Название: Systems Analysis and Design, 11th Edition
Автор: Kenneth E. Kendall, Julie E Kendall
Издательство: Pearson
Год: 2024
Страниц: 610
Язык: английский
Формат: True PDF, True EPUB
Размер: 150.5 MB

Systems Analysis and Design presents you with the latest systems development methods, tools and techniques in an engaging and easy-to-understand manner. Design elements, including color-coded diagrams and screenshots, combine with pedagogical features and activities throughout the text to support and enhance learning. You'll develop the skills required to create structured, yet intuitive, multilayered and complex systems.

The 11th Edition reflects today's rapidly changing IS field and genuinely improves on the diversity of decision makers and organizations represented throughout the text. New coverage includes innovations in open source software, agile development, workplace analytics, data visualization, metaverse and cybercrime.

Object-oriented analysis and design facilitate logical, rapid, and thorough methods for creating new systems that are responsive to a changing business landscape. Object-oriented techniques work well in situations in which complicated information systems are undergoing continuous maintenance, adaptation, and redesign. In this chapter, we introduce unified modeling language (UML), the industry standard for modeling object-oriented systems. The UML toolset includes diagrams that allow you to visualize the construction of an object-oriented system. Each design iteration takes a successively more detailed look at the design of the system, until the things and relationships in the system are clearly and precisely defined in UML documents. UML is a powerful tool that can greatly improve the quality of your systems analysis and design and thereby help create higher-quality information systems.

Some consider data storage to be the heart of an information system. The data have to be available when the user wants to use them. In addition, the data must be accurate and consistent (they must possess integrity). The objectives of database design include efficient storage of data as well as efficient updating and retrieval. Finally, it is necessary that information retrieval be purposeful. The information obtained from stored data must be in a form that is useful for managing, planning, controlling, or making decisions. There are two approaches to the storage of data in a computer-based system. The first is to store data in individual files, each unique to a particular application. The second approach involves building a database. A database is a formally defined and centrally controlled store of data intended for use in many different applications.

Individual files are often designed with only immediate needs in mind, so it becomes important to query the system for a combination of some of the attributes; these attributes may be contained in separate files or may not even exist. Databases need to be planned so that data are organized for efficient storage and effective retrieval. Data warehouses are very large databases that store summarized data relating to a specific subject, so queries are answered very efficiently. Business intelligence is built around the concept of processing large volumes of data, sometimes called big data. Business analytics uses quantitative tools to analyze big data and inform decisions of managers and computer systems. Data lakes are repositories for raw data, normalized and unnormalized data from relational databases, and nonrelational data from the Internet of Things, mobile devices, and apps of all kinds. Data deposited in data lakes are not structured and predefined before they are collected. Data lakes can be queried simply to gain heretofore unknown insights into customers and their relationships to business goals.

Data warehouses differ from traditional databases. The purpose of a data warehouse is to organize information for quick and effective queries. Data warehouses are seen as a critical part of business intelligence. In effect, they store denormalized data, but they go one step further. They organize data around subjects. Most often, a data warehouse consists of more than one database in which the data represented are processed in uniform ways. The data stored in data warehouses comes from different sources, usually databases that were set up for different purposes.