some Important Questions About BI - Where, When and What<br/><br/>4.8 Evolution of BI and Role of DSS, EIS, MIS, and Digital Dashboards<br/><br/>4.9 Need for BI at Virtually all Levels<br/><br/>4.10 BI for Past, Present, and Future<br/><br/>4.11 The BI Value Chain<br/><br/>4.12 Introduction to Business Analytics<br/><br/> <br/><br/>5 BI Definitions and Concepts<br/><br/>5.1 BI Component Framework<br/><br/>5.2 Who is BI for?<br/><br/>5.3 BI Users<br/><br/>5.4 Business Intelligence Applications<br/><br/>5.5 BI Roles and Responsibilities<br/><br/>5.6 Best Practices in BI/DW<br/><br/>5.7 The Complete BI Professional<br/><br/>5.8 Popular BI Tools<br/><br/> <br/><br/>6 Basics of Data Integration<br/><br/>6.1 Need for Data Warehouse<br/><br/>6.2 Definition of Data Warehouse<br/><br/>6.3 What is a Data Mart?<br/><br/>6.4 What is then an ODS?<br/><br/>6.5 Ralph Kimball’s Approach vs. W.H. Inmon’s Approach<br/><br/>6.6 Goals of a Data Warehouse<br/><br/>6.7 What Constitutes a Data Warehouse?<br/><br/>6.8 Extract, Transform, Load<br/><br/>6.9 What is Data Integration?<br/><br/>6.10 Data Integration Technologies<br/><br/>6.11 Data Quality<br/><br/>6.12 Data Profiling<br/><br/> <br/><br/>7 Multidimensional Data Modeling<br/><br/>7.1 Introduction<br/><br/>7.2 Data Modeling Basics<br/><br/>7.3 Types of Data Model<br/><br/>7.4 Data Modeling Techniques<br/><br/>7.5 Fact Table<br/><br/>7.6 Dimension Table<br/><br/>7.7 Typical Dimensional Models<br/><br/>7.8 Dimensional Modeling Life Cycle<br/><br/> <br/><br/>8 Measures, Metrics, KPIs and Performance Management<br/><br/>8.1 Understanding Measures and Performance<br/><br/>8.2 Measurement System Terminology<br/><br/>8.3 Navigating a Business Enterprise, Role of Metrics and Metrics Supply Chain<br/><br/>8.4 “Fact-Based Decision Making” and KPIs<br/><br/>8.5 KPI Usage in Companies<br/><br/>8.6 Where do Business Metrics and KPIs Come From?<br/><br/>8.7 Connecting the Dots: Measures to Business Decisions and Beyond<br/><br/> <br/><br/>9 Basics of Enterprise Reporting<br/><br/>9.1 Reporting Perspectives Common to All Levels of Enterprise<br/><br/>9.2 Report Standardization and Presentation Practices<br/><br/>9.3 Enterprise Reporting Characteristics in OLAP World<br/><br/>9.4 Balanced Scorecard<br/><br/>9.5 Dashboards<br/><br/>9.6 How Do You Create Dashboards?<br/><br/>9.7 Scorecards vs. Dashboards<br/><br/>9.8 The Buzz behind Analysis…<br/><br/> <br/><br/>10 Understanding Statistics<br/><br/>10.1 Role of Statistics in Analytics<br/><br/>10.2 Data, Data Description and Summarization<br/><br/>10.3 Statistical Tests<br/><br/>10.4 Understanding Hypothesis and t-Test<br/><br/>10.5 Correlation Analysis<br/><br/>10.6 Regression<br/><br/>10.7 ANOVA<br/><br/>10.8 The F-Test<br/><br/>10.9 Time Series Analysis<br/><br/> <br/><br/>11 Application of Analytics<br/><br/>11.1 Application of Analytics<br/><br/>11.2 Analytics in Industries<br/><br/>11.3 Widely Used Application of Analytics<br/><br/> <br/><br/>12 Data Mining Algorithms<br/><br/>12.1 Association Rule Mining<br/><br/>12.2 k-Means Clustering<br/><br/>12.3 Decision Tree<br/><br/> <br/><br/>13 BI Road Ahead<br/><br/>13.1 Understanding BI and Mobility<br/><br/>13.2 BI and Cloud Computing<br/><br/>13.3 Business Intelligence for ERP Systems<br/><br/>13.4 Social CRM and BI<br/><br/> <br/><br/>Unsolved Exercises<br/><br/>Glossary<br/><br/>Index<br/><br/>
650 ## - Subject
Subject	FUNDAMENTALS OF BUSINESS ANALYTICS
700 ## - Added Entry Personal Name
Relator Code	auth.
Added Entry Personal Name	Acharya, Seema
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type	MBA - Masters on Business Administration

Holdings
Source of classification or shelving scheme	Location (home branch)	Sublocation or collection (holding branch)	Shelving location	Date acquired	Source of acquisition	Cost, normal purchase price	Serial Enumeration / chronology	Koha issues (times borrowed)	Koha full call number	Barcode (Accession No.)	Koha date last seen	Koha date last borrowed	Copy Number	Price effective from	Koha item type
Dewey Decimal Classification	St. Xavier's University, Kolkata	St. Xavier's University, Kolkata	Lending Section	08/09/2019	Bharat	769.00	S.X.U.K	2	658.4 PRA(FUN)Ed2.C3	M782	02/26/2020	02/25/2020	934;C3	08/13/2019	MBA - Masters on Business Administration
Dewey Decimal Classification	St. Xavier's University, Kolkata	St. Xavier's University, Kolkata	Lending Section	08/09/2019	Bharat	769.00	S.X.U.K	4	658.4 PRA(FUN)Ed2.C2	M781	08/31/2022	08/17/2022	935;C2	08/13/2019	MBA - Masters on Business Administration
Dewey Decimal Classification	St. Xavier's University, Kolkata	St. Xavier's University, Kolkata	Lending Section	08/09/2019	Bharat	769.00	S.X.U.K	1	658.4 PRA(FUN)Ed2.C1	M780	09/14/2022	08/31/2022	936;C1	08/13/2019	MBA - Masters on Business Administration
Dewey Decimal Classification	St. Xavier's University, Kolkata	St. Xavier's University, Kolkata	Lending Section	08/09/2019	Bharat	769.00	S.X.U.K	4	658.4 PRA(FUN)Ed2	M779	01/29/2024	01/15/2024	937	08/13/2019	MBA - Masters on Business Administration