Introduction to Business & Information Systems PDF

FBB0025 VALUING AND STORING INTRODUCTION TO BUSINESS & ORGANIZATIONAL INFORMATION - INFORMATION SYSTEMS DATABASES  CHAPTER SIX OVERVIEW Data, Information, Databases. © McGraw Hill 2 ...

FBB0025 VALUING AND STORING INTRODUCTION TO BUSINESS & ORGANIZATIONAL INFORMATION - INFORMATION SYSTEMS DATABASES  CHAPTER SIX OVERVIEW Data, Information, Databases. © McGraw Hill 2  LEARNING OUTCOMES 1. Explain the four primary traits that determine the value of data. 2. Describe a database, a database management system, and the relational database model. 3. Identify the business advantages of a relational database. © McGraw Hill 3  DATA QUALITY 1 Data is everywhere in an organization. Employees must be able to obtain and analyze the many different levels, formats, and granularities of organizational data to make decisions. Successfully collecting, compiling, sorting, and analyzing data can provide tremendous insight into how an organization is performing. © McGraw Hill 4  DATA QUALITY 2 Levels, Formats, and Granularities of data Access the text alternative for slide images. © McGraw Hill 5  DATA TYPE 3 The four primary traits of the value of data. © McGraw Hill 6  DATA TYPE 1 Transactional data – Encompasses all of the data contained within a single business process or unit of work, and its primary purpose is to support the performing of daily operational tasks. Analytical data – Encompasses all organizational data, and its primary purpose is to support the performing of managerial analysis tasks. © McGraw Hill 7  DATA TYPE 2 Access the text alternative for slide images. © McGraw Hill 8  DATA TIMELINESS Timeliness is an aspect of data that depends on the situation. Real-time data – Immediate, up- to-date data. Real-time system – Provides real-time data in response to requests. © McGraw Hill 9  DATA QUALITY 3 Business decisions are only as good as the quality of the data used to make the decisions. You never want to find yourself using technology to help you make a bad decision faster. Data inconsistency. Data integrity issues. © McGraw Hill 10  DATA QUALITY 4 Characteristics of High-quality data. Accurate. Complete. Consistent. Unique. Timely. © McGraw Hill 11  DATA QUALITY 5 Low Quality Data Example Access the text alternative for slide images. © McGraw Hill 12  UNDERSTANDING THE COSTS OF USING LOW-QUALITY DATA 1 The four primary sources of low quality data include: 1. Customers intentionally enter inaccurate data to protect their privacy. 2. Different entry standards and formats. 3. Operators enter abbreviated or erroneous data by accident or to save time. 4. Third party and external data contains inconsistencies, inaccuracies, and errors. © McGraw Hill 13  UNDERSTANDING THE COSTS OF USING LOW-QUALITY DATA 2 Potential business effects resulting from low quality data include: Inability to accurately track customers. Difficulty identifying valuable customers. Inability to identify selling opportunities. Marketing to nonexistent customers. Difficulty tracking revenue. Inability to build strong customer relationships. © McGraw Hill 14  UNDERSTANDING THE BENEFITS OF GOOD DATA High quality data can significantly improve the chances of making a good decision. Good decisions can directly impact an organization's bottom line. A data steward is responsible for ensuring data policies and procedures are implemented across an organization. © McGraw Hill 15  DATA GOVERNANCE Data governance - Refers to the overall management of the availability, usability, integrity, and security of company data. Master data management (MDM) - The practice of gathering data and ensuring that it is uniform, accurate, consistent, and complete, including such entities as customers, suppliers, products, sales, employees, and other critical entities that are commonly integrated across organizational systems. Data validation - Includes the tests and evaluations used to determine compliance with data governance polices to ensure correctness of data. © McGraw Hill 16  STORING DATA IN A RELATIONAL DATABASE 1 Data is everywhere in an organization. Data is stored in databases. Database – maintains data about various types of objects (inventory), events (transactions), people (employees), and places (warehouses). © McGraw Hill 17  STORING DATA IN A RELATIONAL DATABASE 2 Database management systems (DBMS) – Allows users to create, read, update, and delete data in a relational database. Access the text alternative for slide images. © McGraw Hill 18  STORING DATA IN A RELATIONAL DATABASE 3 Data element – The smallest or basic unit of data. Data model – Logical data structures that detail the relationships among data elements using graphics or pictures. Metadata –Details about data. Data dictionary – Compiles all of the metadata about the data elements in the data model. © McGraw Hill 19  STORING DATA ELEMENTS IN ENTITIES AND ATTRIBUTES Entity – A person, place, thing, transaction, or event about which data is stored. The rows in a table contain entities. Attribute (field, column) – The data elements associated with an entity. The columns in each table contain the attributes. Record – A collection of related data elements. © McGraw Hill 20  CREATING RELATIONSHIPS THROUGH KEYS Primary keys and foreign keys identify the various entities (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. © McGraw Hill 21  USING A RELATIONAL DATABASE FOR BUSINESS ADVANTAGES Database advantages from a business perspective include: © McGraw Hill 22  INCREASED FLEXIBILITY A well-designed database should, Handle changes quickly and easily. Provide users with different views. Have only one physical view - Deals with the physical storage of data on a storage device. Have multiple logical views – Focuses on how individual users logically access data to meet their own particular business needs. © McGraw Hill 23  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. © McGraw Hill 24  REDUCED DATA REDUNDANCY Databases reduce data redundancy. Data redundancy – The duplication of data or storing the same data in multiple places. Inconsistency is one of the primary problems with redundant data. © McGraw Hill 25  INCREASE DATA – INTEGRITY (QUALITY) Data integrity – measures the quality of data. Integrity constraint – rules that help ensure the quality of data. Relational integrity constraint. Business-critical integrity constraint. © McGraw Hill 26  INCREASED DATA SECURITY Data is an organizational asset and must be protected. Databases offer several security features. Password – Provides authentication of the user. Access level – Determines who has access to the different types of data. Access control – Determines types of user access, such as read-only access. © McGraw Hill 27