Utilization of Open Data in Quality Monitoring and Anticipation of Measures
Lamsijärvi, Eemeli (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-202504287984
https://urn.fi/URN:NBN:fi:amk-202504287984
Tiivistelmä
The purpose of this thesis is to give an overview of what open data is and how it can be used to gain new insights based on historical data, how the data can be used to measure the quality of a business and how it can be used to anticipate measures in the near future. The thesis offers concrete steps on how the open data was collected and how it was analyzed.
Open road maintenance data from City of Oulu area provided by Oulunliikenne.fi was used as a concrete example of open data analysis and what new information can be gained from such analysis. While focusing on the data available openly, the insights provided by the thesis can also be utilized for the internal data of any individual company as well.
The data was managed to be visualized. The area where maintenance was carried out, the frequency each route was maintained and the total distances for maintenance vehicles were presented as readable and understandable graphs and maps. A tool for finding the snowiest days was made and maintenance occurring near the snowiest periods were visualized as a graph to analyze the maintenance activity during those time periods.
Based on the visualizations and calculations some suggestions of how the data can be used in data quality monitoring and anticipation of measures are presented. However, it is also remarked that for proper utilization of the data, it should be better connected to the daily operations of a company to get the most benefits out of it.
Open road maintenance data from City of Oulu area provided by Oulunliikenne.fi was used as a concrete example of open data analysis and what new information can be gained from such analysis. While focusing on the data available openly, the insights provided by the thesis can also be utilized for the internal data of any individual company as well.
The data was managed to be visualized. The area where maintenance was carried out, the frequency each route was maintained and the total distances for maintenance vehicles were presented as readable and understandable graphs and maps. A tool for finding the snowiest days was made and maintenance occurring near the snowiest periods were visualized as a graph to analyze the maintenance activity during those time periods.
Based on the visualizations and calculations some suggestions of how the data can be used in data quality monitoring and anticipation of measures are presented. However, it is also remarked that for proper utilization of the data, it should be better connected to the daily operations of a company to get the most benefits out of it.