Title Didžiųjų duomenų analitikos taikymo verslo valdymo sprendimuose modelis /
Translation of Title Model of big data analytics application for business management decisions.
Authors Karbauskas, Edvinas
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Pages 88
Keywords [eng] big data ; data analytics ; management decisions ; data management ; management accounting
Abstract [eng] The technological improvement in the world is leading to a significant increase in the amount of information in households, business environments or public spaces. Managing authorities and businesses realise that increasing amount of information provide new opportunities to use collected and analyzed data for problematic areas identification and performance improvement. Data volumes are growing at such a rapid pace that scientific literature created a new definition of large and diverse data called big data. The growth of data diversity and quantity makes data analysis more difficult as data generated by new technologies are often unstructured or require additional processing. Big data has a very wide potential of application for improving business value propositions to customers since companies can optimize their business processes using big data and offer the best solutions to meet their clients‘ needs. It is important for firms to identify the possibilities of using big data in business, especially in decision making, review possible application problems and ways of solving them, as well as to determine the decisions of organizational managers necessary for successful integration of big data into business management processes. There is a lack of systematic methods in the scientific literature which would assess the state of big data analytics application for business management decisions, identify the scope for big data application and areas for improvement of big data analytics application for business management decisions. The problem of lack of assessment methods is addressed by proposing a systematic model of big data analytics application for business management decisions.
Dissertation Institution Kauno technologijos universitetas.
Type Master thesis
Language Lithuanian
Publication date 2019