Coursehero >> California >> San Jose State >> BUS 188

Course Hero has millions of student submitted documents similar to the one below including study guides, homework solutions, papers, exam answer keys and textbook solutions.

6 CHAPTER DATABASES AND DATA WAREHOUSES Opening Case Searching for Revenue - Google McGrawHill/Irwin 2008 The McGrawHill Companies, All Rights Reserved 6-2 Chapter Six Overview SECTION 6.1 DATABASE FUNDAMENTALS Understanding Information Database Fundamentals Database Advantages Relational Database Fundamentals Database Management Systems Integrating Data Among Multiple Databases SECTION 6.2 DATA WARAEHOUSE FUNDAMENTALS Accessing Organizational Information History of Data Warehousing Data Warehouse Fundamentals Business Intelligence Data Mining SECTION 6.1 DATABASE FUNDAMENTALS McGrawHill/Irwin 2008 The McGrawHill Companies, All Rights Reserved 6-4 UNDERSTANDING INFORMATION Information is everywhere in an organization Employees must be able to obtain and analyze the many different levels, formats, and granularities of organizational information to make decisions Successfully collecting, compiling, sorting, and analyzing information can provide tremendous insight into how an organization is performing 6-5 UNDERSTANDING INFORMATION Information granularity refers to the extent of detail within the information (fine and detailed or coarse and abstract) Levels Formats Granularities 6-6 Information Quality Business decisions are only as good as the quality of the information used to make the decisions Characteristics of high quality information include: Accuracy Completeness Consistency Uniqueness Timeliness 6-7 Information Quality Low quality information example 6-8 Understanding the Costs of Poor Information The four primary sources of low quality information include: 1. Online customers intentionally enter inaccurate information to protect their privacy 2. Information from different systems have different entry standards and formats 3. Call center operators enter abbreviated or erroneous information by accident or to save time 4. Third party and external information contains inconsistencies, inaccuracies, and errors 6-9 Understanding the Costs of Poor Information Potential business effects resulting from low quality information include: Inability to accurately track customers Difficulty identifying valuable customers Inability to identify selling opportunities Marketing to nonexistent customers Difficulty tracking revenue due to inaccurate invoices Inability to build strong customer relationships 6-10 Understanding the Benefits of Good Information High quality information can significantly improve the chances of making a good decision Good decisions can directly impact an organization's bottom line 6-11 DATABASE FUNDAMENTALS Information is everywhere in an organization Information is stored in databases Database maintains information about various types of objects (inventory), events (transactions), people (employees), and places (warehouses) 6-12 DATABASE FUNDAMENTALS Database models include: Hierarchical database model information is organized into a tree-like structure (using parent/child relationships) in such a way that it cannot have too many relationships Network database model a flexible way of representing objects and their relationships Relational database model stores information in the form of logically related two-dimensional tables 6-13 DATABASE ADVANTAGES Database advantages from a business perspective include Increased flexibility Increased scalability and performance Reduced information redundancy Increased information integrity (quality) Increased information security 6-14 Increased Flexibility A well-designed database should: Handle changes quickly and easily Provide users with different views Have only one physical view Physical view deals with the physical storage of information on a storage device Have multiple logical views Logical view focuses on how users logically access information 6-15 Increased Scalability and Performance A database must scale to meet increased demand, while maintaining acceptable performance levels Scalability refers to how well a system can adapt to increased demands Performance measures how quickly a system performs a certain process or transaction 6-16 Reduced Redundancy Databases reduce information redundancy Redundancy the duplication of information or storing the same information in multiple places Inconsistency is one of the primary problems with redundant information 6-17 Increased Integrity (Quality) Information integrity measures the quality of information Integrity constraint rules that help ensure the quality of information Relational integrity constraint rule that enforces basic and fundamental information-based constraints Business-critical integrity constraint rule that enforce business rules vital to an organization's success and often require more insight and knowledge than relational integrity constraints 6-18 Increased Security Information is an organizational asset and must be protected Databases offer several security features including: Password provides authentication of the user Access level determines who has access to the different types of information Access control determines types of user access, such as read-only access 6-19 RELATIONAL DATABASE FUNDAMENTALS Entity a person, place, thing, transaction, or event about which information is stored The rows in each table contain the entities In Figure 6.5 CUSTOMER includes Dave's Sub Shop and Pizza Palace entities Entity class (table) a collection of similar entities In Figure 6.5 CUSTOMER, ORDER, ORDER LINE, DISTRIBUTOR, and PRODUCT entity classes 6-20 RELATIONAL DATABASE FUNDAMENTALS Attributes (fields, columns) characteristics or properties of an entity class The columns in each table contain the attributes In Figure 6.5 attributes for CUSTOMER include: Customer ID Customer Name Contact Name Phone 6-21 RELATIONAL DATABASE FUNDAMENTALS Primary keys and foreign keys identify the various entity classes (tables) in the database Primary key a field (or group of fields) that uniquely identifies a given entity in a table Foreign key a primary key of one table that appears an attribute in another table and acts to provide a logical relationship among the two tables 6-22 Potential relational database for CocaCola 6-23 DATABASE MANAGEMENT SYSTEMS Database management systems (DBMS) software through users which and application programs interact with a database 6-24 DATABASE MANAGEMENT SYSTEMS Four components of a DBMS 6-25 Data Definition Component Data definition component creates and maintains the data dictionary and the structure of the database The data definition component includes the data dictionary Data dictionary a file that stores definitions of information types, identifies the primary and foreign keys, and maintains the relationships among the tables 6-26 Data Definition Component Data dictionary essentially defines the logical properties of the information that the database contains 6-27 Data Manipulation Component Data manipulation component allows users to create, read, update, and delete information in a database A DBMS contains several data manipulation tools: View allows users to see, change, sort, and query the database content Report generator users can define report formats Query-by-example (QBE) users can graphically design the answers to specific questions Structured query language (SQL) query language 6-28 Data Manipulation Component Sample report using Microsoft Access Report Generator 6-29 Data Manipulation Component Sample report using Access Query-By-Example (QBE) tool 6-30 Data Manipulation Component Results from the query in Figure 6.10 6-31 Data Manipulation Component SQL version of the QBE Query in Figure 6.10 6-32 Application Generation and Data Administration Components Application generation component includes tools for creating visually appealing and easy-touse applications Data administration component provides tools for managing the overall database environment by providing faculties for backup, recovery, security, and performance IT specialists primarily use these components 6-33 INTEGRATING DATA AMONG MULTIPLE DATABASES Integration allows separate systems to communicate directly with each other Forward integration takes information entered into a given system and sends it automatically to all downstream systems and processes Backward integration takes information entered into a given system and sends it automatically to all upstream systems and processes 6-34 INTEGRATING DATA AMONG MULTIPLE DATABASES Forward and backward integration 6-35 INTEGRATING DATA AMONG MULTIPLE DATABASES Building a central repository specifically for integrated information SECTION 6.2 DATA WAREHOUSE FUNDAMENTALS McGrawHill/Irwin 2008 The McGrawHill Companies, All Rights Reserved 6-37 HISTORY OF DATA WAREHOUSING Data warehouses extend the transformation of data into information In the 1990's executives became less concerned with the day-to-day business operations and more concerned with overall business functions The data warehouse provided the ability to support decision making without disrupting the day-to-day operations 6-38 DATA WAREHOUSE FUNDAMENTALS Data warehouse a logical collection of information gathered from many different operational databases that supports business analysis activities and decision-making tasks The primary purpose of a data warehouse is to aggregate information throughout an organization into a single repository for decision-making purposes 6-39 DATA WAREHOUSE FUNDAMENTALS Extraction, transformation, and loading (ETL) a process that extracts information from internal and external databases, transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse Data mart contains a subset of data warehouse information 6-40 DATA WAREHOUSE FUNDAMENTALS 6-41 Multidimensional Analysis Databases contain information in a series of two-dimensional tables In a data warehouse and data mart, information is multidimensional, it contains layers of columns and rows Dimension a particular attribute of information 6-42 Multidimensional Analysis Cube common term for the representation of multidimensional information 6-43 Multidimensional Analysis Data mining the process of analyzing data to extract information not offered by the raw data alone To perform data mining users need data-mining tools Data-mining tool uses a variety of techniques to find patterns and relationships in large volumes of information and infers rules that predict future behavior and guide decision making 6-44 Information Cleansing or Scrubbing An organization must maintain highquality data in the data warehouse Information cleansing or scrubbing a process that weeds out and fixes or discards inconsistent, incorrect, or incomplete information 6-45 Information Cleansing or Scrubbing Contact information in an operational system 6-46 Information Cleansing or Scrubbing Standardizing Customer name from Operational Systems 6-47 Information Cleansing or Scrubbing 6-48 Information Cleansing or Scrubbing Accurate and complete information 6-49 BUSINESS INTELLIGENCE Business intelligence information that people use to support their decisionmaking efforts Principle BI enablers include: Technology People Culture 6-50 DATA MINING Data-mining software includes many forms of AI suc as neural networks and expert systems 6-51 DATA MINING Common forms of data-mining analysis capabilities include: Cluster analysis Association detection Statistical analysis 6-52 Cluster Analysis Cluster analysis a technique used to divide an information set into mutually exclusive groups such that the members of each group are as close together as possible to one another and the different groups are as far apart as possible CRM systems depend on cluster analysis to segment customer information and identify behavioral traits 6-53 Association Detection Association detection reveals the degree to which variables are related and the nature and frequency of these relationships in the information Market basket analysis analyzes such items as Web sites and checkout scanner information to detect customers' buying behavior and predict future behavior by identifying affinities among customers' choices of products and services 6-54 Statistical Analysis Statistical analysis performs such functions as information correlations, distributions, calculations, and variance analysis Forecast predictions made on the basis of time-series information Time-series information time-stamped information collected at a particular frequency

Find millions of documents here - Study Guides, Homework Solutions, Papers, Exam Answer Keys and more. Course Hero has millions of course related materials that will enable you to learn better, faster and get an A in all your courses.
Below is a small sample set of documents: