Amazing Big Data Facts and Stats

Amazing Big Data Facts and Stats


Amazing Big Data Facts

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Relevant Projects

Spark Project-Analysis and Visualization on Yelp Dataset
The goal of this Spark project is to analyze business reviews from Yelp dataset and ingest the final output of data processing in Elastic Search.Also, use the visualisation tool in the ELK stack to visualize various kinds of ad-hoc reports from the data.

Spark Project -Real-time data collection and Spark Streaming Aggregation
In this big data project, we will embark on real-time data collection and aggregation from a simulated real-time system using Spark Streaming.

Tough engineering choices with large datasets in Hive Part - 2
This is in continuation of the previous Hive project "Tough engineering choices with large datasets in Hive Part - 1", where we will work on processing big data sets using Hive.

Analyse Yelp Dataset with Spark & Parquet Format on Azure Databricks
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.

Analysing Big Data with Twitter Sentiments using Spark Streaming
In this big data spark project, we will do Twitter sentiment analysis using spark streaming on the incoming streaming data.

Real-time Auto Tracking with Spark-Redis
Spark Project - Discuss real-time monitoring of taxis in a city. The real-time data streaming will be simulated using Flume. The ingestion will be done using Spark Streaming.

Real-Time Log Processing in Kafka for Streaming Architecture
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.

Design a Hadoop Architecture
Learn to design Hadoop Architecture and understand how to store data using data acquisition tools in Hadoop.

Airline Dataset Analysis using Hadoop, Hive, Pig and Impala
Hadoop Project- Perform basic big data analysis on airline dataset using big data tools -Pig, Hive and Impala.

Data Warehouse Design for E-commerce Environments
In this hive project, you will design a data warehouse for e-commerce environments.