Epistemology

Programming language

Operations management

Data science

Context (archaeology)

Task (project management)

Data modeling

Database

Philosophy

Artificial intelligence

Economics

Set (abstract data type)

Data quality

Metric (unit)

Biology

Management

Data set

Big data

Operating system

Data mining

Computer science

Process (computing)

Quality (philosophy)

Data model (GIS)

Paleontology

Information Systems Frontiers

Data seldom create value by themselves. They need to be linked and combined from multiple sources, which can often come with variable data quality. The task of improving data quality is a recurring challenge. In this paper, we use a case study of a large telecom company to develop a generic process pattern model for improving data quality. The process pattern model is defined as a proven series of activities, aimed at improving the data quality given a certain context, a particular objective, and a specific set of initial conditions. Four different patterns are derived to deal with the variations in data quality of datasets. Instead of having to find the way to improve the quality of big data for each situation, the process model provides data users with generic patterns, which can be used as a reference model to improve big data quality.

A Process Pattern Model for Tackling and Improving Big Data Quality