Transform an SME into a data-driven enterprise
Bisang Stefan, 2016
Betreuende Dozierende: Rainer Telesko
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According a survey1 from Gartner more than 75 percent of companies are investing or planning to invest in Big Data in the next two years. Big Data is getting more visible on the executives agenda. CP Pumps Systems has the aim to turn into a data-driven company in order to streamline processes, to support decision makers or to analyse sensor data. This master thesis deals with a concept for a Big Data platform and the development of a prototype for a certain business scenario.In the very first chapter the reader may find background information about the company, the problems they are facing and the purpose of the thesis. Further, the actual state of literature about Big Data and strategy, the Apache Hadoop stack, hardware and design principles is elaborated. Following that, the research design and the appropriate methodologies are derived. Using the Porter’s generic value chain, the business scenarios for the Big Data platform are identified. In a next step those business scenarios are analysed and rated in regards to technical feasibility, accessibility of required skills and architectural fit and strategic value. Based on the results a high level solution design for the Big Data platform will be worked out and the prototype for the chosen business scenario “Knowledge database” will be developed. The result will be evaluate based on the result during a test period with a defined test audience.The developed prototype, using Apache Hadoop in combination with the search engine ElasticSearch, provides a fast full text search in PDF documents and on top of that analytics based on unstructured data. It was well received from the test audience and also from the executives. The test audience could use the prototype for profound decisions during the daily business. The executives see potential and value in this prototype and they have decided to go ahead with the implementation of a Big Data platform.
Studiengang: Business Information Systems (Master)
Fachbereich der Arbeit: Wirtschaftsinformatik & IT-Management