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Wednesday, March 3, 2021

Nationwide Insurance Used BI

 March 03, 2021     No comments   

 Read "End-of-Chapter Application Case: Nationwide Insurance Used BI to Enhance Customer Service" at the end of Chapter 1 in the textbook, and answer the following questions.

1. Why did Nationwide need an enterprise-wide data warehouse?

2. How did integrated data drive the business value?

3. What forms of analytics are employed at Nationwide?

4. With integrated data available in an enterprise data warehouse, what other applications could Nationwide potentially develop?


Chapter 1 Highlights

• The business environment is becoming complex and is rapidly changing, making decision making more difficult.

• Businesses must respond and adapt to the changing environment rapidly by making faster and better decisions.

• The time frame for making decisions is shrinking, whereas the global nature of decision making is expanding, necessitating the development and use of computerized DSS.

• Computerized support for managers is often essential for the survival of an organization.

• An early decision support framework divides decision situations into nine categories, depending on the degree of structuredness and managerial activities. Each category is supported differently.

• Structured repetitive decisions are supported by standard quantitative analysis methods, such as MS, MIS, and rule-based automated decision support.

• DSS use data, models, and sometimes knowledge management to find solutions for semistructured and some unstructured problems.

• BI methods utilize a central repository called a data warehouse that enables efficient data mining, OLAP, BPM, and data visualization.

• BI architecture includes a data warehouse, business analytics tools used by end users, and a user interface (such as a dashboard).

• Many organizations employ descriptive analytics to replace their traditional flat reporting with interactive reporting that provides insights, trends, and patterns in the transactional data.

• Predictive analytics enable organizations to establish predictive rules that drive the business outcomes through historical data analysis of the existing behavior of the customers.

• Prescriptive analytics help in building models that involve forecasting and optimization techniques based on the principles of operations research and management science to help organizations to make better decisions.

• Big Data analytics focuses on unstructured, large data sets that may also include vastly different types of data for analysis.

• Analytics as a field is also known by industry-specific application names such as sports analytics. It is also known by other related names such as data science or network science


1.11 Resources, Links, and the Teradata University Network Connection

The use of this chapter and most other chapters in this book can be enhanced by the tools described in the following sections.

Resources and Links

We recommend the following major resources and links:

• The Data Warehousing Institute (tdwi.org)

• Information Management (information-management.com)

• DSS Resources (dssresources.com)

• Microsoft Enterprise Consortium (enterprise.waltoncollege.uark.edu/mec.asp)

Vendors, Products, and Demos

Most vendors provide software demos of their products and applications. Information about products, architecture, and software is available at dssresources.com.

Periodicals

We recommend the following periodicals:

• Decision Support Systems

• CIO Insight (cioinsight.com)

• Technology Evaluation (technologyevaluation.com)

• Baseline Magazine (baselinemag.com)

The Teradata University Network Connection

This book is tightly connected with the free resources provided by Teradata University Network (TUN; see teradatauniversitynetwork.com). The TUN portal is divided into two major parts: one for students and one for faculty. This book is connected to the TUN portal via a special section at the end of each chapter. That section includes appropriate links for the specific chapter, pointing to relevant resources. In addition, we provide hands-on exercises, using software and other material (e.g., cases) available at TUN.

The Book’s Web Site

This book’s Web site, pearsonhighered.com/turban, contains supplemental textual material organized as Web chapters that correspond to the printed book’s chapters. The topics of these chapters are listed in the online chapter table of contents. Other content is also available on an independent Web site (dssbibook.com).2

2 As this book went to press, we verified that all the cited Web sites were active and valid. However, URLs are dynamic. Web sites to which we refer in the text sometimes change or are discontinued because companies change names, are bought or sold, merge, or fail. Sometimes Web sites are down for maintenance, repair, or redesign. Many organizations have dropped the initial “www” designation for their sites, but some still use it. If you have a problem connecting to a Web site that we mention, please be patient and simply run a Web search to try to identify the possible new site. Most times, you can quickly find the new site through one of the popular search engines. We apologize in advance for this inconvenience.


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