Master File

Masters file

Definition of: A collection of records pertaining to one of the main subjects of an information system, such as customers, employees, products and vendors. Master files contain descriptive data, such as name and address, as well as summary information, such as amount due and year-to-date sales. Following are the kinds of fields that make up a typical master record in a business information system. There can be many more fields depending on the organization. The "key" fields below are the ones that are generally indexed for matching against the transaction records as well as fast retrieval for queries. The account number is usually the primary key, but name may also be primary. There can be secondary indexes; for example, in an inverted file structure, almost all the fields could be indexed. EMPLOYEE MASTER RECORD key Employee account number key Name (last) Name (first) Address, city, state, zip Hire date Birth date Title Job class Pay rate Year-to-date gross pay CUSTOMER MASTER RECORD key Customer account number key Name Bill-to address, city, state, zip Ship-to address, city, state, zip Credit limit Date of first order Sales-to-date Balance due VENDOR MASTER RECORD key Vendor account number key Name Address, city, state, zip Terms Quality rating Shipping method PRODUCT MASTER RECORD key Product number key Name Description Quantity on hand Location Primary vendor Secondary vendor

Definition of:

Transactions file

A collection of transaction records. The data in transaction files is used to update the master files, which contain the data about the subjects of the organization (customers, employees, vendors, etc.). Transaction files also serve as audit trails and history for the organization. Where before they were transferred to offline storage after some period of time, they are increasingly being kept online for routine analyses. Following are the kinds of fields that make up a typical transaction record in a business information system. There can be many more fields depending on the organization. The "key" fields below are the ones that are generally indexed for fast matching against the master record. The account number is usually the primary key, but name may also be used as a primary key. EMPLOYEE PAYROLL RECORD key Employee account number Today's date Hours worked ORDER RECORD key Customer account number Today's date Quantity Product number PAYMENT RECORD key Customer number Today's date Invoice number Amount paid Check number PURCHASE ORDER key Purchase order number Today's date Department Authorizing agent Vendor account number Quantity Product number Due date Total cost WAREHOUSE RECEIPT key Purchase order number key Invoice number Today's date Quantity Product number

Data processing: Data processing is any computer process that converts data into information. The processing is usually assumed to be automated and running on an a mainframe, minicomputer, microcomputer, or personal computer. Because data are most useful when well-presented and actually informative, data-processing systems are often referred to as information systems to emphasize their practicality. Nevertheless, both terms are roughly synonymous, performing similar conversions; data-processing systems typically manipulate raw data into information, and likewise information systems typically take raw data as input to produce information as output. To better market their profession, a computer programmer or a systems analyst that might once have referred, such as during the 1970s, to the computer systems that they produce as data-processing systems more often than not nowadays refers to the computer systems that they produce by some other term that includes the word information, such as information systems, information technology systems, or management information systems. In the context of data processing, data are defined as numbers or characters that represent measurements from the real world. A single datum is a single measurement from the real world. Measured information is then algorithmically derived and/or logically deduced and/or statistically calculated from multiple data. (evidence). Information is defined as either a meaningful answer to a query or a meaningful stimulus that can cascade into further queries. More generally, the term data processing can apply to any process that converts data from one format to another, although data conversion would be the more logical and correct term. From this perspective, data processing becomes the process of converting information into data and also the converting of data back into information. The distinction is that conversion doesn't require a question (query) to be answered. For example, information in the form of a string of characters forming a sentence in English is converted or encoded from a keyboard's key-presses as represented by hardwareoriented integer codes into ASCII integer codes after which it may be more easily processed by a computer—not as merely raw, amorphous integer data, but as a meaningful character in a natural language's set of graphemes—and finally converted or decoded to be displayed as characters, represented by a font on the computer display. In that example we can see the stage-by-stage conversion of the presence of and then absence of electrical conductivity in the key-press and subsequent release at the keyboard from raw substantially-meaningless integer hardware-oriented data to evermoremeaningful information as the processing proceeds toward the human being. Conversely, that simple example for pedagogical purposes here is usually described as an embedded system (for the software resident in the keyboard itself) or as

(operating-)systems programming, because the information is derived from a hardware interface and may involve overt control of the hardware through that interface by an operating system. Typically control of hardware by a device driver manipulating ASIC or FPGA registers is not viewed as part of data processing proper or information systems proper, but rather as the domain of embedded systems or (operating-)systems programming. Instead, perhaps a more conventional example of the established practice of using the term data processing is that a business has collected numerous data concerning an aspect of its operations and that this multitude of data must be presented in meaningful, easy-to-access presentations for the managers who must then use that information to increase revenue or to decrease cost. That conversion and presentation of data as information is typically performed by a data-processing application. When the domain from which the data are harvested is a science or an engineering, data processing and information systems are considered too broad of terms and the more specialized term data analysis is typically used, focusing on the highly-specialized and highly-accurate algorithmic derivations and statistical calculations that are less often observed in the typical general business environment. This divergence of culture is exhibited in the typical numerical representations used in data processing versus numerical; data processing's measurements are typically represented by integers or by fixed-point or binary-coded decimal representations of real numbers whereas the majority of data analysis's measurements are often represented by floating-point representation of real numbers. Practically all naturally occurring processes can be viewed as examples of data processing systems where "real world" information in the form of pressure, light, etc. are converted by human observers into electrical signals in the nervous system as the senses we recognise as touch, sound, and vision. Even the interaction of non-living systems may be viewed in this way as rudimentary information processing systems. Conventional usage of the terms data processing and information systems restricts their use to refer to the algorithmic derivations, logical deductions, and statistical calculations that recur perennially in general business environments, rather than in the more expansive sense of all conversions of real-world measurements into real-world information in, say, an organic biological system or even a scientific or engineering system.

Database design Database design is the process of producing a detailed data model of a database. This model contains all the needed logical and physical design choices and physical storage parameters needed to generate a design in a Data Definition Language, which can then be used to create a database. A fully attributed data model contains detailed attributes for each entity. The term database design can be used to describe many different parts of the design of an overall database system. Principally, and most correctly, it can be thought of as the logical design of the base data structures used to store the data - in the relational model these are the tables and views. However, the term database design could also be used to apply to the overall process of designing, not just the base data structures, but also the forms and queries used as part of the overall database application within the Database Management System or DBMS. Design process The process of doing database design generally consists of a number of steps which will be carried out by the database designer. Not all of these steps will be necessary in all cases, but most usually, the designer must: • • •

Determine the data to be stored in the database Determine the relationships between the different data elements Superimpose a logical structure upon the data on the basis of these relationships.

Within the relational model the final step can generally be broken down into two further steps, that of determining the grouping of information within the system, generally determining what are the basic objects about which information is being stored, and then determining the relationships between these group of information, or objects. The tree structure of data may enforce hierarchical model organization, with parent-child relationship table.

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Determining data to be stored In a majority of cases, the person who is doing the design of a database is a person with expertise in the area of database design, rather than expertise in the domain from which the data to be stored is drawn e.g. financial information, biological information etc. Therefore the data to be stored in the database must be determined in cooperation with a

person who does have expertise in that domain, and who is aware of what data must be stored within the system. This process is one which is generally considered part of requirements analysis, and requires skill on the part of the database designer to elicit the needed information from those with the domain knowledge. This is because those with the necessary domain knowledge frequently cannot express clearly what their system requirements for the database are as they are unaccustomed to thinking in terms of the discrete data elements which must be stored. [edit]

Conceptual schema Once a database designer is aware of the data which is to be stored within the database, he must then determine how the various pieces of that data relate to one another. When performing this step, the designer is generally looking out for the dependencies in the data, where one piece of information is dependent upon another i.e. when one piece of information changes, the other will also. For example, in a list of names and addresses, the address is dependent upon the name, because if the name is different then the associated address is different too. However, the inverse is not necessarily true,i.e. when the address changes name may be the same. For example, assuming the normal situation where two people can have the same address, but one person cannot have two addresses. (NOTE: A common misconception is that the relational model is so called because of the stating of relationships between data elements therein. This is not true. The relational model is so named such because it is based upon the mathematical structures known as relations.) [edit]

Logically structuring data Once the relationships and dependencies amongst the various pieces of information have been determined, it is possible to arrange the data into a logical structure which can then be mapped into the storage objects with the database management system. In the case of relational databases the storage objects are tables which store data in rows and columns. The way this mapping is generally performed is such that each set of related data which depends upon a single object, whether real or abstract, is placed in a table. Relationships between these dependent objects is then stored as links between the various objects.