Jason P.’s Post

🔥 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.

**** 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 

Reposting this webinar on zero ETL and GenAI with Redshift.

Simplify AWS Redshift integration in 4 simple steps: 1. Create connections between AWS Redshift and targets. 2. Prepare a pipeline between AWS Redshift and targets by selecting tables in bulk. 3. Create a workflow and schedule it to kickstart the migration. 4. Share your data with third-party platforms over API Hub. #AWS #CloudComputing #Integration #DataManagement

Elevate your AWS Redshift ETL with Ease Workflow-free, gain operational intelligence in your preferred business intelligence tools, load data from AWS Management into data warehouses, and execute analytical transformations. #Lyftrondata #AWSRedshiftETL #ETL #DataWarehouse

Ready to take your data analytics to the next level? Amazon Redshift can analyze huge volumes of data at a near-limitless scale, but leveraging its immense processing power requires equally large considerations for consistently loading data into the platform. That's where WhereScape comes in. Automate your data migration to Redshift and streamline ETL processes with our built-in best practices. Your data is growing in volume and complexity faster than ever, and we're here to help you scale beyond your wildest expectations. #automation #bigdata #WhereScape #dataautomation 🔍 Want to see it in action? Book a demo now! https://buff.ly/4ccfauQ

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

AWS Glue detects schema changes in your data and updates your ETL jobs automatically. This means smoother data transitions and less time spent managing evolving data. Ready to streamline your data workflows? Contact us today! #DataManagement #SchemaEvolution #ETLAutomation #CloudSolutions #DataProcessing #Fasttrack #FasttrackDataSolutions #AWSCloud

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

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