In this Spark project, we are going to bring processing to the speed layer of the lambda architecture which opens up capabilities to monitor application real time performance, measure real time comfort with applications and real time alert in case of security
In this Databricks Azure project, you will use Spark & Parquet file formats to analyse the Yelp reviews dataset. As part of this you will deploy Azure data factory, data pipelines and visualise the analysis.
In this big data project, we will continue from a previous hive project "Data engineering on Yelp Datasets using Hadoop tools" and do the entire data processing using spark.
In this machine learning pricing project, we implement a retail price optimization algorithm using regression trees. This is one of the first steps to building a dynamic pricing model.
This Elasticsearch example deploys the AWS ELK stack to analyse streaming event data. Tools used include Nifi, PySpark, Elasticsearch, Logstash and Kibana for visualisation.
