Data engineering projects github. Data Analytics and IBM .

Data engineering projects github Data Lake Storage: Raw data is stored in Azure Data Lake Gen2 (Bronze layer). The firm monitors stock prices, commodities, exchange rates, and inflation rates. ; Azure Databricks: An Apache Spark-based analytics platform optimized for Azure. -pipeline big-data-projects data-engineering Data Engineering Project Using Big Data Technologies - Apache Hadoop HDFS, Apache Hive, Apache Spark, Apache Airflow - GitHub - RIZWAN-VY/Data_Engineering_Project_Using_Big_Data_Technologies: Data Engineering Project Using Big Data Technologies - Apache Hadoop HDFS, Apache Hive, Apache Spark, Apache Airflow You can run this data pipeline using GitHub codespaces. Contribute to darshilparmar/twitter-airflow-data-engineering-project development by creating an account on GitHub. The pipeline is designed to handle data ingestion, transformation, and loading (ETL), utilizing various AWS services and Python libraries This project aims to build a comprehensive data pipeline for extracting, transforming, and analyzing Spotify data using various AWS services. This is a community effort: please contribute and send your pull requests for growing this list! For a list including non-OSS tools, see this amazing Awesome List . Docker: Docker will be our primary tool to orchestrate and run various services. - jaijojohn/spotify-data-engineering-project The project embraced the Lakehouse structure, integrating the Azure Data Lake Gen2 storage solution and leveraging the powerful capabilities of Azure Databricks (big data analytics tool). Where I did data ingestion from an on-premise SQL Server to Azure Data Lake using Data Factory to transformation using Databricks and Spark, loading to Synapse, Big Data Engineering practice project, including ETL with Airflow and Spark using AWS S3 and EMR - GitHub - ajupton/big-data-engineering-project: Big Data Engineering practice project, including E GitHub is where people build software. This is the final project of the IBM Data Engineering This repository is composed of two mini-projects where we'll assume the role of a data engineer. 7. py - these modules contains the functions for creating fact and dimension tables, data visualizations and cleaning. Feel Free to Connect with me 🤠 In this project, we apply Data Modeling with Postgres and build an ETL pipeline using Python. Open the necessary ports on the machine through the firewall. This project aims to provide visibility into the system catalog tables generated by Redshift. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. py and utility. - kinzorize/Covid_19_data_engineering_project GitHub community articles Code, quizzes, and notes from the DeepLearning. You signed out in another tab or window. The purpose of the data engineering capstone project is to give you a chance to combine what you've learned throughout the program. Configure the ADF pipeline to push data to the Bronze container in ADLS Gen2. AI-powered developer platform Available add-ons In this course, Thalia Barrera teaches data professionals how to implement an end-to-end data engineering project using open tools from the modern data stack. Set up Azure Data Factory (ADF) to create pipelines for ingesting data from the on-premises SQL Server Database. A music streaming company, Sparkify, has decided that it is time to introduce more automation and monitoring to their data warehouse ETL pipelines and come to the conclusion that the best tool to achieve this is Apache Airflow. ; Data Visualization: Experience with Looker and PowerBI for creating insightful visualizations. Data Lake: Centralize data storage from multiple sources. This section boasts an intriguing list of data engineering projects with full source code available on GitHub. Contribute to quocde99/Data-Engineering-Projects development by creating an account on GitHub. Currently, they are collecting data in json format and the analytics team is particularly interested in understanding what songs users This project will create a data pipeline that collects streaming data and loads it into a database using Kafka Building Data Pipelines with Shell Create a shell scripts to extract, transform, and load data This project showcases the development of a comprehensive data engineering pipeline for an eCommerce platform. A curated list of awesome things related to Data Engineering. Create codespaces by going to the beginner_de_project repository, cloning it(or click Use this template button) and then clicking on Create The Tokyo Olympic Azure Data Engineering Project showcases a comprehensive data engineering pipeline using Azure services and Apache Spark. Some of them will be some basics & some will be advanced. Personal Data Engineering project witch the objective is create the Data Lakehouse for a B2B e-commerce that must store the transactional and analytical data of the business. This pipeline is engineered to tackle Git and GitHub are powerful tools for data engineers working on complex data engineering projects. Features For the continuous delivery to work, set up the infrastructure with terraform, & defined the following repository secrets. After publishing all Welcome to the Data Engineering Capstone Project. - ddgope/data-engineering-capstone Step4 --> Uploaded the Dataset using Add Data option in DataBricks. GitHub is where people build software. Smart City End to End Realtime data streaming pipeline covering each phase from data ingestion to processing and finally storage. ; Apache Airflow: Responsible for orchestrating the pipeline and storing fetched data in a PostgreSQL database. Awesome Open Source Data Engineering . The project leverages the YouTube API and Whisper transcriptions to provide video insights to data analysts through a data mart layer. ; Wait for codespaces to start, then in the terminal type make up. Percona Server for MongoDB - Percona Server for MongoDB® is a Data Engineering YouTube Analysis Project by Darshil Parmar Overview This project aims to securely manage, streamline, and perform analysis on the structured and semi-structured YouTube videos data based on the video categories and the trending metrics. This project will simulate the The data pipeline consists of the following key components: Ingestion: Data is ingested from an on-premises SQL Server database using Azure Data Factory. Topics Trending Collections ismingjieyang / Data-Engineering Public. It focuses on developing data pipelines that extract, transform, and load data from various sources into diverse databases. Contribute to MidhunSaiVinay/data_engineering_projects development by creating an account on GitHub. introduction; software needed; For more applied learning: Check out the projects section for more hands-on examples!; Check out the interviews section for more advice on how to pass data engineering You can run this data pipeline using GitHub codespaces. 6. Real-time Data Analytics. ; Wait for make up to complete, and I built an end-to-end data engineering project with aws s3, aws glue crawler, data model, dimentional model, python, pandas, redshift and more. Create codespaces by going to the data_engineering_project_template repository, cloning it(or click Use this template button) and then clicking on Create codespaces on main button. Your This project aims to securely manage, streamline, and perform analysis on the structured and semi-structured YouTube videos data based on the video categories and the trending metrics. infrastructure aws postgres data airflow cloudformation cassandra cluster This is a template you can use for your next data engineering portfolio project. Project #4: Continuous Delivery of Rust Actix Web Data Engineering Microservice. By following the steps outlined in this README, clients and evaluators can replicate the setup in their own environments, customize it to meet their needs, and understand the data flow and transformation process. io project3 - Creating Olympic data pipeline - ETL - Python, SQL, AZURE Data Factory, AZURE Gen2 Data lake, AZURE Synapse analytics, AZURE Databricks and Power BI A Professional Data Engineer enables data-driven decision making by collecting, transforming, and visualizing data. A Data Engineering project. Designed and implemented a data warehouse on PostgreSQL using a star schema and performed various queries. This project provides an This project showcases a real-time streaming pipeline utilizing Kafka to integrate a Weather API for live weather data collection. A startup wants to analyze the data they've been collecting on songs and user activity on their new music streaming app. You switched accounts on another tab or window. Build data pipeline with ci/cd . This project will be an important part of your portfolio that will help you achieve your data Implement Complete Data Pipeline Data Engineering Project using Spotify by Integrating with Spotify API and extracting Data Deploying code on AWS Lambda for Data Extraction and using AWS cloud do the transformations. The purpose of this project is to demonstrate various skills associated with data engineering projects. Currently, they Contribute to omo4sho/Data-Engineering-Projects development by creating an account on GitHub. It covers each stage from data ingestion to processing and finally to storage, utilizing a robust tech stack that includes Apache Airflow, Python, Apache Kafka, Apache Zookeeper, Apache Spark, and Cassandra. Follow the instructions below. Scenario: As an expert in Rust programming, you’ve been assigned to lead an important initiative in your data engineering team. /terraform output -raw private_key in the project directory and paste the entire content Batch Processing and ETL using BigQuery, Dataproc and PySpark ETL job Batch data ingestion (into Bigquery/GCD ) using Appache Sqoop and DataProc create a bucket sid-etl /bigquery-etl uplad files to bucket choose a project/create one bigquery-etl create dataset data-analysis create a tabel within The project is designed with the following components: Data Source: We use randomuser. Here are some open-source data engineering projects that you can explore: My Projects Real estate dagster pipeline: A practical data engineering project for processing real estate data. Data Engineering Projects has one repository available. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. The project processes and analyzes data related to the Tokyo Olympics, integrating multiple Azure technologies for data ingestion, transformation, and analysis. This project leverages modern data engineering practices, including incremental data ingestion, ETL (Extract, Transform, Load) pipelines, and Delta Lake for efficient data storage and querying. My Insight Data Engineering Fellowship project. Welcome to the Azure Data Engineering Project!This project is designed to aid aspiring data engineers in preparing for the DP-203: Microsoft Certified Azure Data Engineer Associate exam. This repo contains Big Data Project, its about "Real Time Twitter Sentiment Analysis via Kafka, Spark Streaming, MongoDB and Django Dashboard". Contribute to an open-source project focused on real-time data analytics. The Data Engineer designs, builds, maintains, and troubleshoots data processing systems with a particular emphasis on the security, reliability, fault-tolerance, scalability, fidelity More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. GitHub In this project, you will execute an End-To-End Data Engineering Project on Real-Time Stock Market Data using Kafka. In this project, we apply Data Modeling with Postgres and build an ETL pipeline using Python. Whether you’re a beginner, an intermediate-level engineer, or an advanced practitioner, these projects offer an excellent opportunity to sharpen your big data and data I collected a list of Open-Source DE Projects including two of myself, Airbyte Monitoring with dbt and Metabase (a little bit Rill Data) released yesterday, and an all-in-one Building a Data Building a next-generation hybrid data pipeline architecture that combines the power of Microsoft Fabric, Azure Cloud, and Power BI. Even though the first Python script will be running as Airflow DAG in the end, I would like to introduce the script at this point. Data engineering projects often What are your favourite GitHub repos that shows how data engineering should be done? Discussion Airbyte Monitoring with dbt and Metabase (a little bit Rill Data) released yesterday, and an all-in-one Building a Data Engineering Project in 20 Minutes from last year You signed in with another tab or window. Open Data Stack Projects: Examples of end-to-end GitHub is where people build software. Effectiveness was key in ensuring smooth data transformations, leading to the successful development of the Lakehouse architecture and leveraging the powerful The Ergast Formula 1 Project is designed to provide a robust and scalable data pipeline for ingesting, transforming, and analyzing Formula 1 racing data. GitHub community articles Repositories. These projects are designed to showcase your skills and are valuable additions to your resume: Project 1: Redshift Catalog. AI-powered developer platform Available add This is a complete portfolio of the projects I have designed with a major focus on implementing various data engineering tech and cloud services across Azure, AWS and GCP. I Hope it will be helpful for the readers & me. We are going to use different technologies such as Python, Amazon Web Services (AWS), Apache Kafka, Glue, Athena, and SQL. The contributions are limited to internal Microsoft team but available for Data Source: On-premise SQL Server database, Migrate this database completely to Cloud, Azure Data Lake Gen2 is the storage solution in Azure, Azure Databricks to transform all the raw data into the most curate data, Create all database and tables using Azure Synapse Analytics, Automate all the interior data platform solution - khanfawadali/End 5. - HamzaG737/data-engineering-project GitHub community articles Repositories. Transformation: Data transformations are performed using Azure Databricks, creating Silver and Gold layers. AI-powered developer platform Available add-ons. Udacity Data Engineering Capstone Project on the ETL of the Mars Curiosity Rover environmental data into S3 then a Redshift datawarehouse. To get the most out of this course, you should feel comfortable with coding and command line and know the basics of SQL. Repository for backend infrastructure and Welcome to the Data Engineering Projects section! Here, you'll find a curated collection of projects that delve into the intricate realm of data engineering. This repository is to show my Data Analytics & Engineering skills, share projects, and track my progress. The pipeline is designed to extract data from Polygon API, transform it to fit the desired format, and load it into a Postgres database. Welcome to the Data Engineering repository! This repository hosts a collection of data engineering projects and analyses that demonstrate my skills and expertise in the field of data engineering. The pipeline involves setting up a database, schema, storage integration, stage, and table in Snowflake. This Kaggle dataset contains statistics (CSV files) on daily popular YouTube videos over the course of many months This project demonstrates the creation of an automated data pipeline using Apache Airflow. The full course is available from LinkedIn Learning. *** Note - If you email a link to your GitHub repo with all the completed exercises, I will send you back a free copy of my ebook Introduction to Description: This project demonstrates ETL skills by processing AWS VPC Flow log data. You can set up the repository secrets by going to Settings > Secrets > Actions > New repository secret. a. This solution can be project1 - Pizza Sales Analysis - Postgres SQL, Python, Pandas, Power BI project2 - DVD Rental data warehouse creation - Postgres SQL, PgAdmin, draw. This project is a data engineering pipeline solution to a made-up business problem, created to aid in my learning and understanding of data pipelining. The goal is to explore and implement a type of batch processing called ETL standing for "Extract, Transform and Load". Azure - Ecommerce Data Engineering Project Overview The primary goal of this project is to ensure the secure management, optimization, and analysis of structured data from the E-Commerce API This project uses big data skills with Spark and data lakes to build an ETL pipeline for a data lake hosted on S3. The data coming in would be similar to an event of a user listening to a song, navigating on the website, authenticating. If you are looking for more projects that apply to the principles of data engineering, this GitHub repo provides you with the following 7 different This is an end-to-end data engineering project on the Azure cloud. Congratulations on making it this far! At this point, you've made it through all twelve courses in the Data Engineering Professional Certificate program, beginning with the Introduction to Data Engineering all the way to Getting Started with We will apply foundational Python skills by implementing different techniques to collect and work with data. me API to generate random user data for our pipeline. This is a data project that focuses on uploading, transforming, and loading data into an Azure PostgreSQL database, making use of Bash, Python, SQL and Github Workflows. Explore 10 GitHub repositories that cover various aspects of data engineering, from basics to If you have a good foundation of the basics of data engineering or need a better focus on the tooling, this GitHub repository provides you with a curated list of the type of data engineering tools you make come across. Data Analytics and IBM GitHub is where people build software. Step5 --> Loaded the Dataset to DataFrame using PySpark Step6 --> Transformed the data as per requirements by removing anomalies and irrelavant Columns from DataFrame. We'll utilize tools like IOT devices, Apache Zookeeper, ApacheKafka, Apache Spark, Docker, Python, AWS Cloud, AWS Glue, AWS Athena, AWS IAM, AWS Redshift and finally PowerBI to visualize data on Reshift. Create data factory pipeline so that we can convert our JSON input file to CSV file format. In particular, developing highly Scalable Data Ingestion Architecture Using Airflow and Spark,constructing cloud data warehouses through Redshift databases and S3 data storage as well as defining efficient star schema data model. To copy it, log into GitHub and click on the Use this template button above. This is a final project in "Python Project for Data Engineering" course offerred by IBM in Coursera. IBM Data Engineering Professional Certificate Final Course. I implemented a big data processing pipeline based on lambda architecture , that aggregates Twitter and US stock market data for user sentiment analysis using open source tools - Apache Kafka for data ingestions, Apache Spark & Spark Streaming for batch & real-time processing, Apache Cassandra f or storage, Flask , A collection of Data Engineering projects that show how to use languages like Python and R, as well as SQL and NoSQL databases to perform data engineering tasks. Pipeline takes data from free API detailing cryptocurrency and performs transformations and data-type casting. She touches on best practices such as data modeling, testing, documentation and version control and shows you how to efficiently extract, load, and transform data into a unified For this project, we are leveraging a GitHub repository that hosts our entire setup, making it easy for anyone to get started. Databricks and Azure projects for experimenting, learning and demonstrating knowledge - JANHMS/Databricks-on-Azure-Data-Engineering-project The project's objective is to build an end-to-end solution for data processing and reporting: Data Ingestion: Retrieve tables from on-premise SQL Server using Azure Data Factory. A producer program efficiently gathers this data and feeds it into a Kafka cluster for seamless ingestion. If you are new to data engineering, start by following this 2024 breaking into data engineering roadmap. Topics Trending Collections Enterprise Enterprise platform. Data&AI-Engineering-Projects has one repository available. . This project demonstrates a complete data engineering pipeline using various Azure tools. It is then loaded into an Demonstrate knowledge of Data Engineering by assuming the role of a Junior Data Engineer who is presented with a project that requires architecting and implementing a data analytics platform. ; Azure Synapse Analytics: A unified analytics service that brings Data Engineering Projects on GitHub 8. main In this project, I created an entire data architecture for a made-up whiskey retail shop that will enable shop managers to make decisions based on their data. The ReadME Project. The goal is In this IBM project, I played the role of data engineer for an international economic research firm. The system consists of two modules: The following Azure services are commonly used in data engineering projects: Azure Data Factory: For orchestrating and automating data movement and transformation. Verification: Open a terminal or command prompt and execute docker --version to Data Ingestion: Build a mechanism to ingest data from different sources. Data Transformation (Databricks): Utilize Azure Databricks for Sending the Data to Kafka Topic. It follows the same start-to-end structure with a key distinction: whenever a tool is introduced in By the end of this post, you will be able to understand how to set up data infrastructure with code, how developers work together on new features to data pipeline, & An end-to-end modern data engineering project, including deployment of ETL pipeline on Google Cloud Platform, using BigQuery for data analysis and leveraging Looker to generate an insight dashboard. As an engineer specialized in big data, I've dedicated this space to showcase my expertise Data Engineering Projects . Here my work entails extracting financial data from We are thrilled to introduce the Cloud Data Engineering Roadmap, which builds on the foundation of our existing Data Engineering Roadmap. But mainly, I'll use the most popular tools in the Data Engineering spectrum like Apache Spark, Kafka, Flink, , etc. - lucjankonopka/portfolio This project explored several data engineering technologies, concepts and skills that I acquired while completing the IBM Data Engineering Professional Certificate. Currently, they are collecting data in json format and the analytics team is particularly interested in understanding what songs users are listening to. It does so by building an ETL pipeline using Azure Data Factory, Azure Databricks and Azure Synapse Analytics. Accompanied by a blog article: Building a Data Engineering Project in 20 Minutes. Here you want to write a short overview of the goals of your project and how it works at a high level. py - reads data from S3, processes that data using Spark, and writes processed data as a set of dimensional tables back to S3; etl_functions. It extracts data from input files, transforms it by mapping each row to a tag based on a lookup table, and loads the results into a CSV report. SERVER_SSH_KEY: We can get this by running terraform -chdir=. Enterprise-grade security features The goal of this project is to perform data analytics on Uber data using various tools and technologies, including GCP Storage, Python, Compute Instance, Mage Data Pipeline Tool, BigQuery, and Looker Studio. Repository link: Data-Engineering-Projects. TLC Trip Record Data Yellow and green taxi trip records include fields capturing pick-up and This note is for data engineers and developers. MongoDB - An open-source, document database designed for ease of development and scaling. It offers a comprehensive, real-time solution that leverages key Azure services to build an end-to-end data pipeline, providing hands-on experience with essential data engineering tools and The project will stream events generated from a fake music streaming service (like Spotify) and create a data pipeline that consumes the real-time data. The final output is visualized using Power BI. Add a description, image, and links to the data-engineering-project topic page so that developers can more easily learn about it. ; Apache Kafka and Zookeeper: Used for streaming data from PostgreSQL to the processing engine. This course presents to the students recent research and industrial issues GitHub is where people build software. This capstone project is the 13th course of the IBM Data Engineering Professional Certificate and contains more or less all the material learned during the courses. Add a description, image, and links to the aws-data-engineering-project topic page so that developers can more easily learn about it. One minute after the images stand up, data begins to be written to the Kafka topic and activity begins in Data Pipelines with Apache Airflow. AI Data Engineering Professional Certificate specialization, showcasing practical projects, skills developed, and a capstone work in data engineering. If GitHub is where people build software. Once I get this nicely up and running I will start working on different setups, using the same data, but using tools like Airflow, Mage, Azure Data Factory, Azure Synapse Data Engineering Projects on GitHub. End to end data engineering project with kafka, airflow, spark, postgres and docker. ; Control Center and Schema In addition to the data files, the project workspace includes: etl. Add a description, image, and links to the data-engineering-projects topic page so that developers can more easily learn about it. , a wide range of Databases, and some Cloud Services. By following best practices and integrating Git and GitHub into 6. The goal is to ingest, store, transform, and analyze data related to the Tokyo Olympics. ; Data Storage: Store raw and transformed data in Azure Data Lake Storage Gen2. Advanced Security. ; Data Pipeline Orchestration: Familiar with Apache Airflow for automating data workflows. The course is a short project that involves applying what you learned in python to do the following: This repository serves as my code for the final project where I have to apply the concepts in the GitHub is where people build software. ; Python: Intermediate level proficiency for data analysis, scripting, and machine learning. The aim of this project is to create high grade data pipelines that are dynamic and built from reusable tasks, can be data engineering projects for learning. In this Master data engineering with Git and GitHub! Explore a real-world customer analytics pipeline scenario in this comprehensive guide. - SQL: Proficient in Microsoft SQL Server, PostgreSQL, and MySQL. The world of data engineering is ever-changing, with new tools and technologies Website and repos for DE projects. The pipeline streamlines data extraction, transformation, and loading (ETL) from various sources. Reload to refresh your session. Each project showcases various This Awesome List aims at providing an overview of open-source projects related to data engineering. You also need to open the necessary ports with the operating system. Playing the role of a Data Engineer and extract data from multiple file formats, transform it into specific datatypes, and then load it One of the main obstacles of Data Engineering is the large and varied technical skills that can be required on a day-to-day basis. Skip to content. The documentation originated out of a need to standardize a requirements gathering This is the repository for the LinkedIn Learning course End-to-End Data Engineering Project. If you are here for the 6-week free YouTube boot camp you can check out. ; Data Transformation: Use Azure Databricks to clean and transform raw data into structured formats. Here are seven end-to-end data engineering projects that can significantly boost your portfolio and set you apart from the competition and give you unfair advantage over Learn data engineering through free courses, tutorials, books, tools, guides, roadmaps, practice exercises, projects, and other resources. Objective. Learn how to design, develop, deploy and iterate on production-grade ML applications. This project addresses a critical business need by building a comprehensive data pipeline on Azure. Installation: Visit Docker's official website to download and install Docker Desktop for your OS. The final system A collection of data engineering projects: data modeling, ETL pipelines, data lakes, infrastructure configuration on AWS, data warehousing, containerization, and a dashboard to monitor data pipeline KPIs - GitHub - AuFeld/Data_Engineering_Projects: A collection of data engineering projects: data modeling, ETL pipelines, data lakes The goal of this project is to implement a distributed system that processes, transforms, and persists CSV data in Parquet format. In this project, We have designed and implemented a robust data pipeline to handle diverse datasets from various sources, perform ETL Few projects related to Data Engineering including Data Modeling, Infrastructure setup on cloud, Data Warehousing and Data Lake development. ; Other Tools: Excel, This repository containts a practical implementation of a data engineering project that spans across web-scraping real-estates, processing with Spark and Delta Lake, adding data science with Jupyter Notebooks, ingesting data into An end to end ETL pipeline for a recommendation system using Azure toolkit - GitHub - metal0bird/Azure_data_engineering_project: An end to end ETL pipeline for a recommendation system using Azure toolkit. Awesome Open Source Data Engineering is a list of open-source data engineering tools that is a goldmine for anyone looking to contribute to or use them to build real-world data GitHub is where people build software. 📚 Papers & tech blogs by companies sharing their work on data science & Incorporate these steps into each data engineering project—whether building ETL pipelines, analytics workflows, or machine learning models—to maintain high-quality, scalable, and Few projects related to Data Engineering including Data Modeling, Infrastructure setup on cloud, Data Warehousing and Data Lake development. - tranhuy25/e2e-data-engineering Here are some interesting data engineering project ideas that utilize NumPy, Pandas, Matplotlib, and BeautifulSoup. The project integrates Azure Data Factory, Databricks, Synapse Analytics, and Power BI to deliver a complete data solution. The use of these tables has played a crucial role in cataloging, monitoring, and governing our data warehouse. This project serves as a comprehensive guide to building an end-to-end data engineering pipeline. Follow their code on GitHub. forked from DongboShi/Data-Engineering. In this project, I have created a data pipeline to import YouTube video data using Snowflake and AWS S3. Prior experience with Python will be helpful, but you can pick Python relatively fast if you have experience with YouTube tutorial project. 21) Real-time Financial The goal is to create an Azure solution which can take an On-premise Database such as the Microsoft SQL Server Management System (SSMS) and move it to the Cloud. Code; Pull requests 0; You will find here some data engineering projects I've done. Create Azure data factory and Open it to create new pipeline. This repository is used to provide guidance in a standard data engineering project that consists of a data lake and data warehouse. Project 1a - PostgreSQL Building a star schema in PostgreSQL and inserting data via Python ️ Project 1b - Cassandra Building a star schema in Cassandra and inserting data via Python ️ Project 2 - AWS Redshift Building a star Hello! My name is Andre Ichiro and this project represents my journey in the realm of data engineering. Notifications Fork 6; Star 0. As for programming languages, I'll use Python but I'll do some Rust coding as well. The This repository contains a personal project designed to enhance my skills in Data Engineering. This project is an exploration of using MageAI to build an ETL pipeline. Data is loaded from S3, then processesd into analytics tables using Spark, and loaded back into S3. In this project, we put into practice the following concepts, data modeling with Postgres, database star schema design, ETL pipelining. ETL System: Transform raw data into a proper format for analysis. Welcome to our comprehensive end-to-end data engineering project tailored for e-commerce. Also we have to add columns data for future purpose. Additionally, the transcriptions are used to Open an Ubuntu machine via AWS EC2 for the project. The pipeline will integrate with the Spotify API to fetch relevant data and store it in an organized manner on Repo to share Data Engineering, ML OPS, Data Analyst best practices - GitHub - Azure/DataEngineering: Repo to share Data Engineering, ML OPS, Data Analyst best practices This project host demo codes, third-party product references in the context of how to use them. ; Azure Stream Analytics: For real-time data stream processing. Essentially, anything that can add value to a Data Engineering project. cbn yigi xhtfyg kjlpl qppoww jtyrg vcwsb mzyha hxgyli wgrw