Dawiso’s Post

🚀 A quick guide to Delta & Iceberg tables in Snowflake data platform for Data Architects! 🚀 Navigating the world of table formats in Snowflake? Our latest guide breaks down key concepts you need to know about Delta and Iceberg support in Snowflake. 🔍 What's Inside: ✨ Key Snowflake Objects: Understanding Storage Integration, Stage, and External Volumes. ✨ External Tables: Learn why they’re considered second-class citizens in Snowflake. Delta Tables: How Snowflake handles Delta format with some limitations. Iceberg Tables: Advanced integration options for seamless data management. ✨ Summary: Quick comparison to help you choose the right table format for your needs. Don't miss out on this essential guide to optimizing your data architecture in Snowflake! 👉 Swipe through the carousel and level up your data game! #blackstraw #data_engineering #snowflake

🌟 𝐃𝐚𝐭𝐚 𝐌𝐨𝐝𝐞𝐥𝐥𝐢𝐧𝐠 𝐈𝐧𝐬𝐢𝐠𝐡𝐭: 𝐒𝐭𝐚𝐫 𝐒𝐜𝐡𝐞𝐦𝐚 𝐯𝐬. 𝐒𝐧𝐨𝐰𝐟𝐥𝐚𝐤𝐞 𝐒𝐜𝐡𝐞𝐦𝐚 🌟 Understanding the difference between Star Schema and Snowflake Schema is pivotal for efficient data architecture. 🔸 𝐓𝐡𝐞 𝐒𝐭𝐚𝐫 𝐒𝐜𝐡𝐞𝐦𝐚 offers simplicity and speed, with a centralized fact table surrounded by dimension tables. It's the go-to for a clear, straightforward design that promises faster query performance and easier maintenance. Perfect for businesses looking for quick insights from their data. 🔹 𝐎𝐧 𝐭𝐡𝐞 𝐟𝐥𝐢𝐩 𝐬𝐢𝐝𝐞, 𝐭𝐡𝐞 𝐒𝐧𝐨𝐰𝐟𝐥𝐚𝐤𝐞 𝐒𝐜𝐡𝐞𝐦𝐚 provides a more normalized form. It's a bit complex with multiple tables but shines in reducing data redundancy and saving storage space. It's ideal for dynamic businesses with evolving data needs, offering greater flexibility and efficiency in storage. Both have their merits: ✅ Star Schema excels in performance and simplicity. ✅ Snowflake Schema stands out in normalization and flexibility. Infographic credit: Gina Acosta 🌟 #DataWarehousing #StarSchema #SnowflakeSchema #DataArchitecture #BusinessIntelligence #DataStrategy #data #datanalytics

Hi all #Snowflake Data Jedis! If you are interested on #Observability and check some of the features that Snowflake offers, and how to use them, you are on the right reading place! On my publication on Snowflake, I teach you how to use some Dataobjects, from the big wideband available, in order to track all #DML actions done in your database tables in a structured way. All this, only using #SQL commands. I invite you to join with me, you only read it and enjoy in an easy way how to achieve big things with the less effort in Snowflake. https://lnkd.in/drSEi6Ze

Exciting Opportunity Alert! Join us on June 13th for a captivating webinar hosted by ORI, where we delve into the remarkable success story in Pima County. **Unlock the Secrets to Success with Qlik: A Pima County Case Study** In this exclusive webinar, you'll discover firsthand how Pima County leveraged Qlik to revolutionize their data analytics journey, driving impactful insights and transformative outcomes. From enhancing operational efficiencies to elevating decision-making processes, their journey with Qlik offers invaluable lessons for organizations seeking to harness the power of data. **Why Attend? ** - Gain insights into real-world applications of Qlik in a governmental setting. - Learn best practices and strategies for successful implementation and utilization of Qlik. - Engage with industry experts and thought leaders to address your burning questions and challenges. - Network with peers and professionals from diverse sectors to exchange ideas and experiences. Don't miss out on this exceptional opportunity to learn, connect, and elevate your data analytics game! Register now to secure your spot. #Qlik #DataAnalytics #SuccessStory #Webinar #ORI #PimaCounty #BusinessIntelligence

#Snowflake is one of the most commonly used data warehouses. Activities requiring orchestration are usually part of a larger data pipeline that involves ingestion, transformation, and reverse #ETL activities. In this blog we are zooming into one part of the data pipeline: orchestrating Snowflake with Control-M orchestrating the following activities.

🌟 Data Engineering Tip! 🌟 📊 When designing your data warehouse, choose the right schema: Star Schema for simplicity and quick queries or Snowflake Schema for normalization and storage efficiency. 🚀 🔍 The right design enhances performance and scalability! 💡 #DataDude #DataEngineering #DataWarehousing #StarSchema #SnowflakeSchema #DataScience

💡 Snowflake ETL Tip: Accelerate Data Loading with Snowpipe Real-Time Data Ingestion! ⚡️ To efficiently load real-time data into Snowflake, leverage Snowpipe. Snowpipe is a continuous data ingestion service that automatically loads streaming data into Snowflake tables, enabling near-real-time analytics. Here's an example code snippet showcasing how to use Snowpipe for real-time data ingestion: -- Create an External Stage for the Snowpipe CREATE STAGE my_stage URL = 's3://my-bucket' CREDENTIALS = (AWS_KEY_ID='<AWS_KEY_ID>', AWS_SECRET_KEY='<AWS_SECRET_KEY>'); -- Create a Pipe for the Snowpipe CREATE PIPE my_pipe AUTO_INGEST = TRUE AS COPY INTO my_table FROM @my_stage FILE_FORMAT = (TYPE = 'JSON'); -- Ingest real-time data by putting files in the Snowpipe stage (e.g., S3 bucket) #Snowflake #ETL #Snowpipe #RealTimeData #StreamingAnalytics #TechTips #DataIngestion #LORSIVTechnologies By utilizing Snowpipe in Snowflake, you can automate the ingestion of real-time data, enabling near-instant analytics and reducing the latency between data arrival and insights generation. Share your experience or tag a colleague interested in leveraging real-time data ingestion! Don't forget to follow #LORSIV

💡 Snowflake ETL Tip: Accelerate Data Loading with Snowpipe Real-Time Data Ingestion! ⚡️ To efficiently load real-time data into Snowflake, leverage Snowpipe. Snowpipe is a continuous data ingestion service that automatically loads streaming data into Snowflake tables, enabling near-real-time analytics. Here's an example code snippet showcasing how to use Snowpipe for real-time data ingestion: -- Create an External Stage for the Snowpipe CREATE STAGE my_stage URL = 's3://my-bucket' CREDENTIALS = (AWS_KEY_ID='<AWS_KEY_ID>', AWS_SECRET_KEY='<AWS_SECRET_KEY>'); -- Create a Pipe for the Snowpipe CREATE PIPE my_pipe AUTO_INGEST = TRUE AS COPY INTO my_table FROM @my_stage FILE_FORMAT = (TYPE = 'JSON'); -- Ingest real-time data by putting files in the Snowpipe stage (e.g., S3 bucket) #Snowflake #ETL #Snowpipe #RealTimeData #StreamingAnalytics #TechTips #DataIngestion #LORSIVTechnologies By utilizing Snowpipe in Snowflake, you can automate the ingestion of real-time data, enabling near-instant analytics and reducing the latency between data arrival and insights generation. Share your experience or tag a colleague interested in leveraging real-time data ingestion! Don't forget to follow #LORSIV

Do you find scaling your big data projects complex? Maybe it’s time to switch to a new data warehousing system. #GoogleBigQuery, a fully managed service, can simplify the migration process by redefining workflows that align with warehouse operations. Read our white paper to learn key design aspects that would help in the successful implementation of #BigQuery. Author: Mahesh Reghupathy https://lnkd.in/dR_9JqMD #WhitePaper #BigData #DataScience #GoogleAnalytics #DataModeling #DataWarehouse #DataStrategy #DataPrivacy #DataShuffling #DataStructures #DatabaseManagement #DataWarehouse #DatabaseApplication #DataStorage #DataTypes #DataWorkflow #GSPANN