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Data Information Systems and Management. Valuing Organizational Information. Transactional Information Contained within a business process Supports performing daily operations Analytical Information Includes transactional information plus market and industry information
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Valuing Organizational Information • Transactional Information • Contained within a business process • Supports performing daily operations • Analytical Information • Includes transactional information plus market and industry information • The Value of Timely Information • Real Time: Immediate, up-to-date • Within the Decision Makers Time frame
Characteristics of High-Quality Information • Accuracy • Completeness • Consistency • Uniqueness • Timeliness
The Cost of Low-Quality Information • Using the wrong information can lead to making the wrong decision • The wrong decision can cost time, money, and even reputations
The Benefits Of High-Quality Information • Improve chances of making a good decision which, in turn, may directly affect the organization’s bottom line
Data Resource Management Data Planning • Develop an overall data and architecture for the firm’s data resources that ties in with the firm’s strategic mission and plans, and the objectives and processes of it’s business units. Data Administration • Involves the establishment and enforcement of policies and proceduresfor managing data as a strategic corporate resource.
Database Structures • Hierarchical • One-to-many (Tree like) • Network • Many-to-many • Relational • Elements reside in two dimensional interlinked tables • Multidimensional • Cubes of data • Object Oriented • Encapsulation: data and operations are stored together
Entity Relationship Diagram (ERD) • Tool Used In Data Modeling • Depicts relationships between entities • Entity: a category of stored data • Relationship: how entities are associated • Attributes: descriptive components of an entity • An ERD model can be easily translated into virtually any type of physical data base implementation
Entity Relationship Diagram Customer Order Item
Rules Of Thumb • 1:1 : One Table • 1:M :primary key from one side used as a foreign key in the many side • M:M : New table with a primary key which is a combination of both the other primary keys.
Rules Of Thumb Bit Byte ≡ Character Field ≡ Data Element ≡ Attributes Record ≡ Data Structure Entity ≡ Table File ≡ Database ≡ Relational Database • Primary Key • Secondary Key (or Foreign Key) • Referential Integrity • Normalization
Referential Integrity The Primary key data must exist before data can be entered in the table where the primary key is used as a Foreign key.
Normalization • A method of simplifying complex data structures • A process of assigning attributes to entities • Determine how to traverse a relational database by identifying primary keys and foreign keys
Normalization First Normal Form (1NF) • An entity is in 1NF if there are no elements, or group of elements, which repeat for a single occurrence of the entity. Second Normal Form (2NF) • An entity is in 2NF if it is in 1NF and if the full key and not part of it derive all non-key elements Third Normal Form (3NF) • An entity is in 3NF if it is in 2NF and if the values for the non-key elements are not dependent on any other non-key elements.
ERD Example Faculty Department Course Student
U of L Database Calendar HR Course • Course # (K) • Course Name • Course Description • Faculty # (k) Faculty • Fac. # (K) • Name • Address • Dept # (k) Phone Book Registration Course # Student # Mark To Grading System Department • Dept. # (K) • Dept. Name • Dept. Description Student • Student # (K) • Student Name • Student Address Admissions Organizational Chart
Organizing Data • Data is processed into information which in turn supports decision making • Database Management System (DBMS) • User/database interface • Database Administrator (DBA) • IT professional responsible for all aspects of the database
Data Management • For data to be turned into information it must first be organized in a meaningful way • Traditional approach • Data redundancy: duplication of data in separate files • Data integrity: the degree to which data is correct • Database approach • A pool of related data is shared by mulitple application programs
Data Modeling • Key Considerations: • What data will be collected • Who will have access to it • How the data will be used • Data Model • A diagram of data entities and their relationships
Data Modeling • Enterprise Data Modeling • Data modeling done at the enterprise level • Entity Relationship Diagram (ERD) • Use basic graphic symbols • Show the organization and relationships between data • Planned Data Redundancy • Summary totals carried in data • To improve system performance • Data Marts in ERP systems
The Relational Database Model • Relational Model: • A database model that describes data in which all data elements are placed in two dimensional tables • The tables are the logical equivalent to files • Domain: Allowable values for data attributes
Data Clean-up • The process of looking for and fixing inconsistencies to ensure that data are accurate and complete
Overview of Database Types • Flat file • Sequential or direct • Does not use database concepts • Single User • One person can use the database at a time (Access) • Multiple Users • Large DBMS (Oracle)
Providing a User View • Schema: • a description of the entire database • Sub schema: • a description of a subset of the database • Users can view and modify data terms in the subset
Creating and Modifying the Database • Data Definition Language (DDL) • Commands used to describe data and their relationships • Data Dictionary • Detailed descriptions of all data in the database
Storing and Retrieving Data • The system must calculate the physical location based upon logical application of data • Concurrency Control • A method of dealing with two people accessing the same location, in the same database, at the same time
Manipulating Data and Generating Reports • Query-by-example (QBE) • Point and click, drag and drop • Data Manipulation Language (DML) • Commands used to manipulate data in a database • Structured Query Language (SQL)
Selecting a Database Management System • Determine information needs of the organization • Considerations • Size (current and future) • Number of Concurrent Users • Performance (response time) • Integration (relation to other applications) • Features (security, privacy, templates) • The Vendor (service, reputation, viability) • Cost
Enterprise Resource Planning • Replace functional mainframe legacy systems with cross-functional client/server network applications. • SAP and others
Cross-Functional Information Systems • Support business processes • Production • Distribution • Order management • Cross boundaries of Traditional business functions. • IT helps by supporting the re-engineering and improvement of business processes. • A strategic way to use IT to share information resources and improve both efficiency and effectiveness of business processes to help a business attain it’s strategic objectives.
Data Warehouse: • A database that collects business information from many sources in the enterprise, covering all aspects of the company’s processes, products, and customers • Data Mart: • Subset of a data warehouse
Data Mining • An information analysis tool that involves the automated discovery of patterns and relationships in a data warehouse • Predictive Analysis • Combines historical data with assumptions about future conditions • Used to predict outcome of events
Business Intelligence • The process of gathering enough of the right information in a timely manner and usable form and analyzing it to have a positive impact on business strategy, tactics, or operations • Competitive Intelligence • Counter Intelligence • Knowledge Management
More Business Intelligence • Competitive Intelligence • One aspect of business intelligence limited to information about competitors • Counter Intelligence • The steps an organization takes to protect information sought by “hostile” intelligence gathers • Knowledge Management • The process of capturing a company’s collective expertise wherever it resides – in computers, on paper, in people’s heads – and distributing it wherever it can help produce bigger payoffs
Distributed Databases • A database in which the data may spread across several smaller databases connected via telecommunication devices • Replicated Database • A database that holds a duplicate set of data
Online Analytical Processing (OLAP) • Software that allows users to explore data from a number of different perspectives
Object-Oriented • Object-Oriented Database • Database that stores both data and its processing instructions together • Encapsulation