Search for dissertations about: "data analytics in business"
Showing result 1 - 5 of 23 swedish dissertations containing the words data analytics in business.
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1. Data-driven AI Techniques for Fashion and Apparel Retailing
Abstract : Digitalisation allows companies to develop many new ways of interacting with customers and other stakeholders. These digital interactions typically generate data that can be stored and later processed for different objectives. READ MORE
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2. Business Intelligence through a sociomaterial lens : The imbrication of people and technology in a sales process
Abstract : Digitalization and digital devices are on the rise, and as a result, many new products and services have been developed, which has led to greater interaction between people and technology. This thesis explores the interaction between people and technology by looking at the daily use of a business intelligence (BI) system in an automotive company’s sales process, where sellers use the system to analyze, report, and measure sales performance. READ MORE
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3. Reliable Information Exchange in IIoT : Investigation into the Role of Data and Data-Driven Modelling
Abstract : The concept of Industrial Internet of Things (IIoT) is the tangible building block for the realisation of the fourth industrial revolution. It should improve productivity, efficiency and reliability of industrial automation systems, leading to revenue growth in industrial scenarios. READ MORE
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4. Data-driven Innovation : An exploration of outcomes and processes within federated networks
Abstract : The emergence and pervasiveness of digital technologies are changing many aspects of our lives, including what and how we innovate. Industries and societies are competing to embrace this wave of digitalization by developing the right infrastructures and ecosystems for innovation. READ MORE
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5. Smart Cities and Big Data Analytics : A Data-Driven Decision-Making Perspective
Abstract : The phenomenon of digitalization has led to the emergence of a new term—big data. Big data refers to the vast volumes of digital data characterized by its volume, velocity, variety, veracity, and value. READ MORE