7 August 2022
Introduction to Near Real-time Data Analytics
This course serves as an introduction to the technical and engineering aspects of near real-time data analytics.
The core idea of data analytics is to generate relevant information and insights from unrefined organizational data. Data analytics focuses on guiding the decision-making process, i.e. data-driven decision making - using data and facts, rather than intuition. The concepts related to data analytics include data warehouses, data lakes and big data.
We are seeing data grow in size, speed and variety. At the same time, organizations have an expectation that time-to-insight should accelerate. It is no longer enough to have analytics available from the previous day - decision-makers want to see data in near real-time. The use cases for applying near real-time analytics include handling user location data, fraud detection, marketing, Internet-of-Things and any other field where integrating and analyzing data in motion generates business value.
Basic knowledge of SQL and Python/Java is beneficial for taking this course.
Kristo Raun, Junior Research Fellow of Big Data
All students on the level of BA/MA/PhD
Students who complete the course will have:
– An understanding of how to setup stream processing and near real-time analytics services
– Practical experience with state-of-the-art big data tools and frameworks, such as Kafka and Flink.
– Knowledge about different solution architectures and known tradeoffs.
EUR 300: Students are responsible for their travel, accommodation and travel insurance (visa arrangements if needed) from their home country to Tartu and back to their home country. It is recommended to visit the Tartu Welcome Centre website and Student Hostel website to find accommodation opportunities. It is possible to take a bus from Tallinn Airport to Tartu Coach Station (180km). Ticket information on Tpilet.
Find out about the scholarships on our website.