Relevance: Information technologies with growing amounts of digital storage and more devices or sensors than ever before have resulted in massive quantities of diverse data, where applying this data for many useful purposes becomes challenging. Term Big Data indicates massive and often unstructured data, for which traditional data management and analysis tools are insufficient.
The aim of the course is to give an an overview of the Big Data concept and main techniques for working with it effectively. Practical focus is on extracting value and formulating data-driven insights using analytics and visualization.
Learning outcome: by the end of the course, students should have a sufficient knowledge of big data analytics as a tool for addressing research questions and approaching challenging problems with data-driven solutions.
Relevance: Information technologies with growing amounts of digital storage and more devices or sensors than ever before have resulted in massive quantities of diverse data, where applying this data for many useful purposes becomes challenging. Term Big Data indicates massive and often unstructured data, for which traditional data management and analysis tools are insufficient.
The aim of the course is to give an an overview of the Big Data concept and main techniques for working with it effectively. Practical focus is on extracting value and formulating data-driven insights using analytics and visualization.
Learning outcome: by the end of the course, students should have a sufficient knowledge of big data analytics as a tool for addressing research questions and approaching challenging problems with data-driven solutions.
Relevance: Information technologies with growing amounts of digital storage and more devices or sensors than ever before have resulted in massive quantities of diverse data, where applying this data for many useful purposes becomes challenging. Term Big Data indicates massive and often unstructured data, for which traditional data management and analysis tools are insufficient.
The aim of the course is to give an an overview of the Big Data concept and main techniques for working with it effectively. Practical focus is on extracting value and formulating data-driven insights using analytics and visualization.
Learning outcome: by the end of the course, students should have a sufficient knowledge of big data analytics as a tool for addressing research questions and approaching challenging problems with data-driven solutions.
Relevance: Information technologies with growing amounts of digital storage and more devices or sensors than ever before have resulted in massive quantities of diverse data, where applying this data for many useful purposes becomes challenging. Term Big Data indicates massive and often unstructured data, for which traditional data management and analysis tools are insufficient.
The aim of the course is to give an an overview of the Big Data concept and main techniques for working with it effectively. Practical focus is on extracting value and formulating data-driven insights using analytics and visualization.
Learning outcome: by the end of the course, students should have a sufficient knowledge of big data analytics as a tool for addressing research questions and approaching challenging problems with data-driven solutions.