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4 Components of a Data Science Project

Scott Plewes | October 10, 2019 | 7 Min Read

Understanding the structure of a typical data science project is the first step in the process of building your internal data science practice. Missing any of the core components of data science can result in the failure of your efforts to realize any true business value.

Data science, at its core, is a practice that involves finding patterns within data. From these patterns, insight can be derived and used for business intelligence purposes or as the basis for creating new product features. Both of these outcomes of a data science project can be beneficial to product teams that are looking to differentiate their offerings in the market and provide customers with greater value. However, before your team can begin to implement data science, they should be well versed in the core components of the domain. Unfortunately, like many fields, there is some variance in how these terms are defined, but for the most part, this should help you better understand some key concepts.

The four components of Data Science include:

Data Strategy

Data Engineering

Data Analysis and Models

Data Visualization and Operationalization

Answer 2

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