Event-entity-relationship modeling in data warehouse environments

Bækgaard, Lars

doi:10.1145/319757.319779

Cited by 11 publications

(12 citation statements)

References 10 publications

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“…To make the model starER, we begin by gathering user requirements for modeling DW. Another example of work based on the ER model that of [10] who presents a design language called EVent-Entity-Relationship (EVER). The structure of the information at EVER is under the shape of entities and events.…”

Section: State Of Artmentioning

confidence: 99%

A Data Warehouse Assistant Design System Based on Clover Model

Arfaoui¹,

Akaichi²

2010

IJDMS

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Section: State Of Artmentioning

confidence: 99%

A Data Warehouse Assistant Design System Based on Clover Model

Arfaoui¹,

Akaichi²

2010

IJDMS

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“…However, while analyzing the user requirements, starER model reveals a set of new modeling concepts that need to be handled with well-known models and schema resulting in the extension with new constructs. EVER [13] is an entity-based model language based on an event concept that is suited for multi-dimensional modeling because measurement data often represents events in multidimensional databases. However, this language does not support specification of filtering predicates and aggregation functions.…”

Section: Related Workmentioning

confidence: 99%

Derivation of initial data warehouse structure by mapping operational database on transaction patterns

Khalfe¹,

Hyder²

2006

WIT Transactions on Information and Communication Technologies, Vol 36

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Data warehouses improve the quality of integrated information in the organization for decision-making. The data for the data warehouse comes from online transaction systems. Typically, an involved process of analysis precedes the actual design phase of a data warehouse [1]. The analysis process becomes more difficult because of the costs involved in hiring experienced staff and the privacy issues arising from the use of external consultants [2]. Peter Coad's transaction pattern [3] is a higher-level description of a generic business process (or a template) that has helped in the analysis and design of a wide range of business domains. Thesis of this paper is that the mapping of the operational databases on the transaction pattern facilitates the derivation of initial data warehouse structure. During the mapping process, the relationships, roles and attributes of the players defined by the transaction pattern help us in identifying the instances of the pattern in the database. Through these instances, we can then derive the initial data warehouse structure i.e. the attributes of the fact and dimension table(s). The data warehouse structure thus derived reduces the need for an extensive information analysis of the needs of the user and the dependency on the experienced personnel for data warehouse development. This paper proposes a three-step derivation methodology that is illustrated using a case study of an organization's operational database.

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“…The ER extension approach uses an ER model as input and extends it with additional constructs such that it can be mapped to the corresponding multidimensional model. Some examples of this approach are the Multidimensional Entity Relationship (ME/R) [10] , the Structured Entity Relationship Model (SERM) [11] and the Event-Entity-Relationship model (EVER) [12] .…”

Section: Conceptual Data Warehouse Designmentioning

confidence: 99%

A Transformation-oriented Methodology to Knowledge-based Conceptual Data Warehouse Design

Sitompul¹,

Noah²

2006

J. of Computer Science

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Applications of artificial intelligence (AI) technology in the form of knowledge-based systems within the context of database design have been extensively researched particularly to provide support within the conceptual design phase. However, a similar approach to the task of data warehouse design has yet to be seriously initiated. In this paper, we proposed a design methodology for conceptual data warehouse design called the transformation-oriented methodology, which transforms an Entity-Relationship (ER) model into a multidimensional model based on a series of transformation and analysis rules. The transformation-oriented methodology translates the ER model into a specification language model and transformed it into an initial problem domain model. A set of synthesis and diagnosis rules will then gradually transform the problem domain model into the multidimensional model. A prototype KB tool called the DWDesigner has been developed to implement the aforementioned methodology. The multidimensional model produces by the DWDesigner as output is presented in a graphical form for better visualization. Testing has been conducted to a number of design problems, such as university, business and hospital domains and consistent results have been achieved

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Event-entity-relationship modeling in data warehouse environments

Cited by 11 publications

References 10 publications

A Data Warehouse Assistant Design System Based on Clover Model

A Data Warehouse Assistant Design System Based on Clover Model

Derivation of initial data warehouse structure by mapping operational database on transaction patterns

A Transformation-oriented Methodology to Knowledge-based Conceptual Data Warehouse Design

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