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A structured introduction to the science and craft of data management, including: data representations and their advantages and disadvantages; workflow and data governance; combining and splitting data sets; data cleaning; the creation of non-trivial summary variables; and the handling of missing data. These will be illustrated by data sets of varying size and complexity, and students will implement data processing steps in at least two software systems.

A structured introduction to the science and craft of data management, including: data representations and their advantages and disadvantages; workflow and data governance; combining and splitting data sets; data cleaning; the creation of non-trivial summary variables; and the handling of missing data. These will be illustrated by data sets of varying size and complexity, and students will implement data processing steps in at least two software systems.

A structured introduction to the science and craft of data management, including: data representations and their advantages and disadvantages; workflow and data governance; combining and splitting data sets; data cleaning; the creation of non-trivial summary variables; and the handling of missing data. These will be illustrated by data sets of varying size and complexity, and students will implement data processing steps in at least two software systems.