Mage

🍁 In October, Mage Pro introduced a ton of features to give your data even more magical powers! These updates will boost your team’s productivity, performance, security, and collaboration. 🤝 Terminal collaboration 📦 Azure Block Templates 🌀 Git sync 2.0 🌐 Hybrid deployment 🖥️ Deployboard (apps/deploy) 📊 Pipeline dependency graph Transform your data insights by accessing all these features and more with Mage Pro! 🔗 Express your interest in getting access to our private beta by filling out this short form: https://lnkd.in/gCcUEP9D 🌍 Join our community of 6800+ data engineers: mage.ai/chat

Experience the Power of Teamwork with Mage Pro's Shared Terminal Workspace! The shared terminal workspace in Mage Pro enables real-time, seamless collaboration in a consistent environment, accelerating development and reducing workflow friction. Key benefits: 🤝 Real-Time Collaboration: Work together effortlessly! Team members can make live edits and updates, transforming how you code and collaborate. 📝 Advanced Version Control: Enjoy peace of mind with built-in version control, ensuring every change is tracked and conflicts are minimized for a smooth, coordinated workflow. 🔐 Custom User Permissions: Manage access with precision. Assign specific roles to team members for efficient project management and secure collaboration. 🔥 Express your interest in Mage Pro by filling out this short form: https://lnkd.in/gCcUEP9D 🌐 Join community with 6800+ data engineers: mage.ai/chat

🔓💫 Unlock the full potential of your SQL workflows with Mage's SQL Blocks, designed to make complex data tasks easier, faster, and more efficient than ever! Mage's SQL Blocks provide a powerful toolkit that combines flexible data transformations with seamless integration across multiple data sources. Enjoy streamlined automation for advanced SQL tasks, making complex workflows simpler and more efficient. ✨ Boost Efficiency: Tackle intricate data transformations and streamline pipeline management to save time and effort. ⚙️ Full Flexibility: From automated workflows to advanced SQL queries, you can tailor your approach to match any level of complexity—simplifying both straightforward and demanding data tasks. 🔗 Effortless Connections: SQL Blocks integrate smoothly with Python, R, and other SQL blocks, making it easy to build dynamic pipelines that flow seamlessly from one task to the next. 🌐 Join our community of our 6800+ data engineers: mage.ai/chat 📚 Link in the comments to learn how you can implement SQL blocks in your workflows

6 FREE End-To-End Data Engineering Projects (2Million+ Views)📈 Kick-start your career in Data Engineering with these projects, you will learn more than any paid courses for FREE! 1. IPL Data Analysis (End-To-End Apache Spark Databricks Project)- https://lnkd.in/dQiMq6PJ What will you learn? ✅ Python and PySpark ✅ SQL ✅ Apache Spark Basics and Databricks ✅ Writing transformation logic ✅ Visualizing data for insights 2. YouTube Data Analysis (End-To-End Data Engineering Project) - https://lnkd.in/d5BRZfXv What will you learn? ✅ Python and PySpark ✅ SQL ✅ How to understand the business problem ✅ AWS Services - Athena, Glue, Redshift, S3, IAM ✅ Building Data Pipeline and Scheduling it 3. Twitter Data Pipeline using Airflow - https://lnkd.in/dE2VvdSg What will you learn? ✅ Python ✅ Basics of Airflow ✅ Working with Twitter Data and Package - Tweepy ✅ Python Package - Pandas ✅ Writing ETL job and storing data on S3 4. Stock Market Real-Time Data Analysis using Kafka, AWS, and Python - https://lnkd.in/dah8Au3B What will you learn? ✅ Build a Real-Time app using Python ✅ Understand the basics of Kafka ✅ Install Kafka on EC2 ✅ Generate a real-time pipeline and ✅ Analyze Data in Real-Time 5. Uber Data Analytics Project On GCP Video Link - https://lnkd.in/daiFAMHT Here's what you will learn: ✅ How to understand raw data ✅ Building Data Model (Lucid Chart) ✅ Writing ETL Script (Python) ✅ Modern Data Pipeline Tool (mage) ✅ SQL queries for analysis 6. Olympic Data Analytics | End-To-End Azure Data Engineering Project Video Link - https://lnkd.in/dEtjqhar Here's what you will learn: ✅ Extract Data from APIs ✅ Learn Azure Services DataBricks, DataFactory, and Synapse Analytics ✅ Writing Spark Code ✅ SQL queries for analysis Tag someone who might find this helpful 👇🏻 Have you ever done any of these projects? Let me know!

Dear Network! Excited to share insights from my latest project focused on conducting comprehensive data analytics on Uber data. 🚗💼 In this project, I utilized a diverse array of tools and technologies, including Google Cloud Platform , Python, Compute Instance, Mage Data Pipeline Tool, BigQuery, and Looker Studio. By leveraging these resources, I was able to extract valuable insights and optimize decision-making processes. Key responsibilities included defining project objectives, conducting data preprocessing, developing Python scripts for analysis, configuring data pipelines, executing complex SQL queries, and designing interactive dashboards. 📈 Reflecting on this project, I gained invaluable experience in data engineering, analytics, and visualization techniques, further honing my self-reliance and problem-solving skills. Check out my GitHub to explore the Python scripts and technical details behind this data-driven solution: https://lnkd.in/erHgkQXr Your feedback and insights are always welcome as I continue to refine and optimize my projects. Let's drive innovation together! 🚀 #DataAnalytics #DataScience #DataEngineering #SQL #BigQuery #GitHub #Innovation #MachineLearning #Internship

Vejam que legal! Parabéns Paulo, pelo engajamento e contribuição! Aqui na Neogrid, usamos Mage, dentre outras ferramentas open source em nossa plataforma de dados. Incentivamos a colaboração com a comunidade e o crescimento de ecossistemas ganha-ganha.

Community Spotlight: Paulo Henrique Zen Messerschmidt, MSc. Eng. 🧙♂️💫 Paulo created two PR’s to enhance Mage’s notification system by allowing notifications to be sent to multiple Microsoft Teams channels, and updated the documentation to hep users implement this new feature effectively. These new features enable better communication, collaboration, and flexibility. Thanks for your contributions, Paulo! 👏 Check out Paulo’s PRs: https://lnkd.in/gttPvBkn https://lnkd.in/gaSfYRwx

Mage Pro Now Integrates with Apache Iceberg! 🧊 Boost your data engineering capabilities with Mage Pro's new integration of Apache Iceberg, which directly addresses common pain points in managing data pipelines and storage. This integration makes workflows more efficient, adaptable, and reliable. Key benefits: 🛡️ Improved Data Integrity: Ensure all data operations are consistent and reliable with full ACID compliance. 🌊 Greater Flexibility: Iceberg supports schema evolution, allowing data structures to adapt without major overhauls or downtime. 🧩 Broader Compatibility: Seamlessly work with popular data processing tools and cloud services like Apache Spark, Flink, Hive, and AWS offerings. 🌐 Join community with 6700+ data engineers: mage.ai/chat 🔥 Express your interest in Mage Pro by filling out this short form: https://lnkd.in/gCcUEP9D

Join our Mage + Iceberg Workshop! Learn hands-on with two powerful open-source tools and see how they’ve helped our clients transform data engineering. Don’t miss out—register today: https://lnkd.in/gXX23HWw #dataengineering #workshop

💡 One-Click Data Platform for CRM Consultancy Firm: Completed another data platform for a consultancy business that onboards new clients with a single click. Data Platform Setup: - Mage on GCP Cloud Run (2CPU/4GB RAM) - Automated CRM data extraction from Close (Pure Python, no fancy tools) - BigQuery + Looker Studio analytics 📊 Real Production Numbers: - Daily records: 150K-170K (~500MB of CRM Data) - Infrastructure cost: ~€6/day - Active pipelines: 5 clients - Cost per client: ~€1.2/day - Current setup can still have the capacity to integrate a new pipeline/client Key Features: - One-click pipeline deployment integrated with the client onboarding process - Zero manual configuration - Instant CRM data integration - Standardized KPI metrics for each client - Automated dashboard setup Result: Consultants now focus on a data-driven strategy instead of manually fetching CRM API data via Postman and struggling to derive insights using Google Sheets, Excel, Airtable etc If you're a consultant struggling with similar CRM data challenges, let's connect! Always happy to share experiences and discuss solutions. #DataPlatform #Automation #DataEngineering #Consulting #CloudCosts #CRM What automation challenges have you solved in your data platforms?