Business Plan

CONSUMER

Family Stage:

Vacation Choices:

Television Shows Watched:

Favorite Websites:

Hobbies/Sports/Other Entertainment:

Publication Subscriptions:

Organizations/Affiliations:

Political Affiliation:

Type of Car Owned:

Other:

What is the current approximate size of your target market?

What is the rate of growth of your target market?

What changes are occurring in the makeup of the market?

What changes in social values and concerns are affecting the product/service

Chapter 7, pages 113 and 117

DATABASE SYSTEMS

REFERENCES

[1] Bais, Hanane, Mustapha Machkour, and Lahcen Koutti. “Querying database using a universal natural language interface based on machine learning.” In 2016 International Conference on Information Technology for Organizations Development (IT4OD), pp. 1-6. IEEE, 2016.

This paper shows how extracting information from a database system is a basic obligation. It recognize the importance of providing easy access to information stored in a database system. The paper elaborates about the tools that allow users to query database using database query languages such as SQL (Structured Query Language). This paper presents the Architecture and the implementation of a generic natural language interface based on machine learning approach for a relational database. It is useful for the undergraduate students and professional whose job is to keep database for institutions.

[2] Elmasri, Ramez. Fundamentals of database systems. Pearson Education India, 2008.

The paper clearly explains the theory and design, broad coverage of models and real systems, and an up-to-date introduction to modern database technologies which result in a leading introduction to database systems. The paper is useful for computer science majors, as it emphasizes on math models, design issues, relational algebra, and relational calculus and it give students opportunities to practice the fundamentals of design and implementation. The paper also cover the most popular database topics, including SQL, security, and data mining, and features increased emphasis on XML and semi-structured data.

[3] Coronel, Carlos, and Steven Morris. Database systems: design, implementation, & management. Cengage Learning, 2016.

This edition gives students a foundation in design and implementation with diagrams, tables and illustrations. The text provides students with an outstanding equality of theory and practice, this edition has many improvements like; expanded relational algebra coverage, updated coverage of cloud data services among others. New review questions, cases and problem sets have been added in the book to ensure students have multiple opportunities to see if they understand and also help them develop useful design skills. The book is useful for researchers and those interested in the studying database management.

[4] Nidzwetzki, Jan Kristof, and Ralf Hartmut Guting. “DISTRIBUTED SECONDO: An extensible highly available and scalable database management system.” (2016).

This papers is a highly available and scalable data store but it provides only limited capabilities for data analyses. However, database management systems (DBMS) provide a lot of functions to analyse data but most of them scale poorly. In this paper, a novel method is proposed to couple Cassandra with a DBMS. The result is a highly available and scalable system that provides all the functions from the DBMS in a distributed manner. The paper is useful for the students interested to learn about the functions of DBMS and how they can be used in data management.

[5] Seghier, Mohamed L., Elnas Patel, Susan Prejawa, Sue Ramsden, Andre Selmer, Louise Lim, Rachel Browne et al. “The PLORAS Database: A data repository for predicting language outcome and recovery after stroke.” NeuroImage 124 (2016): 1208-1212.

The paper is practical and easy to understand, database systems: design, implementation, and management, gives students a solid foundation in database design and implementation. Filled with visual aids such as diagrams, illustrations, and tables, it has provided an in-depth coverage of database design, demonstrating that the key to successful database implementation is in proper design of databases to fit within a larger strategic view of the data environment. The paper has also expanded coverage of Big Data and related Hadoop technologies, SQL coverage expanded to include MySQL databases. The book is important for students and it gives them multiple opportunities to test their understanding and develop real and useful design skills.

[6] Venables, Anne, and Paul I. Boon. “What environmental, social or economic factors identify high-value wetlands? Data-mining a wetlands database from south-eastern Australia.” Pacific Conservation Biology (2016).

In this paper the authors show the benefits of questioning databases to identify wetlands of high social, economic and environmental worth. There are three data mining methods; artificial neural networks, univariate analysis and multivariate analysis and they were applied. Simple statistical techniques were applied in identifying high-value wetlands with a prediction accuracy using small set of environmental indicators. The general approach came from the analysis of a single wetland database and is more likely to get conservation applications in other many Pacific regions. The paper is useful for the students who are interested in data mining and other professions.

[7] Levitus, Sydney, J. I. Antonov, Olga K. Baranova, T. P. Boyer, C. L. Coleman, H. E. Garcia, A. I. Grodsky et al. “The world ocean database.” Data Science Journal 12, no. 0 (2013): WDS229-WDS234.

The authors talk of the World Ocean Database (WOD) as the most exhaustive database available internationally without any bounds. All the data are in one well recorded format and can be found in DVDs for less charge and are also available on on-line without charge. The World Ocean Database 2009 is the latest DVD version, the WOD is the product of the U.S. National Oceanographic Data centre. International oceanographic data exchange that has occurred under the auspices of the Intergovernmental Oceanographic Commission encompasses WOD. This paper is crucial for the data mining students in the undergraduate and those in the Database management professions.

Page | 2