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Each project comes with 2-5 hours of micro-videos explaining the solution.
Get access to 50+ solved projects with iPython notebooks and datasets.
Add project experience to your Linkedin/Github profiles.
In this spark project, we will embark on real-time data collection and aggregation from a simulated real-time system.
The dataset for the project which will simulate our sensor data delivery is from Microsoft Research Asia GeoLife project. According to the paper, the dataset recoded a broad range of users’ outdoor movements, including not only life routines like go home and go to work but also some entertainments and sports activities, such as shopping, sightseeing, dining, hiking, and cycling. This trajectory dataset can be used in many research fields, such as mobility pattern mining, user activity recognition, location-based social networks, location privacy, and location recommendation.
As a part of this big data project, we will use the data to provide real time aggregates of the movements along a number of dimension like effective distance, duration, trajectories and more. All streamed data will be stored in the NoSQL database - HBase.
In this big data project, we will talk about Apache Zeppelin. We will write code, write notes, build charts and share all in one single data analytics environment using Hive, Spark and Pig.
In this big data spark project, we will do Twitter sentiment analysis using spark streaming on the incoming streaming data.
In this project, we will take a look at three different SQL-on-Hadoop engines - Hive, Phoenix, Impala and Presto.