Enterprise Data Modeling
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Enterprise Data Modeling
Enterprise data modelling or enterprise data modeling (EDM) is the practice of creating a graphical model of the data used by an enterprise or company. Typical outputs of this activity include an enterprise data model consisting of entity–relationship diagrams (ERDs), XML schemas (XSD), and an enterprise wide data dictionary. Overview Producing such a model allows for a business to get a 'helicopter' view of their enterprise. In EAI (enterprise application integration) an EDM allows data to be represented in a single idiom, enabling the use of a common syntax for the XML of services or operations and the physical data model for database schema creation. Data modeling tools for ERDs that also allow the user to create a data dictionary are usually used to aid in the development of an EDM. The implementation of an EDM is closely related to the issues of data governance Data governance is a term used on both a macro and a micro level. The former is a political concept and for ...
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Data Modeling
Data modeling in software engineering is the process of creating a data model for an information system by applying certain formal techniques. Overview Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations. Therefore, the process of data modeling involves professional data modelers working closely with business stakeholders, as well as potential users of the information system. There are three different types of data models produced while progressing from requirements to the actual database to be used for the information system.Simison, Graeme. C. & Witt, Graham. C. (2005). ''Data Modeling Essentials''. 3rd Edition. Morgan Kaufmann Publishers. The data requirements are initially recorded as a conceptual data model which is essentially a set of technology independent specifications about the data and is used to discuss initial requirements w ...
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Entity–relationship Model
An entity–relationship model (or ER model) describes interrelated things of interest in a specific domain of knowledge. A basic ER model is composed of entity types (which classify the things of interest) and specifies relationships that can exist between entities (instances of those entity types). In software engineering, an ER model is commonly formed to represent things a business needs to remember in order to perform business processes. Consequently, the ER model becomes an abstract data model, that defines a data or information structure which can be implemented in a database, typically a relational database. Entity–relationship modeling was developed for database and design by Peter Chen and published in a 1976 paper, with variants of the idea existing previously, but today it is commonly used for teaching students the basics of data base structure. Some ER models show super and subtype entities connected by generalization-specialization relationships, and an ER mode ...
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XML Schema (W3C)
XSD (XML Schema Definition), a recommendation of the World Wide Web Consortium ( W3C), specifies how to formally describe the elements in an Extensible Markup Language (XML) document. It can be used by programmers to verify each piece of item content in a document, to assure it adheres to the description of the element it is placed in. Like all XML schema languages, XSD can be used to express a set of rules to which an XML document must conform to be considered "valid" according to that schema. However, unlike most other schema languages, XSD was also designed with the intent that determination of a document's validity would produce a collection of information adhering to specific data types. Such a post-validation ''infoset'' can be useful in the development of XML document processing software. History XML Schema, published as a W3C recommendation in May 2001, is one of several XML schema languages. It was the first separate schema language for XML to achieve Recommendation s ...
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Data Dictionary
A data dictionary, or metadata repository, as defined in the ''IBM Dictionary of Computing'', is a "centralized repository of information about data such as meaning, relationships to other data, origin, usage, and format". ''Oracle'' defines it as a collection of tables with metadata. The term can have one of several closely related meanings pertaining to databases and database management systems (DBMS): * A document describing a database or collection of databases * An integral component of a DBMS that is required to determine its structure * A piece of middleware that extends or supplants the native data dictionary of a DBMS Documentation The terms ''data dictionary'' and ''data repository'' indicate a more general software utility than a catalogue. A ''catalogue'' is closely coupled with the DBMS software. It provides the information stored in it to the user and the DBA, but it is mainly accessed by the various software modules of the DBMS itself, such as DDL and DML compil ...
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Enterprise Application Integration
Enterprise application integration (EAI) is the use of software and computer systems' architectural principles to integrate a set of enterprise computer applications. Overview Enterprise application integration is an integration framework composed of a collection of technologies and services which form a middleware or "middleware framework" to enable integration of systems and applications across an enterprise. Many types of business software such as supply chain management applications, ERP systems, CRM applications for managing customers, business intelligence applications, payroll, and human resources systems typically cannot communicate with one another in order to share data or business rules. For this reason, such applications are sometimes referred to as islands of automation or information silos. This lack of communication leads to inefficiencies, wherein identical data are stored in multiple locations, or straightforward processes are unable to be automated. Enterp ...
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Data Governance
Data governance is a term used on both a macro and a micro level. The former is a political concept and forms part of international relations and Internet governance; the latter is a data management concept and forms part of corporate data governance. Macro level On the macro level, data governance refers to the governing of cross-border data flows by countries, and hence is more precisely called ''international data governance''. This new field consists of "norms, principles and rules governing various types of data." Micro level Here the focus is on an individual company. Here data governance is a data management concept concerning the capability that enables an organization to ensure that high data quality exists throughout the complete lifecycle of the data, and data controls are implemented that support business objectives. The key focus areas of data governance include availability, usability, consistency, data integrity and data security, standard compliance and inc ...
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