Principles of Information Systems Chapter 5: Database System and Big Data PDF

Summary

This chapter from the Principles of Information Systems textbook covers database systems and big data. It discusses various data models, the relational database model, database schemas, data manipulation languages, and the roles of database administrators and data administrators. The chapter also introduces big data, data warehouses, data marts, and data lakes, highlighting their distinctions.

Full Transcript

Principles of Information Systems, Thirteenth Edition Chapter 5 Database System and Big Data © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a...

Principles of Information Systems, Thirteenth Edition Chapter 5 Database System and Big Data © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain 1 product or service or otherwise on a password-protected website for classroom use. Objectives After completing this chapter, you will be able to: Identify the advantages of the database approach to data management Identify the various types of data models and explain how they are useful in planning a database Describe the relational database model Define the role of the database schema, data definition language, and data manipulation language Discuss the role of a database administrator and data administrator Define the term big data Define the terms data warehouse, data mart, and data lakes and explain how they are different © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. Introduction Database: an organized collection of data A database management system (DBMS) is a group of programs that: Manipulate the database Provide an interface between the database and its users and other application programs © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 3 or otherwise on a password-protected website for classroom use. Data Fundamentals Without data and the ability to process it: An organization could not successfully complete most business activities Data consists of raw facts Data must be organized in a meaningful way to transform it into useful information © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 4 or otherwise on a password-protected website for classroom use. Hierarchy of Data A bit (binary digit) represents a circuit that is either on or off A byte is made up of eight bits Each byte represents a character Field: a name, number, or combination of characters that describes an aspect of a business object or activity Record: a collection of related data fields File: a collection of related records © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 5 or otherwise on a password-protected website for classroom use. Hierarchy of Data Database: a collection of integrated and related files Hierarchy of data: bits, characters, fields, records, files, and databases © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 6 or otherwise on a password-protected website for classroom use. Data Entities, Attributes, and Keys Entity: a person, place, or thing for which data is collected, stored, and maintained Attribute: a characteristic of an entity Data item: the specific value of an attribute Primary key: a field or set of fields that uniquely identifies the record © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 7 or otherwise on a password-protected website for classroom use. Data Entities, Attributes, and Keys © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 8 or otherwise on a password-protected website for classroom use. The Database Approach Traditional approach to data management Each distinct operational system used data files dedicated to that system Database approach to data management Information systems share a pool of related data Offers the ability to share data and information resources A database management system (DBMS) is required © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 9 or otherwise on a password-protected website for classroom use. The Database Approach © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 10 or otherwise on a password-protected website for classroom use. Data Modeling and Database Characteristics Considerations when building a database Content: what data should be collected? cost? Access: what data should be provided to which users and when? Logical structure: how should data be arranged so that it makes sense? Physical organization: where should data be physically located? Archiving: how long to store? Security: how can data be protected? © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 11 or otherwise on a password-protected website for classroom use. Data Modeling Data model: a diagram of data entities and their relationships Enterprise data modeling: data modeling done at the level of the entire enterprise Entity-relationship (ER) diagrams: data models that use basic graphical symbols to show the organization of and relationships between data © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 12 or otherwise on a password-protected website for classroom use. Data Modeling © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 13 or otherwise on a password-protected website for classroom use. Data Modeling © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 14 or otherwise on a password-protected website for classroom use. Relational Database Model Relational model: a simple but highly useful way to organize data into collections of two-dimensional tables called relations Each row in the table represents an entity Each column represents an attribute of that entity Domain: range of allowable values for a data attribute © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 15 or otherwise on a password-protected website for classroom use. Relational Database Model © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 16 or otherwise on a password-protected website for classroom use. Manipulating Data Selecting: eliminating rows according to certain criteria Projecting: eliminating columns in a table Joining: combining two or more tables Linking: combining two or more tables through common data attributes to form a new table with only the unique data attributes © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 17 or otherwise on a password-protected website for classroom use. Manipulating Data © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 18 or otherwise on a password-protected website for classroom use. Manipulating Data © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 19 or otherwise on a password-protected website for classroom use. Data Cleansing Also called data cleaning or data scrubbing The process of detecting and then correcting or deleting incomplete, incorrect, inaccurate, irrelevant records that reside in a database The cost of performing data cleansing can be quite high Different from data validation Which involves the identification of “bad data” and its rejection at the time of data entry © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 20 or otherwise on a password-protected website for classroom use. Data Cleansing © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 21 or otherwise on a password-protected website for classroom use. Relational Database Management Systems (DBMSs) Creating and implementing the right database system ensures that the database will support both business activities and goals Capabilities and types of database systems vary considerably © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 22 or otherwise on a password-protected website for classroom use. SQL Databases SQL: a special-purpose programming language for accessing and manipulating data stored in a relational database SQL databases conform to ACID properties: Atomicity, consistency, isolation, and durability 1986: SQL was adopted by ANSI as the standard query language for relational databases © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 23 or otherwise on a password-protected website for classroom use. SQL Databases © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 24 or otherwise on a password-protected website for classroom use. Database Activities Providing a user view of the database Adding and modifying data Storing and retrieving data Manipulating the data and generating reports © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 25 or otherwise on a password-protected website for classroom use. Providing a User View Schema: a description of the entire database A schema can be part of the database or a separate schema file The DBMS can reference a schema to find where to access the requested data in relation to another piece of data © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 26 or otherwise on a password-protected website for classroom use. Creating and Modifying the Database Data definition language (DDL) A collection of instructions and commands used to define and describe data and relationships in a specific database Allows the database’s creator to describe data and relationships that are to be contained in the schema Data dictionary: a detailed description of all the data used in the database Can also include a description of data flows, information about the way records are organized, and the data- processing requirements © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 27 or otherwise on a password-protected website for classroom use. Storing and Retrieving Data When an application program needs data, it requests the data through the DBMS Concurrency control deals with the situation in which two or more users or applications need to access the same record at the same time © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 28 or otherwise on a password-protected website for classroom use. Manipulating Data and Generating Reports Data manipulation language (DML): a specific language, provided with a DBMS Allows users to access and modify the data, to make queries, and to generate reports A DBMS can produce a wide variety of documents, reports, and other output that can help organizations achieve their goals © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 29 or otherwise on a password-protected website for classroom use. Database Administration Database administrators (DBAs): skilled and trained IS professionals Works with users to define their data needs Applies database programming languages to craft a set of databases to meet those needs Tests and evaluates databases Implements changes to improve their databases’ performance Assures that data is secure from unauthorized access Data administrator: a nontechnical position responsible for defining and implementing consistent principles for a variety of data issues Including setting data standards and data definitions that apply across all the databases in an organization The data administrator can be a high-level position reporting to top-level managers © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 30 or otherwise on a password-protected website for classroom use. Popular Database Management Systems © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 31 or otherwise on a password-protected website for classroom use. Popular Database Management Systems Database as a Service (DaaS) The database is stored on a service provider’s servers The database is accessed by the client over a network, typically the Internet Database administration is handled by the service provider Example of DaaS: Amazon Relational Database Service (Amazon RDS) © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 32 or otherwise on a password-protected website for classroom use. Using Databases with Other Software DBMSs can act as front-end or back-end applications Front-end applications interact directly with people Back-end applications interact with other programs or applications Example: The Library of Congress (LOC) provides a back-end application that allows Web access to its databases, which include references to books and digital media in the LOC collection © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 33 or otherwise on a password-protected website for classroom use. Big Data Extremely large and complex data collections Traditional data management software, hardware, and analysis processes are incapable of dealing with them Three characteristics of big data Volume Velocity Variety © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 34 or otherwise on a password-protected website for classroom use. Sources of Big Data © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 35 or otherwise on a password-protected website for classroom use. Big Data Uses Examples: Retail organizations monitor social networks to engage brand advocates, identify brand adversaries Advertising and marketing agencies track comments on social media Hospitals analyze medical data and patient records Consumer product companies monitor social networks to gain insight into consumer behavior Financial service organizations use data to identify customers who are likely to be attracted to increasingly targeted and sophisticated offers © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 36 or otherwise on a password-protected website for classroom use. Challenges of Big Data How to choose what subset of the data to store Where and how to store the data How to find the nuggets of data that are relevant to the decision making at hand How to derive value from the relevant data How to identify which data needs to be protected from unauthorized access © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 37 or otherwise on a password-protected website for classroom use. Data Warehouses, Data Marts, and Data Lakes Data warehouse: a large database that collects business information from many sources in the enterprise in support of management decision making ETL process Extract Transform Load © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 38 or otherwise on a password-protected website for classroom use. Data Warehouses, Data Marts, and Data Lakes Data mart: a subset of a data warehouse that is used by small- and medium- sized businesses and departments within large companies to support decision making A specific area in the data mart might contain greater detailed data than the data warehouse Data lake: takes a “store everything” approach to big data, saving all the data in its raw and unaltered form Also called an enterprise data hub Raw data is available when users decide just how they want to use the data Only when the data is accessed for a specific analysis is it extracted from the data lake © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 39 or otherwise on a password-protected website for classroom use. NoSQL Databases NoSQL database Provides a means to store and retrieve data that is modeled using some means other than the simple two-dimensional tabular relations used in relational databases Advantages: Ability to spread data over multiple servers so that each server contains only a subset of the total data Do not require a predefined schema Data structures are more flexible and can provide improved access speed and redundancy © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 40 or otherwise on a password-protected website for classroom use. NoSQL Databases © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 41 or otherwise on a password-protected website for classroom use. Hadoop Hadoop An open-source software framework that includes several software modules that provide a means for storing and processing extremely large data sets Has two primary components: A data processing component (MapReduce) A distributed file system (Hadoop Distributed File System, HDFS) © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 42 or otherwise on a password-protected website for classroom use. Hadoop © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 43 or otherwise on a password-protected website for classroom use. In-Memory Databases In-memory database (IMDB) A database management system that stores the entire database in random access memory (RAM) Provides access to data at rates much faster than storing data on some form of secondary storage Enables the analysis of big data and other challenging data-processing applications Performs best on multiple multicore CPUs © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 44 or otherwise on a password-protected website for classroom use. Summary The database approach to data management has become broadly accepted Data modeling is a key aspect of organizing data and information A well-designed and well-managed database is an extremely valuable tool in supporting decision making We have entered an era where organizations are grappling with a tremendous growth in the amount of data available and struggling how to manage and make use of it A number of available tools and technologies allow organizations to take advantage of the opportunities offered by big data © 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service 45 or otherwise on a password-protected website for classroom use.

Use Quizgecko on...
Browser
Browser