Review universal data models and discuss how these are being used more widely today. Does a data modeling project using a packaged data model require less or greater skill than a project not using a packaged data model?

2. A data modelling project using a packaged data model REQUIRES A GREATER SKILL than a project not using a packaged data model.

Explanation:

1a. Review of universal models:

A data model is an abstract model that organizes elements of data and standardizes how they relate to one another and to the properties of real world entities. It has become the standard approach used towards designing databases.

A universal data model is a template data model that can be reused as a starting point or a building block to jump-start development of a data modelling project, industry specific model, logical data models.

1b. Discuss how these are being used more widely today.

*Universal data models helps professional reduce development time, improve consistency and standardization while achieving high quality models.

*Higher quality: just as architects consider blue prints before constructing a building, one should also consider data before building an app. A data model helps define the problem, enabling one to consider different approaches and choose best ones.

*By properly modelling and organization's data, the database designer can eliminate data redundancies (needless repetitions) which are a key source for inaccurate information and ineffective systems.

2. Greater and advanced skills are adequate and required when data modelling project is done using packaged data model while fewer skills are required when data modelling is done without packaged data model.

A data modelling project using a packaged data model requires same amount skills as a project not using packaged data model, and in some cases it can also require more skills to work with data models. The main reason for this is that when a packaged data model is being used by project because the packaged data needs to be customized by data modeler to meet the project needs. Therefore, a data modeler using a packaged data modeler needs more advanced skills to work with.

Explanation:

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