Database Management Review
- Pages: 16
- Word count: 3857
- Category: Management
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• Data are raw facts. Information is the result of processing data to reveal their meaning. Accurate, relavant and timely information is the key to good decision making and good decision making is the key to organizational survival in a global environment
• Data are usually stored in a database. To implement a database and manage its contents you need a database management system (DBMS). DBMS serves as an intermediary between the user and the database. The database contains the data you have collected & “data about data” metadata.
• Database design defines the database structure. A well-designed database facilitates data management and generates accurate and valuable information. A poorly designed database can lead to bad decision making and bad decision making can lead to the failure of an organization.
• Databases can be classified according to the number of users supported, where the data are located, the type of data stored, the intended data usage and the degree to which the data are structured.
• Databases evolved from manual and then computerized file systems. In a file system, data are stored in independent files, each requiring its own data management programs. Although this method of data management is largely out-moded, understanding its characteristics makes database design easier to comprehend.
• Some limitations of file system data management are that it requires extensive programming, system administration can be complex and difficult, making changes to existing structures is difficult and security features are likely to be inadequate. Also, independent files tend to contain redundant data, leading to problems of structural and data dependence.
• Database management systems were developed to address the file system’s inherent weaknesses. Rather than depositing data in independent files, a DBMS presents the database to the end user as a single data repository. This arrangement promotes data sharing, thus eliminating the potential problem of islands of information. In addition, the DBMS enforces data integrity, eliminates redundancy, and promotes data security.
1. define each of the following terms:
A) DATA: raw facts such as telephone number, birth date, customer name. Data have little meaning unless they have been organized in some logical manner. B) FIELD: a character or group of characters (alphabetic or numeric) that has a specific meaning. a field is used to define and store data. C) RECORD: a logically connected set of one or more fields that describes a person, place, or thing. For eg. The fields that constitute a customer record might consist of the customer’s name, address, phone number, date of birth, credit limit and unpaid balance. D) FILE: A collection of related records. For example, a file might contain data about the students currently enrolled at Bond University.
2. What is Data redundancy, and which characteristics of the file system can lead to it? Data redundancy is when the same data are stored unnecessarily at different places. Poor data security, data inconsistency, data anomalies (when not all the required changes in the redundant data rare made successfully).
3. What is data independence and why is it lacking in the file systems? Data independence exists when you can change the data storage characteristics without affecting the program’s ability to access the data. Lacking in the file system as most data relies on other data
4. What is a DBMS and what are its functions?
A database management system (DBMS) is a collection of programs that manages the database structure and controls access to the data stored in the database. In a sense, a database resembles a very well organized electronic filing cabinet in which powerful software (the DBMS) helps manage the cabinet’s contents. DBMS functions include data dictionary management (look up the required data component structures and relationships), Data storage management, Data transformation and presentation, security management, multiuser access control, backup and recovery management, data integrity management (accuracy and consistency of data), database access languages and application programming interfaces (Query language where users specify what must be done without having to specify how) and Database communication interfaces (accessing via different networks).
5. What is structural independence and why is it important? Structural independence exists when you can change the file structure without affecting the application’s ability to access the data. Because the file system application programs are affected by changes in the file structure, they exhibit structural dependence.
6. What is the role of a DBMS and what are its advantages and disadvantages? It serves as the intermediary between the user and the database and the database structure itself is stored as a collection of files and the only way to access the data in those files is through the DBMS. Advantages: Improved data sharing, improved data security, minimized data inconsistency, improved data access, improved decision-making, increased end-user productivity. Disadvantages: Increased costs, management complexity, maintaining currency, vendor dependence, frequent upgrade/replacement cycles.
7. List and describe the different types of databases.
• Single-user database supports only one user at a time • Multi-user database supports multiple users at the same time • Enterprise databases used by the entire organization • Centralized database supports data located at a single site. • Distributed database supports data distributed across several different sites • General-purpose databases contain a wide variety of data used in multi disciplines eg. Census and demographic data • Discipline-specific databases contain data focused on a specific subject area. • Operation database also known as Online transactional processing (OLTP), transactional or production database supports a company’s day-to-day operations. • Analytical databases focuses primarily on storing historical data and business metrics used exclusively for tactical or strategic decision making. It consists of a Data warehouse is a specialized database that stores data in a format optimized for decision support and an Online analytical processing (OLAP) is a set of tools that work together to provide an advanced data analysis environment for retrieving, processing and modeling data fro m the data warehouse. Business intelligence describes a comprehensive approach to capture and process business data. 8. What are the main components of a database system?
Hardware software, People, procedures and Data.
9. What are metadata?
Data about data
10. Explain why database design is important?
Database design refers to the activities that focus on the design of the database structure that will be used to store and manage end-user data. A database that meets all user requirements does not just happen: its structure must be designed carefully. In fact, a database design is such a crucial aspect of working with databases.
11. What are the potential costs of implementing a database system? Sophisticated hardware and software, trained personnel training, licensingm and regulation compliance costs vendor dependence – vendors are less likely to offer pricing point advantages to existing customer and updating of hardware and software; additional training
12. Use examples to compare and contrast unstructured and structure data. Which type is more prevalent in a typical business environment? Unstructured data are data that exist in their original (raw) state, that is, in the format which they were collected and does not lend itself to the processing that yields information. Structured data are the result of formatting unstructured data to facilitate storage, use and the generation of information. An invoice. If one were to take an invoice and simply scan it into a graphic, it would be unstructured data. In contrast, if it were processed and put into a database (subsequently becomming structured data), employees could eventually find the monthly averages, amount owed, etc. from various invoices. While both are prevelant, I would think semistructed data would be the most common in a typical business. Some data is stored but not processed (unstructured data such as memos), and some others are stored in databases (such as invoices) but most data are only processed to a certain extent that is displayed in a prearranged format but not able to yield all of the information contained within.
13. What are some basic database functions that a spreadsheet cannot perform? spreadsheets do not support basic functionality such as: support for self-documentation through metadata enforcement of data types or domains to ensure consistency of data within a column, defined relationships among tables, or contraints to ensure consistency of data across related tables.
14. What common problems does a collection of spreadsheets created by end users share wit hthe typical file system? Common problems with using both a collection of spreadsheets created by end users and the typical file system include: lengthy development times, difficulty of getting quick answers,, complex system administration, lack of security and limited data sharing, extensive programming
15. Explain the significance of the loss of direct, hands-on access to business data that end users experienced with the advent of computerized data repositories. The loss of direct, hands on access to business data to end-users was significant because it gave them the tools to convert their data into the information they needed and manipulating the company data that would allow them to create new information. However, it seperated end-users from data. While this increased security, prevented redundancy and the such, it also created a delay in which the end-user could request information from the data and when it was delivered by the DP.
Chapter 2: Data Models
• A data model is an abstraction of a complex real-world data environment. Database designers use data models to communicate with programmers and end users. The basic data-modelling componenets are entities, attributes, relationships and constraints. Business rules are used to indentify and define the basic modelling components within a specific real-world environment. • The hierarchal and network data models were early models that are no longer used, but some of the concepts are found in current data models. • The relational model is the cureent database implementation standard. In the relational model, the end user perceives the data as being stored in tables. Tables are related to each other by means of common values in common attributes. The entity relationship (ER) model is a popular graphical tool for data modelling that complements the relational model.
The ER model allows database designers to visually present different views of the data – as seen by database designers, programmers, and end users – and to integrate the data into a common framework. • The object-oriented data model (OODM) uses objects as the basic modelling structure. Like the relational model’s entity, an object is described by its factual content. Unlike an entity, however, the object also includes information about relationships between the facts, as well as relationships with other objects, thus giving its data more meaning. • The relational model has adopted many object-oriented (OO) extensions to become the extended relational data model (ERDM). Object-relational database management systems (O/R DBMS) were developed to implement the ERDM. At this point, the OODM is largely used in specialized engineering and scientific applications, while the ERDM is primarily geated to business applications.
NoSQL databases are a new generation of databases that do not use the relational model and are geared to support the very specific needs of Big Data organizations. NoSQL databasesses offer distributed data stores that provide high scalability, availability, and fault tolerance by sacrificing data consistency and shifting the burden of maintaining relationships and data integrity to the program code. • Data modeling requirements are a function of different data views (global vs. local) and the level of data abstraction. The American national standards institute standards planning and requirements committee (ANSI/SPARC) describes three levels of data abstraction: external, conceptual and internal. The fourth and lowest level of data abstraction, called the physical level, is concerned exclusively with physical storage methods.
1. Discuss the importance of data models.
Data model is a reltively simple representation, usually graphical, of more complex real-world data structures. Data models are a great communication toold because they facilitate interaction and communication between the designers, programmers and end users. IN essence it does not allow one party’s bias toward a certain view of a data (what they consider to be most important) to take hold.
2. What is a business rule, and what is its purpose in data modeling? A business rule is a brief, precise and unambiguous description of a policy, procedure or principle within a specific organization. They are important in data modeling because they set the stage for proper identification of entities, attributes, relationships and constraints.
3. How do you translate business rules into data model components? You translate business rules into data model components by following basic principles: A noun in a business rule will translate into an entity in the model and a verb (active or passive) associating nouns will translate into a relationship among the entities.
4. What languages emerged to standardize the basic network model, and why was such standardization important to users and designers? Data manipulation language (DML) defines the environment in which data can be managed and is used to work with the data in the database. Data definition language (DDL) enables the database administrator to define the schema components. They both emerged to standardize the basic data model. This standardization was important to both users and designers because it allowed for the conception of the schema and subschema. Schema is the conceptual organization of the entire database as viewed by the database administrator and subscema defines the portion of the database “seen” by the application programs that actually produced the desired information from the data within the database.
5. Describe the basic features of the relational data model and discuss their importance to the end user and the designer. The basic feature of the relational data model include: Hierarchal and network DBMS systems. The importance of the relational model was essentially that its simplicity set the stage for genuine database revolution.
6. Explain how the entity relationship (ER) model helped produce a more structured relational database design environment. The ER model helped produce a more structured relational database design environment because it allowed designers to visually see entities, their attributes and the relationships between entities. 7. Consider the scenario described by a statement “A customer can make many payments, but each payment is made by only one customer.” Use this scenario as the basis for entity relationship diagram (ERD) representation. 1:M
8. Why is an object said to have greater semantic content than an entity? An object is described by its factual content and also includes information about relationships between the facts within the object as well as information about its relation to other objects. Entities on the other hand, stop at being described by its factual content. The term semantic indicates meaning, thus an object obviously has more semantic content since it contains more information.
9. What is the difference between an object and a class in the object-oriented data model (OODM)? In the OODM, an object contains both data and their relationships. Meanwhile, a class is a group of objects that share similar objects with shared structure (attributes) and behavior (methods).
10. What is an ERDM and what role does it play in the modern (production) database environment? Extended relational data model (ERDM) adds many of the OO model’s features within the inherently simpler relational database structure.
11. What is a relationship and what types of relationships exist? Relationships describe associations among data. Most relationships describe associations between two entities. When the basic data model were introduced, three types of data relationships were illustrated: 1:M, M:N and 1:1.
12. What is a table and what role does it play in the relational model? The relational model’s foundation is a mathematical concept known as a relation. To avoid the complexity of abstract mathematical theory, you can think of a relation, called table, as a matrix composed of intersecting rows and columns. Each row in a relation is called a tuple. Each column represents an attribute. The relational model also describes a precise set of data manipulation constructs based on advanced mathematical concepts.
13. What is a relational diagram?
A relational diagram is a representation of the relational database’s entities, the attributes within those entities, and the relationships between those entities.
14. What is connectivity?
The ER model uses the term connectivity to label the relationship types.
15. What is sparse data?
A case in which the number of table attributes is very large but the number of actual data instances is low.
16. Define and describe the basic characteristics of a NoSQL database NoSQL is a new generation of database management systems that is not based on the traditional relational database model. Characteristics include: Not based on relational model, supports distributed database architectures, provides high scalability, high availability and fault tolerance, supports very large amounts of sparse data and geared toward performance rather than transaction consistency.
17. What is logical independence and physical independence? Logical independence is when you can change the internal model without affecting the conceptual model. Physical independence is when you can change the physical model without affecting the internal model.
Chapter 3: The relational database model
• Tables are the basic building blocks of a relational database. A grouping of related entities, known as an entity set is stored in a table. Conceptually speaking, the relational table is composed of intersecting rows (tuples) and columns. Each row represents a single entity and each column represents the characteristics (attributes) of the entities. • Keys are central to the use of relational tables. Keys define functional dependencies, that is, other attributes are dependent on the key and can therefore be found if the key value is known. A key can be classified as a super key, a candidate key, a primary key and a secondary key and a foreign key. • Each table row must have a primary key. The primary key is an attribute or a combination of attributes that uniquely identifies all remaining attributes found in any given row. Because a primary key must be unique, no null values are allowed if entity integrity is to be maintained. • Although tables are independent, they can be linked by common attributes.
Thus, the primary key of one table can appear as the foreign key in another table to which it is linked. Referential integrity dictates that the foreign key must contain values that match the primary key in the related table or must contain nulls. • The relational mode supports relational algebra functions: SELECT, PROJECT and DIVIDE. A relational database performs much of the data manipulation work to house a data dictionary for your database. Each time you create a new table within the database, the RDBMS updates the data dictionary, thereby providing database documentation. • Once you know the basics of relational database, you can concentrate on design. Good design begins by identifying appropriate entities and their attributes and then the relationships among the entities. Those relationships (1:1, 1:M & M:N) can be presented using ERDs. The use of ERDs allows you to create and evaluate simple logical design. The 1:M relationship is most easily incorporated in a good design; just make sure that the primary key of the “1” is included in the table of the “many”.
1. What is the difference between a database and a table? A table is perceived as a two-dimensional structure composed of rows and columns, it is also called a relation. Where as, a database is more so a 3 dimensional structure that consists of many of these relations “tables.
2. What does it mean to say that a database displays both entity integrity and referential integrity? Referential integrity means the condition in which every reference to an entity instance by another entity instance is valid. Entity integrity is an integrity rule which states that every table must have a primary key and that the column or columns chosen to be the primary key should be unique and not null.
3. Why are entity integrity and referential integrity important in a database? They ensure there are no data redundancy and data is not null.
4. What are the requirements that two relations must satisfy to be considered union-compatible? When two or more tables share the same number of columns and when their corresponding columns share the same or compatible domains, they are said to be union-compatible. 5. Which relational algebra operators can be applied to a pair of tables that are not union-compatible? A natural join: PRODUCT, SELECT, PROJECT
6. Explain why the data dictionary is sometimes called “the database designer’s database”. Because it records the design decisions about tables and their structures. 7. A database user manually notes that “The file contains two hundred records, each record containing nine fields. Use appropriate relational database terminology to “translate” that statement. The entity contains two hundred attributes, each attribute contains
8. A natural join links tables by selecting only the rows with common values in their common attribute(s). An equijoin links tables on the basis of an equally condition that compares specified columns of each table. An outer join matched pairs would be retained and any unmatched values in the other table would be left null.
Chapter 4: entity relationship (ER) Modeling
• The ERM uses ERDs to represent the conceptual database as viewed by the en user. The ERM’s main components are entities, relationships and attributes. The ERD includes connectivity and cardinality notations and can also show relationship strength, relationship participation (optional or mandatory), and the degree of relationship (such as unary, binary or ternary). • Connectivity describes the relationship classification (1:1, 1:M, or M:N). Cardinality expresses the specific number of entity occurrences associated with an occurrence of a related entity. Connectivities and cardinalities are usually based on business rules. • In the ERM, an M:N relationship is valid at the conceptual level. However, when implementing the ERM in a relational database, the M:N relationship must be mapped to a set of 1:M relationships through a composite entity. • Unified Modeling Language (UML) class diagrams are used to represent the static data structures in a data model. The symbols used I the UML class and ER diagrams are very similar.
The UML class diagrams can be used to depict data models at the conceptual or implementation abstraction levels. • Database designers, no matter how well they can produce designs that conform to all applicable modeling conversations are often forced to make design compromises. Those compromises are required when end users have vital transaction-speed and information requirements that prevent the use of “perfect” modeling logic and adherence to all modeling conventions. Therefore, database designers must use their professional judgment to determine how and to what extent the modeling conventions are subject to modification. To ensure that their professional judgments are sound, database designers must have detailed and in-depth knowledge of data-modeling conventions. It is also important to document the design process from beginning to end, which helps keep the design process on track and allows for easy modification in the future.