The course will begin with an exploration of MongoDB, which is a document database with scalability and flexibility for queries and indexing. Students will progress to the ELK stack - a technology stack used for logging with different components, such as Elasticsearch, Logstash and Kibana. Elastic search is a NoSQL database which stores data as JSON documents, and it can be used to search large data sets. Kibana is an open-source analytics tool which can be used with Elasticsearch for visualisations. Logstash will be covered as a log management tool. Students also learn how to implement real-time scenarios. A review of different Cloud providers will also be covered. A laptop computer with Minimum 8 GB RAM dedicated on your 64 bit OS (16 GB RAM is strongly recommended for DAT 303), Core i5 CPU, 500 GB storage is required.
