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In this hive project, you will work on denormalizing the JSON data and create HIVE scripts with ORC file format.
In this hadoop project, learn about the features in Hive that allow us to perform analytical queries over large datasets.
In this project, we will take a look at three different SQL-on-Hadoop engines - Hive, Phoenix, Impala and Presto.
The goal of this hadoop project is to apply some data engineering principles to Yelp Dataset in the areas of processing, storage, and retrieval.
Hadoop Project- Perform basic big data analysis on airline dataset using big data tools -Pig, Hive and Impala.
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 embark on real-time data collection and aggregation from a simulated real-time system using Spark Streaming.
The goal of this IoT project is to build an argument for generalized streaming architecture for reactive data ingestion based on a microservice architecture.
In this hadoop project, learn about the features in Hive that allow us to perform analytical queries over large datasets.
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.
Hadoop Project- Perform basic big data analysis on airline dataset using big data tools -Pig, Hive and Impala.
In this hive project, you will design a data warehouse for e-commerce environments.
In this Apache Spark SQL project, we will go through provisioning data for retrieval using Spark SQL.
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.
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 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 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 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 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.
Learn to perform 1) Twitter Sentiment Analysis using Spark Streaming, NiFi and Kafka, and 2) Build an Interactive Data Visualization for the analysis using Python Plotly.
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.
This Elasticsearch example deploys the AWS ELK stack to analyse streaming event data. Tools used include Nifi, PySpark, Elasticsearch, Logstash and Kibana for visualisation.
Learn to perform 1) Twitter Sentiment Analysis using Spark Streaming, NiFi and Kafka, and 2) Build an Interactive Data Visualization for the analysis using Python Plotly.
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.
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 project, we will be building and querying an OLAP Cube for Flight Delays on the Hadoop platform.
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.
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 big data project, we will see how data ingestion and loading is done with Kafka connect APIs while transformation will be done with Kafka Streaming API.
In this project, we will show how to build an ETL pipeline on streaming datasets using Kafka.
Use the dataset on aviation for analytics to simulate a complex real-world big data pipeline based on messaging with AWS Quicksight, Druid, NiFi, Kafka, and Hive.
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.
Use the RACE dataset to extract a dominant topic from each document and perform LDA topic modeling in python.
Given big data at taxi service (ride-hailing) i.e. OLA, you will learn multi-step time series forecasting and clustering with Mini-Batch K-means Algorithm on geospatial data to predict future ride requests for a particular region at a given time.
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.
In this GCP Project, you will learn to build a data processing pipeline With Apache Beam, Dataflow & BigQuery on GCP using Yelp Dataset.
In this AWS Project, you will build an end-to-end log analytics solution to collect, ingest and process data. The processed data can be analysed to monitor the health of production systems on AWS.
Every year, people looking to begin their big data career run into a familiar conundrum -
"How can I land a big data job with limited experience in this field?".
For an emerging field like big data, finding internships or full-time big data jobs requires you to showcase relevant achievements working with popular open-source big data tools like Hadoop, Spark, Kafka, Pig, Hive, and more. Big data and project-based learning are a perfect fit. The best way to get started is to begin working on diverse big data project titles under the mentorship of industry experts. Professionals will love working on these big data projects because it's like a secret. There is so much practical learning involved you don't realize it. ProjectPro's big data projects are perfect for beginners, college students, engineering students, professionals wanting to make a career switch, and anyone who wants to master big data skills with hands-on experience.
If you have a graduate degree in analytics or a relevant field from a top-tier college, it is easy for you to get a big data job. Employers believe that you will be able to add value to their business because of the prestige of the college that has awarded you the degree, and the reality that it is in a subject that is relevant to the kind of skills they are looking for. If you do not have an analytics degree from a top-tier college then you need to build that trust yourself that you have the big data skills that the employer is looking for. The best way to build trust with the hiring manager is to work on interesting big data project ideas and build a portfolio of multiple big data projects - Hadoop projects, spark projects, hive projects, Kafka projects, impala projects, and more. The more "real-world" the big data projects are, the more the hiring manager will trust that you will be an asset to their organization, and the greater are your chances of landing the big data job. The best thing about big data careers is that the work you do on building diverse big data projects often looks exactly similar to the work you will do once you are hired.
For IT professionals or anybody with basic big data knowledge, Dezyre's mini projects on big data will help them take responsibility in solving challenging data problems, and help gain expertise on the popular big data tools like Hadoop, Spark, Hive, Pig,
The good news for people in search of big data projects for CSE students is that there are a couple of websites that have big data projects with source code. If you google for search terms like "big data projects GitHub" or "big data projects Quora", you might find suggestions on multiple big data project titles, however, for students on the hunt for big data final year projects, titles and source code is not what all they need for learning. Students need industry expert guidance for deeper understanding and greater retention of knowledge so that they can apply what they know to new real-world big data problems. ProjectPro has an excellent project-based learning platform where students will enjoy using a spectrum of big data tools under expert guidance.
Here are some popular big data project titles among the college students-
IT professionals and college students rate our big data projects as exceptional. Whether you are looking to upgrade your skills or you are looking to learn about the complete end-to-end implementation of various big data tools like Hadoop, spark, pig, hive, Kafka, and more, Dezyre's mini projects on big data are just what you want.
More data is created every hour today than in an entire year just 20 years ago, according to the Seagate Rethink Data Survey by IDC, which was released in January 2020. Today’s tech market is dominated by technologies like big data, data science, machine learning, and cloud computing - the areas that usually go hand-in-hand and see a crossover in skillsets for diverse data job roles like data analyst, data engineer, data architect, and data scientist to name a few. According to Forbes, over 90% of companies state that they are still facing the need to manage unstructured data. Demand for data skills is growing and there is a huge shortage of skilled talent and honing these skills with the know-how of the latest tools and technologies will definitely make you stand out from the crowd of job applicants.ProjectPro helps you hone the most in-demand big data skills through real-time big data projects that have been vetted and created along with industry experts from Uber, JPMorgan, Paypal. This ensures relevance in the big data industry and provides you with the skills that matter the most at any given point in time in your career.
One of the hardest things to do when beginning a big data or data science career is to create a project portfolio of real-time big data projects. Whether you’re taking the first steps in your big data career or just want to brush up on your big data skills, the most important thing to have on your resume is hands-on projects. Most students or beginners do not have any substantial work experience and the big data courses they do might not just be enough in putting up a worthy portfolio to showcase to the hiring managers. ProjectPro’s big data projects have been vetted and created along with industry experts from Uber, JPMorgan, Paypal. This ensures relevance in the big data industry and providing you with the content that is industry-standard and matters the most. We have simple big data projects for practice and also advanced big data projects with source code that will test your data skills and help you build a well-rounded analytics portfolio that a hiring manager will definitely take a notice of. Included in each big data project with source code is –
The number of big data projects available at any point in time cannot be pinned at an exact number because we keep actively building up our project repository every month. The repository of real-time big data projects is updated every month with new projects based on the most in-demand and novel big data tools and technologies, some of which consists of big data tools like Hadoop, Spark, Redis, Kafka, Kylin, Redis, to name a few and popular cloud platforms like AWS, Azure, and GCP. We have projects right from beginner level to the advanced level so there are big data projects for beginners, big data projects for students, and big data projects for professionals willing to upskill. The independent projects available will help you showcase your versatile big data skills to employers making them a great fit for winning the big data job that you have dreamed of.
What kinds of datasets are used in these big data projects and what is their source?
We understand that while working on big data projects, one of the toughest challenges is having access to large datasets. If you have been struggling to find the right dataset for your project, then these big data projects can come to your rescue. All our big data projects provide downloadable datasets so right from the dataset to the source code to video explanations of the source code- these have everything you need to deploy a project in production. Our projects are developed using popular big datasets from online repositories like Kaggle, UCI Machine Learning Repositories, Data.Gov, Google Public Datasets, AWS Public Datasets, and by scraping data from other sources.. Irrespective of whether you require a dataset to start working on a specific big data or data science project, or whether you need it to just practice your big data skills, you need not waste time browsing the internet for the required datasets. We’ve got all sorts of datasets covered to help you meet your project goal.
Can I get a trial period for a week to practice these sample big data projects?
We provide free access to real-time big data projects that are available on the site for a specific duration as notified by our Project Advisors on the date of enrollment. You can always speak with our Project Advisors while enrolling to know the number of free days you are eligible for. Please note that the trial period will be revoked once the number of days specified by our Project Advisors has lapsed.
Can we download the videos for every big data project?
No, the video lectures for the big data projects are not available for download on your device. However, the all-access annual subscription plan gives you unlimited access to the videos, reusable solution code, datasets, and documentation. They can be accessed 24x7, 365 days a year. All you need is your login credentials and a good internet connection.
