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I came to the platform with no experience and now I am knowledgeable in Machine Learning with Python. No easy thing I must say, the sessions are challenging and go to the depths. I looked at graduate... Read More
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
In Dezyre's Hadoop hands-on training course, we perform two different projects that require us to stream data from twitter in real time. Most of these hadoop projects are a production scenario which will then involve analyzing the project in a batch mode and representing to end users.
But what if the decision that needs the streamed data is time sensitive? This means that we must stream that data and analyze it in motion. After analysis, the result must be presented as the streaming is taking place.
An example of a use of such system is to analyze public response to any event in real time like a political speech, a sports game, an economic news and much more. People with the access to quality real-time data can then position themselves for profit in such circumstance.
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 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
The goal of this apache kafka project is to process log entries from applications in real-time using Kafka for the streaming architecture in a microservice sense.