Database assignment Example | Topics and Well Written Essays - 2500 words

Database - Assignment Example This whole function has brought a breakthrough in the fields of re-engineering, modeling and construction. Considering a data model, it is a flowchart or diagram that brings out the specific relationships present within data values. Effective data management requires that relationships between data be accurately determined and represented. It is therefore a process that should not be ignored. Data models which are efficiently designed allow for identification of errors and misconceptions that might be present in a data range. Data modeling has been given different approaches due to its importance. According to Burbank, these approaches include the following: Physical data modeling This type of modeling makes use of the current facilities and specific constraints of a particular database management system. It provides database specific kind of representation of a data model. Conceptual data modeling This kind of data modeling makes use of concepts and their specific relationships appl icable to databases. It explains the nature of a database using a series of assumptions and semantics. Logical data modeling This is a type of data modeling whereby specific data representations of a given company are explained using relationships and entities. Moreover, it is not dependent of any specific technology of data management. Enterprise data modeling In this modeling, graphical models are used to represent data in a company. This implies that outputs like XML Schemas (XSD) and Entity Relationship Diagrams (ERDs) are used to provide data model outputs. (Burbank, 2011) In an attempt to make data modeling more efficient and realistic, several data modeling software have been developed over the past few years. For instance, CA Erwin Data Modeler and Oracle Data Modeler are some of the modeling software that are now widely used all over the world. These two programs have made data modeling more efficient, faster and cheaper than using the conventional methods. This paper will provide deeper insight on both Erwin and Oracle data modeler tools. The two programs will also be compared and their key features and functionalities outlined. Overview of CA Erwin Data Modeler Erwin data modeler is a data modeling tool used to perform the same function by several companies and organizations. There are also several other companies that uses the same data modeler throughout the globe. This program was initially developed by a renowned software developer known as Logic Works. Platinum Technology later purchased it in 1998. In 1999, Computer Associates purchased Platinum and is the same company that directly markets it. As a modern data modeling software, Erwin support a wide variety of database design functions that encompasses the following: Data modeling Forward engineering (This involves the process of creating a specific physical database and database schema model while relying on the grounds of data model) Reverse engineering(Where data models are created in rega rds to a pre-existing model of data) These functions are applicable in Erwin for various relational database hierarchical structures that cover a wide variety of used databases (Burbank, 2011). Erwin can be used to perform data modeling for different types of databases like information systems, database transactional systems, data marts and several others. Erwin support various displays of diagrams drawn or structured from different perspectives. For instance, it allows for viewing and manipulation of

Campbell's targets growing make grocery shopping Case Study

Campbell's targets growing make grocery shopping - Case Study Example The role of classical conditioning also comes into play at this stage. The advertisement acts as a conditioned stimulus (role of shopping performed by men) and the target audience is exposed to this advertisement to elicit the conditioned response (men go out to shop). Table A reveals that both men and women tend to buy less variety so as to reduce the number of items purchased. In general, both genders do not make a list of the specific brands they intend to buy. More than half; 56% men and 51% women list only the categories they have to buy. Neither men nor women choose products because they fetch discounts on loyalty cards. However 33% men and 36% women buy store brands to save money. A vast majority of shoppers; 73% men and 78 % women rely on previous usage and experience while selecting brands. Very few shoppers base their choice on product label and packaging. More women (43%) tend to shop for ‘all-purpose’ cleaning supplies than men (31%). Women also have a tendency to look at a store circular (59%) and make additional unplanned purchases (54%). On the other hand, 49% of the males go through a store circular and only 44% make unplanned purchases. List making behavior, especially making list based on ingredients needed for recipes, elicits pretty divergent behavior between the two genders. 46% of the women make such lists as against 33% males. A lot of women (52%) select brands on the basis of coupons picked up from home as compared to 40% of the males who base their purchase decision on this parameter. If a product is requested by a household member, 44% of women pick it up while only 30% of the males do so. The aforesaid discussion suggests that marketers of packaged-goods grocery items should have their products and brands listed on the circulars in the stores since 49% of the men tend to read such circulars. The advertising objective should be to make the brand synonymous with the product category since 56% of the men mention only