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.

In this hive project , we will build a Hive data warehouse from a raw dataset stored in HDFS and present the data in a relational structure so that querying the data will be natural.

Hive Project- Understand the various types of SCDs and implement these slowly changing dimesnsion in Hadoop Hive and Spark.

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.

Hive Project- Understand the various types of SCDs and implement these slowly changing dimesnsion in Hadoop Hive and Spark.

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.

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 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 big data project, we will be performing an OLAP cube design using AdventureWorks database. The deliverable for this session will be to design a cube, build and implement it using Kylin, query the cube and even connect familiar tools (like Excel) with our new cube.

In this big data project, we will discover songs for those artists that are associated with the different cultures across the globe.

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

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.

In this hadoop project, you will be using a sample application log file from an application server to a demonstrated scaled-down server log processing pipeline.

In this spark streaming project, we are going to build the backend of a IT job ad website by streaming data from twitter for analysis in spark.

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 Apache Spark SQL project, we will go through provisioning data for retrieval using Spark SQL.

Explore hive usage efficiently in this hadoop hive project using various file formats such as JSON, CSV, ORC, AVRO and compare their relative performances

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.

Hadoop Projects for Beginners -Learn data ingestion from a source using Apache Flume and Kafka to make a real-time decision on incoming data.

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.

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.

In this hadoop project, learn about the features in Hive that allow us to perform analytical queries over large datasets.

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.

In this Apache Spark SQL project, we will go through provisioning data for retrieval using Spark SQL.

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.

This Elasticsearch example deploys the AWS ELK stack to analyse streaming event data. Tools used include Nifi, PySpark, Elasticsearch, Logstash and Kibana for visualisation.

The goal of this spark project is to analyse the level and strength of interactions across areas of coverage of a telecom provider between different areas in the city of Milan.

In this Neo4j project, you will do network analysis using a graph database to find patterns on how a social network affects business reviews and ratings.

In this big data project, we will look at how to mine and make sense of connections in a simple way by building a Spark GraphX Algorithm and a Network Crawler.

In this hadoop project, you will be using a sample application log file from an application server to a demonstrated scaled-down server log processing pipeline.

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.

In this big data spark project, we will do Twitter sentiment analysis using spark streaming on the incoming streaming data.

In this big data spark project, we will do Twitter sentiment analysis using spark streaming on the incoming streaming data.

In this Hackerday, we will go through the basis of statistics and see how Spark enables us to perform statistical operations like descriptive and inferential statistics over the very large dataset.

The goal of this spark project for students is to explore the features of Spark SQL in practice on the latest version of Spark i.e. Spark 2.0.

In this project, we will look at Cassandra and how it is suited for especially in a hadoop environment, how to integrate it with spark, installation in our lab environment.

In this Hackerday, we will go through the basis of statistics and see how Spark enables us to perform statistical operations like descriptive and inferential statistics over the very large dataset.

PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.

In this project, we are going to talk about insurance forecast by using regression techniques.

This Elasticsearch example deploys the AWS ELK stack to analyse streaming event data. Tools used include Nifi, PySpark, Elasticsearch, Logstash and Kibana for visualisation.

In this big data project, we'll work with Apache Airflow and write scheduled workflow, which will download data from Wikipedia archives, upload to S3, process them in HIVE and finally analyze on Zeppelin Notebooks.

In this big data project, we will talk about Apache Zeppelin. We will write code, write notes, build charts and share all in one single data analytics environment using Hive, Spark and Pig.

In this spark streaming project, we are going to build the backend of a IT job ad website by streaming data from twitter for analysis in spark.

The goal of this IoT project is to build an argument for generalized streaming architecture for reactive data ingestion based on a microservice 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.

In this big data project using Neo4j, we will be remodelling the movielens dataset in a graph structure and using that structures to answer questions in different ways.

In this Neo4j project, you will do network analysis using a graph database to find patterns on how a social network affects business reviews and ratings.

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.

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 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.