- Statistics for Data Science
- James D. Miller
- 138字
- 2021-07-02 14:58:45
Data modeling
Data developers create designs (or models) for data by working closely with key stakeholders based on given requirements such as the ability to rapidly enter sales transactions into an organization's online order entry system. During model design, there are three kinds of data models the data developer must be familiar with—conceptual, logical, and physical—each relatively independent of each other.
Data scientists create models with the intention of training with data samples or populations to identify previously unknown insights or validate current assumptions.
Modeling data can become complex, and therefore, it is common to see a distinction between the role of data development and data modeling. In these cases, a data developer concentrates on evaluating the data itself, creating meaningful reports, while data modelers evaluate how to collect, maintain, and use the data.
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