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.
Initially, I was unaware of how this would cater to my career needs. But when I stumbled through the reviews given on the website. I went through many of them and found them all positive. I would... Read More
Recently I became interested in Hadoop as I think its a great platform for storing and analyzing large structured and unstructured data sets. The experts did a great job not only explaining the... Read More
The entire goal of investing in a data infrastructure is to improve the edge of business as well as the company's bottom line.
In this big data project, we are going to be designing a data warehouse for a retail shop. The design and implementation, however, we focus on answering some specific questions that are related to price optimization and inventory allocation. The two questions we will be looking to answer in this hive project include:
We will recognize the entire purpose of answer these questions with data is to boost overall bottom line for the business while improving the experience for the shoppers.
In this hadoop project, we are going to be continuing the series on data engineering by discussing and implementing various ways to solve the hadoop small file problem.
This Elasticsearch example deploys the AWS ELK stack to analyse streaming event data. Tools used include Nifi, PySpark, Elasticsearch, Logstash and Kibana for visualisation.
Analyze clickstream data of a website using Hadoop Hive to increase sales by optimizing every aspect of the customer experience on the website from the first mouse click to the last.