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Lecture

Chapter 7.docx

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Department
Administration
Course
ADM2372
Professor
Mirou Jaana
Semester
Winter

Description
Chapter 7 – Databases and Data Warehouses • DATABASES Organizational Data and Information Relational Database Fundamentals Database Management Systems Integrating Data Among Multiple Databases • DATA WAREHOUSING Overview and Fundamentals of Data Warehousing Business Intelligence Data Mining Database: A database is a collection of data. Each database, each file, each group of data should have one unique identifier. We all have an individual student ID, no two students have the same ID. You need to have unique identifiers for elements in the database. If you do analysis, and you want to retrieve information, you will get duplicate information and it would get messy, confusing and inaccurate. What is the difference between data and information? Data is raw numbers, and information is analyzed data, or data with meaning. Data are raw facts that describe the characteristics of an event. Information is data converted into a meaningful and useful context (aspect of granularity) *Granularity: amount of detail of the information. - The higher you go up in an organization, the more you look at the big picture, rather than the tiny details, because you want to do the planning and forecasting. Organizational Data and Information • Information granularity – refers to the extent of detail within the information (fine and detailed or coarse and abstract) Levels Formats Granularities 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. (Transactions within units, and functional areas) Sales receipts, airline tickets, packing slips (Transactional) (processed to give) Product statistics, trends, future growth, sales forecasts (Analytical)Analytical information: Encompasses all organizational information, and its primary purpose is to support the performing of higher-level analysis tasks. (Supports the decision-making at higher levels) The Value of Quality Data and Information Accuracy: Are all the values correct? For example, is the name spelled correctly? Is the dollar amount recorded properly? Typo’s etc. Completeness: Are any of the values missing? For example, is the address complete including street, city, province, and postal code? Consistency: You want to be consistent in the type of data you are collecting. If you are consistent in the type of data you are collecting, and the totals are not consistent with the individual cells. Is aggregate of summary information in agreement with detailed information? For example, do all total fields equal the true total of the individual fields? Uniqueness: Is each transaction, entity, and event represented only once in the information? For example: are there any duplicate customers? Timeliness: Is the information current with respect to the business requirements? For example, is information updates weekly, daily, or hourly? What are some of the reasons why we have poor information? - There are four primary sources of low-quality information that relate to internal and external activities: o Employee is not trained to use the system. o Online customer forms will have mistakes often (intentionally and unintentionally). They write some information, and they don’t want to write all of it. Four Primary Sources of Low-Quality Information: - Online customers intentionally enter inaccurate information to protect their privacy - Data or information from different systems have different entry standards and formats - Call center operators enter abbreviated or erroneous information to save time. - Third party and external information contains inconsistencies, inaccuracies and errors. What Are the Implications of Poor Information for Businesses? • Think of implications related to customers and business opportunities. • 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. 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 Relational Database Fundamentals • Where can information be found in an organization? Information is everywhere. (It is stored in databases) • Information is stored in databases Collection of data organized to serve several applications efficiently Maintain information about various types of objects (inventory), events (transactions), people (employees), and places (warehouses) • 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. Mostly in legacy (old) systems • Information presented in levels, in hierarchy. Insurance companies, and banking industry uses these. Network database model – a flexible way of representing objects and their relationships • Networks. Multiple relationships between levels. The more you add layers, the more complicated they become. Relational database model – stores information in the form of logically related two-dimensional tables • These are the most popular and most used ones • They store information in the form of tables. Example: items sold, suppliers. Relational Databases • Most popular for PCs and large computers • Represent data as two-dimensional tables called relations; tables may be referred to as files • Relate data across tables based on common data element • Example: Microsoft Access is an example, because you have bi-dimensional tables filled with data and you try to link the tables. • Entity – a person, place, thing, transaction, or event about which information is stored The rows in each table contain the entities • Entity class (table) – a collection of similar entities • Attributes (fields, columns) – characteristics or propertie
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