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.
Still on the series on Data engineering using Yelp dataset, we have established several concepts - from data warehousing to graph analysis. Well done.
But in today's world, not all data are best stored on HDFS. Some special requirements and scenario could require a data storage with a very low latency that could also handle large dataset. Here comes the use of NoSQL databases.
In this NoSQL project, we will use two NoSQL databases(HBase and MongoDB) to store Yelp business attributes and also learn how to retrieve these data for processing or query. We will substantiate the value of these other ways to store data over using HDFS and how to join them with data stored in HDFS in real time.
Seeing that MongoDB is not available in Cloudera Quickstart VM, we are encouraged to install MongoDB on our host machine while setting up a host network interface between the host and the VM for this big data project.
The goal of this hadoop project is to apply some data engineering principles to Yelp Dataset in the areas of processing, storage, and retrieval.
In this hive project, you will design a data warehouse for e-commerce environments.
In this project, we will look at two database platforms - MongoDB and Cassandra and look at the philosophical difference in how these databases work and perform analytical queries.