Search for dissertations about: "data quality"
Showing result 1 - 5 of 3759 swedish dissertations containing the words data quality.
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1. Contributions to the Use of Statistical Methods for Improving Continuous Production
Abstract : Complexity of production processes, high computing capabilities, and massive datasets characterize today’s manufacturing environments, such as those of continuous andbatch production industries. Continuous production has spread gradually acrossdifferent industries, covering a significant part of today’s production. READ MORE
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2. Quantifying Process Quality : The Role of Effective Organizational Learning in Software Evolution
Abstract : Real-world software applications must constantly evolve to remain relevant. This evolution occurs when developing new applications or adapting existing ones to meet new requirements, make corrections, or incorporate future functionality. READ MORE
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3. Quality management : National or global driving factors
Abstract : Around the world Quality Management is commonly regarded by industrialists and academics as a management concept that encompasses the potential in any organisation of developing into a company-wide philosophy with a profound focus on stakeholder values and improvement processes. However, there are mounting evidence that Quality Management has developed into an important strategic issue also on a national level, and that some leading industrial nations have enjoyed significant gains in the post War era by means of nation-wide progresses in Quality Management. READ MORE
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4. Flood Hazard Assessment in Data-Scarce Basins : Use of alternative data and modelling techniques
Abstract : Flooding is of great concern world-wide, causing damage to infrastructure, property and loss of life. Low-income countries, in particular, can be negatively affected by flood events due to their inherent vulnerabilities. Moreover, data to perform studies for flood risk management in low-income regions are often scarce or lacking sufficient quality. READ MORE
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5. Data management and Data Pipelines: An empirical investigation in the embedded systems domain
Abstract : Context: Companies are increasingly collecting data from all possible sources to extract insights that help in data-driven decision-making. Increased data volume, variety, and velocity and the impact of poor quality data on the development of data products are leading companies to look for an improved data management approach that can accelerate the development of high-quality data products. READ MORE