Database management systems
Main functions of the database management system. Creation of a conceptual data model that reflects the structure of information that should be stored in the data bank. The peculiarity of the design of spreadsheets. Use the program to store evidence.
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1. Terminology and overview
2. Design and modeling
3. Database and Spreadsheet
One of the reasons companies are hesitant to use Microsoft Access is a lack of understanding of the difference between a spreadsheet and a database. This leads many people to believe that tracking client information, purchase orders, and project details in a spreadsheet is adequate for their needs. The end result is that it is difficult to maintain configuration control, files are lost to corruption, and employees accidently overwrite pertinent information.
With a little knowledge about the power and many uses of a database, it is easier for small businesses to see when a spreadsheet is enough for a job and when a database needs to be created.
It is important to have a basic understanding of what a database is. Most people have accessed databases before, like the ones in the public library, but simply using them does not make it clear how spreadsheets and databases are different. Spending a few minutes learning about databases will help make the comparison clearer.
1. Terminology and overview
Formally, a "database" refers to a set of related data and the way it is organized. Access to this data is usually provided by a "database management system" (DBMS) consisting of an integrated set of computer software that allows users to interact with one or more databases and provides access to all of the data contained in the database (although restrictions may exist that limit access to particular data). The DBMS provides various functions that allow entry, storage and retrieval of large quantities of information and provides ways to manage how that information is organized.
Because of the close relationship between them, the term "database" is often used casually to refer to both a database and the DBMS used to manipulate it.
Outside the world of professional information technology, the term database is often used to refer to any collection of related data (such as a spreadsheet or a card index). This article is concerned only with databases where the size and usage requirements necessitate use of a database management system.
Existing DBMSs provide various functions that allow management of a database and its data which can be classified into four main functional groups:
· Data definition - Creation, modification and removal of definitions that define the organization of the data.
· Update - Insertion, modification, and deletion of the actual data.
· Retrieval - Providing information in a form directly usable or for further processing by other applications. The retrieved data may be made available in a form basically the same as it is stored in the database or in a new form obtained by altering or combining existing data from the database.
· Administration - Registering and monitoring users, enforcing data security, monitoring performance, maintaining data integrity, dealing with concurrency control, and recovering information that has been corrupted by some event such as an unexpected system failure.
Both a database and its DBMS conform to the principles of a particular database model. "Database system" refers collectively to the database model, database management system, and database.
Physically, database servers are dedicated computers that hold the actual databases and run only the DBMS and related software. Database servers are usually multiprocessor computers, with generous memory and RAID disk arrays used for stable storage. RAID is used for recovery of data if any of the disks fail. Hardware database accelerators, connected to one or more servers via a high-speed channel, are also used in large volume transaction processing environments. DBMSs are found at the heart of most database applications. DBMSs may be built around a custom multitasking kernel with built-in networking support, but modern DBMSs typically rely on a standard operating system to provide these functions.
Since DBMSs comprise a significant market, computer and storage vendors often take into account DBMS requirements in their own development plans.
Databases and DBMSs can be categorized according to the database model(s) that they support (such as relational or XML), the type(s) of computer they run on (from a server cluster to a mobile phone), the query language(s) used to access the database (such as SQL or XQuery), and their internal engineering, which affects performance, scalability, resilience, and security.
2. Design and modeling
Main article: Database design
The first task of a database designer is to produce a conceptual data model that reflects the structure of the information to be held in the database. A common approach to this is to develop an entity-relationship model, often with the aid of drawing tools. Another popular approach is the Unified Modeling Language. A successful data model will accurately reflect the possible state of the external world being modeled: for example, if people can have more than one phone number, it will allow this information to be captured. Designing a good conceptual data model requires a good understanding of the application domain; it typically involves asking deep questions about the things of interest to an organization, like "can a customer also be a supplier?", or "if a product is sold with two different forms of packaging, are those the same product or different products?", or "if a plane flies from New York to Dubai via Frankfurt, is that one flight or two (or maybe even three)?". The answers to these questions establish definitions of the terminology used for entities (customers, products, flights, flight segments) and their relationships and attributes.
Producing the conceptual data model sometimes involves input from business processes, or the analysis of workflow in the organization. This can help to establish what information is needed in the database, and what can be left out. For example, it can help when deciding whether the database needs to hold historic data as well as current data. database conceptual information spreadsheet
Having produced a conceptual data model that users are happy with, the next stage is to translate this into a schema that implements the relevant data structures within the database. This process is often called logical database design, and the output is a logical data model expressed in the form of a schema. Whereas the conceptual data model is (in theory at least) independent of the choice of database technology, the logical data model will be expressed in terms of a particular database model supported by the chosen DBMS. (The terms data model and database model are often used interchangeably, but in this article we use data model for the design of a specific database, and database model for the modelling notation used to express that design.)
The most popular database model for general-purpose databases is the relational model, or more precisely, the relational model as represented by the SQL language. The process of creating a logical database design using this model uses a methodical approach known as normalization. The goal of normalization is to ensure that each elementary "fact" is only recorded in one place, so that insertions, updates, and deletions automatically maintain consistency.
The final stage of database design is to make the decisions that affect performance, scalability, recovery, security, and the like, which depend on the particular DBMS. This is often called physical database design, and the output is the physical data model. A key goal during this stage is data independence, meaning that the decisions made for performance optimization purposes should be invisible to end-users and applications. There are two types of data independence: Physical data independence and logical data independence. Physical design is driven mainly by performance requirements, and requires a good knowledge of the expected workload and access patterns, and a deep understanding of the features offered by the chosen DBMS.
Another aspect of physical database design is security. It involves both defining access control to database objects as well as defining security levels and methods for the data itself.
Main article: Database model
Collage of five types of database models
A database model is a type of data model that determines the logical structure of a database and fundamentally determines in which manner data can be stored, organized, and manipulated. The most popular example of a database model is the relational model (or the SQL approximation of relational), which uses a table-based format.
Common logical data models for databases include:
· Navigational databases
· Hierarchical database model
· Network model
· Graph database
· Relational model
· Entity-relationship model
· Enhanced entity-relationship model
· Object model
· Document model
· Entity-attribute-value model
· Star schema
An object-relational database combines the two related structures.
Physical data models include:
· Inverted index
· Flat file
Other models include:
· Associative model
· Multidimensional model
· Array model
· Multivalue model
Specialized models are optimized for particular types of data:
· XML database
· Semantic model
· Content store
· Event store
· Time series model
3. Database and Spreadsheet
Beforethe computer, bookkeepers, record keepers, and accountants used the paper andpencil method along with a ledger or record book containing worksheets. Information and records were stored by hand and financial records werecalculated manually and entered in to the worksheets. Ledgers used rowsand columns that people learned could be used not only for financial records,but also for things like scheduling, inventory tracking, and employeeinformation.
Thedawn of the computer age brought applications that could store information,perform complex calculations, and provide a printed output. This conceptvirtually revolutionized the use of the computer early on. The first application with any real power was Visi-Calc, which laterbecame Lotus 1-2-3. Visi-Calc alone gave businesses a serious enough reason tojustify investing in computers for the office and is actually credited withkeeping Apple computers in business. Theadvantages of using a spreadsheet application rather than paper and pencil werenumerous - not the least of which was that when data was changed, totals andother formulas were automatically recalculated, saving both time and headache. However, Visi-Calc lacked functionality in the way of tools available to theuser.
Currently, Microsoft Excel,along with Lotus 1-2-3, commands most of the market for spreadsheetapplications. Tools have evolved tremendously since that first Visi-Calcprogram. Now users have help available at a click of their mouse along with toolssuch as complex formula support, formula and function builders, sorting andfiltering, scenario managers (for "What-if" analysis), charts andgraphs, and extended data formatting tools.
Adatabase organizes information on a particular subject for retrieval. Databases utilize one or more tables of information entered bythe user to retrieve data for a variety of purposes. Data can be retrievedthrough methods such as asking questions of the data (querying), sorting orfiltering, and pulling information into a formatted report, like an invoice, that canbe printed. Although the tables look similar to spreadsheets, the tablesare used to store raw data. In other words, there is no need to format theinformation in a database table. Reports generated from the data in thetables are where you would want specific formatting. Information in aspreadsheet is formatted in the actual spreadsheet, and that makes data entry abit more tedious.
Databasesalso involve the use of records to structure the tables. A recordcan contain any number of fields. Comparing this to a common phonebook, a record would be an entire entry for one individual, and a field would beeach separate part of the entire entry - like the individual's phonenumber. Reports organize the information in an understandable way and cancombine data by performing complex calculations. Databases can also easilymanage a large amount of information and better maintain data integrity. Forthese reasons, databases are much more powerful and manageable when handling a large amount of information related to a particulartopic.
The downfall? The downfall is that most database programs arenot as easy to learn and use as most spreadsheet applications and are not as easy tomake structural changes in once queries, forms, and reports are developed. One must have knowledge of the best way tostructure the information into one or more tables before any tables are used todevelop the means of retrieving the information. The reason for this, is that once saved queries, forms,and reports are based on the table(s), any changes in the table(s)structure (like deleting/changing field names) may cause errors in all theobjects based on the changed table(s). So, it is important that thedeveloper of the database has a clear vision of all types of information thatwould need to be included and how to organize it. This, combined with aninterface that's not usually as intuitive as a spreadsheet, sometimesintimidates would-be database users.
AnExample of Database vs. Spreadsheet Use
Nowthat you are a bit more familiar with the purposes of the two, how do youdetermine which is best for your data? Most businesses find that using bothworks best. Take a look at the following simple example:
CompanyABC needed a method of storing data related to customer sales where they couldprint invoices and be able to track orders and customer contactinformation. They also needed to be able to quickly calculate what anincrease or decrease in product prices and/or sales would do to their overallrevenue generation along with a way to analyze trends.
First,they developed an Access database to store all of their customer information andordering data. They included the following tables: Contact Information,Products, and Orders. From this they used the tables and also createdqueries of the table data on which to base reports, like invoices. They alsocreated easy to use forms for inputting data and a user-friendly switchboard foreasy navigation. This gave them an efficient way to enter data, storedata, and generate information for invoices, sales by product, sales bycustomer, and so on.
Second,they used Excel spreadsheets to quickly calculate what changes in price andsales would do to their revenue by creating various scenarios. They couldalso use their sales information in Excel to analyze trends by generating chartsand graphs. This gave them an easy way to analyze their data and trends ina tool with understandable and meaningful formats.
Whatcan we gain from this example? As a general rule of thumb, databasesshould be used for data storage and spreadsheets should be used to analyze data.
Ifyou currently use a spreadsheet to store data, ask yourself the followingquestions:
· Do changes made in one spreadsheet force you to make changes in others?
· Is the sheer amount of data unmanageable or becoming unmanageable?
· Do you have several spreadsheets that contain related information (such as separate sheets with sales for branches in Los Angeles, Chicago, and Houston)?
· Can you see all relevant data on one screen, or do you have to keep scrolling to find information?
· Are several people accessing the data at the same time?
· Do you have a difficult time viewing specific data sets that you want?
If you answered yes to at least two of thequestions, you should think about moving your information to a database application.
Use a databaseif...
· the information is a large amount that would become unmanageable in spreadsheet form and is related to a particular subject.
· you want to maintain records for ongoing use.
· the information is subject to many changes (change of address, pricing changes, etc.).
· you want to generate reports based on the information.
Use a spreadsheet if...
· you want to crunch numbers and perform automatic calculations.
· you want to track a simple list of data.
· you want to easily create charts and graphs of your data.
· you want to create "What-if" scenarios.
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