Keith Murray’s Post

**** Attention***** ### You Do not wanna Miss this opportunity ### In today’s data-driven world, organizations rely heavily on data warehouses for analytics and decision-making. To address this, modern data warehouses are embracing the power of GenAI to simplify data management and unlock new possibilities. Please join us for the workshop: ‘Modernize your data warehouse using Amazon Redshift’s Zero ETL and GenAI’ on June 11th. Please register using below: https://lnkd.in/gSnAtxcv In this workshop, participants explore the advantages of Zero ETL and how it can supercharge your data warehouse operations. By eliminating the need for complex ETL pipelines, Zero ETL offers a streamlined and efficient data ingestion process, enabling organizations to rapidly load and analyze data from disparate sources. Attendees will gain insights into the architectural principles of Zero ETL, its seamless integration with Redshift, and how it can accelerate time-to-insight while reducing operational overhead. Also, participants learn about Amazon Q integration with Amazon Redshift which can improve developers productivity. Please register using below: https://lnkd.in/gSnAtxcv 

🔥 Are you excited about saving time in your builds with zero-ETL pipelines? 🛠️ Don't miss out on this workshop around the corner on June 11th, 2024! https://go.aws/458b18Q 👩🏿🏫 👨🏫 Developers, check out this workshop, "Modernize your data warehouse using Amazon Redshift’s Zero ETL and GenAI," in which you learn about: 🚀 Advantages of Zero ETL and how it can supercharge your data warehouse operations 🦶 Kicking to the curb your need for complex ETL pipelines ✨ with streamlined and efficient data ingestion process with Zero-ETL, enabling organizations to rapidly load and analyze data from disparate sources. 📚 Walk away with insights into the architectural principles of Zero ETL ✅ its seamless integration with Redshift ✅ and how it can accelerate time-to-insight while reducing operational overhead. 🚀🚀 Bonus: learn about #AmazonQ integration with Amazon Redshift which can improve developer productivity.

Register for this virtual event happening on June 11. In this workshop participants explore the advantages of Zero ETL and how it can supercharge your data warehouse operations. By eliminating the need for complex ETL pipelines, Zero ETL offers a streamlined and efficient data ingestion process, enabling organizations to rapidly load and analyze data from disparate sources. Attendees will gain insights into the architectural principles of Zero ETL, its seamless integration with Redshift, and how it can accelerate time-to-insight while reducing operational overhead. Also, participants learn about Amazon Q integration with Amazon Redshift which can improve developer productivity.

Prophecy 🤝🏻 Databricks. Join this upcoming webinar to learn how to break free from legacy ETL. Register below 👇🏻 https://lnkd.in/gJMkKZJk

In today’s data-driven world, organizations rely heavily on data warehouses for analytics and decision-making. To address this, modern data warehouses are embracing the power of GenAI to simplify data management and unlock new possibilities. Please join us for the workshop: ‘Modernize your data warehouse using Amazon Redshift’s Zero ETL and GenAI’ on June 11th. Please register using below: https://lnkd.in/gSnAtxcv In this workshop, participants explore the advantages of Zero ETL and how it can supercharge your data warehouse operations. By eliminating the need for complex ETL pipelines, Zero ETL offers a streamlined and efficient data ingestion process, enabling organizations to rapidly load and analyze data from disparate sources. Attendees will gain insights into the architectural principles of Zero ETL, its seamless integration with Redshift, and how it can accelerate time-to-insight while reducing operational overhead. Also, participants learn about Amazon Q integration with Amazon Redshift which can improve developers productivity. Please register using below: https://lnkd.in/gSnAtxcv (edited) 

𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐐1: How do you save money with #redshift? 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐐2: How do you use a combination of a data warehouse and data lake for analytical needs? 𝘞𝘦𝘭𝘤𝘰𝘮𝘦 𝘵𝘰 𝘙𝘦𝘥𝘴𝘩𝘪𝘧𝘵 𝘚𝘱𝘦𝘤𝘵𝘳𝘶𝘮! With this, you can query data not only in the Redshift data warehouse but also in a data lake on #s3. 𝐖𝐞𝐥𝐥! 𝐓𝐡𝐚𝐭'𝐬 𝐭𝐡𝐞 𝐩𝐨𝐬𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐲, 𝐛𝐮𝐭 𝐰𝐡𝐚𝐭'𝐬 𝐭𝐡𝐞 𝐮𝐬𝐞 𝐜𝐚𝐬𝐞? Let's say you have a lot of data in the data lake, and the business users are interested in just the aggregated data, for which they use Redshift. Then, you don't need to get all of the data from the data lake into the data warehouse. Just write an "ETL Stored Procedure in Redshift" using Redshift Spectrum to pull data from the data lake S3 and perform the transformations/aggregations to store the aggregated data into a table in Redshift. This way, you avoid storing data in Redshift, which is far more expensive than the data lake. Business users who want to access the detailed data can always use Redshift Spectrum to query the data in the data lake. P.S ✅Version 3 of 𝐬𝐜𝐞𝐧𝐚𝐫𝐢𝐨 𝐛𝐚𝐬𝐞𝐝 𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞𝐝 𝐡𝐚𝐧𝐝𝐬-𝐨𝐧 𝐑𝐞𝐚𝐥-world AWS Data Engineering ( RADE™) program 𝐰𝐢𝐭𝐡 80+ 𝐚𝐦𝐚𝐳𝐢𝐧𝐠 𝐩𝐞𝐨𝐩𝐥𝐞 completed on Oct 5th. ✅𝐈𝐟 𝐲𝐨𝐮 𝐚𝐫𝐞 𝐚𝐜𝐭𝐢𝐨𝐧-𝐨𝐫𝐢𝐞𝐧𝐭𝐞𝐝 and want to get in the next batch, fill the form below to be get invited for the webinar for RADE™ program V4 Click https://lnkd.in/ervbN-zt 𝐔𝐒𝐏: 𝐑𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐬𝐜𝐞𝐧𝐚𝐫𝐢𝐨 𝐛𝐚𝐬𝐞𝐝 𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞𝐝 𝐡𝐚𝐧𝐝𝐬-𝐨𝐧 program ! doc credit - myself :) #aws #dataengineering

𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐐1: How do you save money with #redshift? 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐐2: How do you use a combination of a data warehouse and data lake for analytical needs 𝘞𝘦𝘭𝘤𝘰𝘮𝘦 𝘵𝘰 𝘙𝘦𝘥𝘴𝘩𝘪𝘧𝘵 𝘚𝘱𝘦𝘤𝘵𝘳𝘶𝘮! With this, you can query data not only in the Redshift data warehouse but also in a data lake on #s3. 𝐖𝐞𝐥𝐥! 𝐓𝐡𝐚𝐭'𝐬 𝐭𝐡𝐞 𝐩𝐨𝐬𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐲, 𝐛𝐮𝐭 𝐰𝐡𝐚𝐭'𝐬 𝐭𝐡𝐞 𝐮𝐬𝐞 𝐜𝐚𝐬𝐞? Let's say you have a lot of data in the data lake, and the business users are interested in just the aggregated data, for which they use Redshift. Then, you don't need to get all of the data from the data lake into the data warehouse. Just write an "ETL Stored Procedure in Redshift" using Redshift Spectrum to pull data from the data lake S3 and perform the transformations/aggregations to store the aggregated data into a table in Redshift. This way, you avoid storing data in Redshift, which is far more expensive than the data lake. Business users who want to access the detailed data can always use Redshift Spectrum to query the data in the data lake. P.S ✅𝐒𝐜𝐞𝐧𝐚𝐫𝐢𝐨 𝐛𝐚𝐬𝐞𝐝 𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞𝐝 𝐡𝐚𝐧𝐝𝐬-𝐨𝐧 𝐑𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐀𝐖𝐒 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 ( 𝐑𝐀𝐃𝐄™) program has has over 170+ 𝐚𝐦𝐚𝐳𝐢𝐧𝐠 𝐩𝐞𝐨𝐩𝐥𝐞 in 2024 so far. Onboarding for the Program has begun. ✅𝐈𝐟 𝐲𝐨𝐮 𝐚𝐫𝐞 𝐚𝐜𝐭𝐢𝐨𝐧-𝐨𝐫𝐢𝐞𝐧𝐭𝐞𝐝 and want to get in the program, fill the form below to be get invited for the webinar for RADE™ program Click https://lnkd.in/ervbN-zt 𝐔𝐒𝐏: 𝐑𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐬𝐜𝐞𝐧𝐚𝐫𝐢𝐨 𝐛𝐚𝐬𝐞𝐝 𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞𝐝 𝐡𝐚𝐧𝐝𝐬-𝐨𝐧 program ! doc credit - Myself :) #aws #dataengineering

🌟 5 Proven Ways to Optimize Your ETL/ELT Pipelines 🌟 At Insignyx, we specialize in delivering scalable IT solutions, and optimizing ETL/ELT pipelines is at the core of enabling efficient data workflows. Here are 5 actionable strategies to take your pipelines to the next level: 1️⃣ Streamline Data Extraction Use incremental loads to process only new or updated data, saving time and resources. Leverage parallel processing to fetch data from multiple sources simultaneously. 2️⃣ Optimize Data Transformation Push transformations closer to the source system to minimize transfer volumes. Shift to ELT workflows, performing transformations in robust platforms like Snowflake or Amazon Redshift. 3️⃣ Enhance Data Load Efficiency Utilize batch loading techniques to reduce overhead. Load data in logical partitions (e.g., date ranges) for better throughput. 4️⃣ Monitor and Automate Pipelines Set up real-time alerts and logs to track performance and resolve bottlenecks swiftly. Automate scheduling and retry mechanisms to ensure seamless operations. 5️⃣ Prioritize Performance Tuning Optimize SQL queries and indexing in source databases for faster extraction. Take advantage of cloud-native features like clustering keys in Snowflake or distribution keys in Redshift. At Insignyx, we’re here to empower your business with scalable IT solutions that drive efficiency and innovation. Let’s unlock the full potential of your data pipelines. 💡 #ETL #ELT #DataTransformation #CloudSolutions #Insignyx #Snowflake #AmazonRedshift #EmpoweringBusiness

I wrote an article that explores real-time data ingestion into Snowflake using Change Data Capture. It compares technologies like #Kafka, #Redpanda, and #CockroachDB for data streaming and ingestion. Kafka #Connect plays a key role in integrating these streams with #Snowflake, ensuring scalable, real-time updates to data warehouses. The focus is on #CDC patterns, which capture data changes efficiently and how each tool contributes to a seamless, low-latency data pipeline into Snowflake. This approach unblocks payment processors to monitor transactions and perform reconciliation in real time by utilizing an online transactional data store in conjunction with a data warehouse, ensuring timely and accurate financial tracking with data lineage and audit trail.