Information Management

Information Management

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Data modeling is the process of designing and validating a database that will be used to meet a business challenge. Data modelers use terms and symbols to identify and represent all of the data objects needed for a business operation to function.

Data models document entities (the persons, places and things [product, warehouse, partner etc.] an organization encounters in the course of business); the relationships of entities (e.g. employee WORKS in warehouse, MANAGES product and SHIPS to partner); and the attributes of entities (description, order number, address, account balance etc.).

There are three common types of data models. Conceptual data models define and describe business concepts at a high level for stakeholders addressing a business challenge. Logical data models are more detailed and describe entities, attributes and relationships in business terms. Physical data models define database objects, schema and the actual columns and tables of data that will be created in the database.

Like the blueprint of a building, a data model is the design specification for a database. Data modeling can be helped by off the shelf data models that can be adapted to a specific use. But data architects warn that without proper time and attention to "design before you build," organizations face inaccurate reporting, incorrect data, costly remediation and difficulty in meeting new user requirements.

Articles

Federated Data Models Can Accelerate Data Integration

Traditional approaches to data integration alone are no match for today’s increasingly complex information environments and accelerated business pace

Creating a Successful High-Level Data Model

The ten steps for completing the high-level data model

10 Easy Steps to Evaluate Data Modeling Tools

How do you sort through all of the conflicting messages to choose the tool that is right for you?

How High-Level Data Modeling Fits with Other Data Initiatives

A brief overview of the hot topics in data management and discussion of how a high-level data model can help with siloed projects or programs

Is Notation Important?

A picture is worth a thousand words, as they say, and it is important that the layout and formatting of your high-level data model is intuitive and easy to understand

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The Qualified Data Modeler

Building a data model that is correct from a business perspective takes more than structural modeling skills

How Long Will the Modeling Take?

Design challengers share techniques to estimate the modeling portion of projects

Who Owns the Data Model?

Does the business, the development team, the individual developer, the application manager, database administrator, own the model?

Real Definitions versus Nominal Definitions in Data Management

Concepts, rather than words, are important to data modelers

Data Modeling in the Cloud

Will the cloud make our data management jobs easier or harder?

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