Hevo Data’s Post

🚀 New Blog Alert! 🚀 Are you looking to supercharge your query performance? Check out my latest blog post on the Dremio blog: "The Who, What, and Why of Data Reflections and Apache Iceberg for Query Acceleration". In this post, I delve into: 🔹 What Data Reflections are and how they work 🔹 The role of Apache Iceberg in modern data architecture 🔹 How these technologies can significantly speed up your queries This read is a must if you're working with large datasets and complex queries! Don't miss out on the opportunity to optimize your data workflows and enhance performance. Read it now and let me know your thoughts! Link in comments! 💡👇 #DataEngineering #DataAnalytics #DataLakehouse

Level Up Your Data Lake with Apache Iceberg Following my previous articles on Iceberg's features and building unified lakehouses, I’m excited to share a practical guide on migrating from #ApacheHive to #ApacheIceberg! In this article, I cover: 🔹 Seamless migration with Table Redirection. 🔹 Lightweight Catalog Migration with Iceberg Migration CLI. 🔹 Flexible CTAS & INSERT INTO operations. Read the full article on Medium : https://lnkd.in/diFkJwZu Let’s future-proof our data infrastructure together! #DataEngineering #DataLakehouse #BigData

Going on now: Data Engineer's Lunch 109: Building a Data Lakehouse on your Laptop Workshop https://lnkd.in/gFZGBk-B In this hands-on workshop, participants will embark on a journey to construct their very own data lakehouse platform using their laptops. The workshop is designed to introduce and guide through the setup and utilization of three pivotal tools in the data lakehouse architecture: Dremio, Nessie, and Apache Iceberg. Each of these tools plays a crucial role in enabling the flexibility of data lakes with the efficiency and ease of use of data warehouses, aiming to simplify and economize data management.

What is Delta Lake Uniform and how to use it to make data lake Interoperable? Delta Lake UniForm is a universal format that aims to streamline interoperability across data lake environments like Delta Lake, Apache Iceberg, and Apache Hudi. It is designed to unify and simplify data access across various open data lake formats. Why Use Delta Lake UniForm? 1. Enhanced Portability: Ensures data can be easily moved and accessed across different data lake formats without compatibility issues. 2. Improved Reliability: Maintains ACID transactions, audit history, and other critical features across platforms. 3. Optimized Performance: Delivers efficient query performance by leveraging uniform metadata handling and optimized data layouts. Benefits: - Flexibility: Quickly adapt to changing data and query patterns without extensive reconfiguration. - Scalability: Efficiently scale data lakes from terabytes to petabytes while maintaining high performance and reliability. - Consistent Metadata: Uses a standardized approach to handle metadata, ensuring consistent performance and reliability across platforms. #databricks #dataengineering #WhatsTheData

From ETL to T.

Are you struggling with poor data quality, redundant datasets, soaring data warehouse costs, and slow time-to-insights that come with multi-hop and medallion architectures using batch pipelines? Shift Left the data preparation, cleaning, and schemas to the point where data is created to build fresh, trustworthy datasets once – and be used as streams for operational use cases or Apache Iceberg tables for analytical use cases. Want to learn more? Stream Adam Bellemare's lightboard video: https://lnkd.in/e9MQDFVk

🚀 Unleash the Power of 3D Data Visualization! 🌐 Don’t let traffic spikes throw you off balance! ⚖️ Find out how to maintain flawless performance, even as data volumes soar. 📊 Discover NGINX load balancing to boost your system’s performance to new heights! 📈 🔍 Dive into our latest blog where we break down the essentials: Postgres for robust geospatial data management 🗺️1 GeoServer for seamless data sharing 🔄 Cesium for stunning 3D mapping visuals 🌟2 Learn how to set up NGINX for optimal load distribution and get insights on monitoring and scaling your architecture for growing demands. 💡 👉 Sneak Peek: “NGINX stands as a guardian, ensuring smooth sailing across your digital oceans.” 🌊 🔗 [https://lnkd.in/gCPC9Auy] 📢 Follow Abhinav Bhaskar for more tech insights and updates! #NGINX #LoadBalancing #3DDataVisualization #Geospatial #TechTips

Ready to enhance your data lake platform? Join me in exploring the integration of Apache Flink and Apache Iceberg. The talk was originally presented at our recent Apache Flink TLV Meetup event, hosted at Panorays. In this video, you'll learn: ✨ Seamless integration techniques: Discover how to effectively combine the power of #Flink and #Iceberg. ⚡ Efficient data ingestion: Implement continuous ETL pipelines and database mirroring with Flink. 🔍 Advanced querying: Utilize Iceberg's querying capabilities to enhance data management and performance. 📊 Streaming and batch execution insights: Leverage Flink's dual processing capabilities for optimal efficiency. Watch now: https://ow.ly/iarY50SsomF

𝐇𝐚𝐯𝐞 𝐲𝐨𝐮 𝐞𝐯𝐞𝐫 𝐰𝐨𝐧𝐝𝐞𝐫 𝐰𝐡𝐚𝐭 𝐢𝐬 𝐨𝐩𝐞𝐧 𝐝𝐚𝐭𝐚 𝐟𝐨𝐫𝐦𝐚𝐭𝐬, 𝐰𝐡𝐲 𝐭𝐡𝐞𝐫𝐞 𝐚𝐫𝐞 𝐦𝐚𝐧𝐲 𝐚𝐧𝐝 𝐰𝐡𝐢𝐜𝐡 𝐨𝐧𝐞 𝐬𝐡𝐨𝐮𝐥𝐝 𝐲𝐨𝐮 𝐮𝐬𝐞 ? The need for efficient data management and processing in data lake has given rise to several advanced open data formats, each with unique features and advantages. Among the most prominent are 𝐀𝐩𝐚𝐜𝐡𝐞 𝐇𝐮𝐝𝐢, 𝐀𝐩𝐚𝐜𝐡𝐞 𝐈𝐜𝐞𝐛𝐞𝐫𝐠, and 𝐃𝐞𝐥𝐭𝐚 𝐋𝐚𝐤𝐞. These formats provide robust solutions for data lakehouse environments, enabling efficient querying, data skipping, and transactional integrity. If you are looking to understand what are they, their origins, architectural details, real-world applications, and comparative advantages of these technologies, then this article is for you.

I'm thrilled to share my latest article: "Unveiling the Invisible: Tracing Apache Airflow Workflows with OpenTelemetry." In the fast-paced world of data engineering, gaining deep insights into your workflows is essential for optimization and troubleshooting. In this piece, I explore how integrating OpenTelemetry with Apache Airflow can enhance observability, providing a detailed view of task executions and data flows within your pipelines. 🔍 What you'll learn: The importance of observability in complex workflows How OpenTelemetry complements Apache Airflow Step-by-step guide to integrating these tools Best practices for tracing and monitoring If you're looking to make the invisible aspects of your data pipelines visible and actionable, this article is for you. 👉 Read it here: Unveiling the Invisible: Tracing Apache Airflow Workflows with OpenTelemetry I'd love to hear your thoughts or experiences with Airflow and OpenTelemetry. Feel free to share your insights or ask any questions! #ApacheAirflow #OpenTelemetry #DataEngineering #Observability #DataPipelines