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The project orientation is very much unique and it helps to understand the real time scenarios most of the industries are dealing with. And there is no limit, one can go through as many projects... Read More
I have worked for more than 15 years in Java and J2EE and have recently developed an interest in Big Data technologies and Machine learning due to a big need at my workspace. I was referred here by a... Read More
Before data on any platform will become an asset to any organization, it has to pass through processing stage to ensure quality and availability. Afterward, that data has to be available to users (both human and system users). The availability of quality data in any organization is the guarantee of the value that data science (in general) will be to that organization.
We are using the airline on-time performance dataset (flights data csv) to demonstrate these principles and techniques in this hadoop project and we will proceed to answer the below questions -
We will also transform the data access model into time series and demonstrate how clients can access data in our big data infrastructure using a simple tool like the Excel spreadsheet.
In this big data project, we will embark on real-time data collection and aggregation from a simulated real-time system using Spark Streaming.
In this PySpark project, you will simulate a complex real-world data pipeline based on messaging. This project is deployed using the following tech stack - NiFi, PySpark, Hive, HDFS, Kafka, Airflow, Tableau and AWS QuickSight.
In this Databricks Azure tutorial project, you will use Spark Sql to analyse the movielens dataset to provide movie recommendations. As part of this you will deploy Azure data factory, data pipelines and visualise the analysis.