DataGalaxy’s Post

DataGalaxy now supports Snowflake’s data metrics functions, making it easier than ever for Snowflake users to manage data quality effectively ❄ Learn more about importing Snowflake’s data metrics functions directly into DataGalaxy to keep your data catalog up-to-date with all your predefined and customized Snowflake DMFs: #datacatalog #dataquality #datagovernance

Unlock the power of Data Metric Functions in Snowflake! My latest blog post explores how DMFs can enhance data quality and governance, with practical examples and insights. 🚀 Discover how these built-in and customizable functions can transform your data management strategy. 💡 #Snowflake #DataQuality #DMFs Jason Small Babu Sridharala Rakesh Reddy Velidandla Veeranjaneya Ashok Tiruveedhula Drew Brigham Prakash Jaya (JP) Nellore Abdul Razack Hussain M

Just published my first piece on the Snowflake Builders Blog - Monitoring Data Quality using Snowflake Data Metric Functions. This is a great feature, now in Public Preview. Thanks to the team at Snowflake for accepting this for publication! #snowflake #dataquality

Great stuff from Barak ... DMFs and Snowflake's data quality solution was a release that really got us excited a few months ago, and is now officially out. Running your data validation using native Snowflake capabilities is a lot more efficient and interestingly is also real-time! It's not trivial to set up so we wrote this guide to help you get started. On our website you can also find a free tool to generate those DMF tests and validate your Snowflake data: https://lnkd.in/gzefuw_h As always, reach out to have a chat! #dataquality #snowflake #datavalidation #datagovernance

📢 Exciting News for Data Enthusiasts! Snowflake has just rolled out a game-changing feature: Dynamic Iceberg Tables. But what does this mean for you if you're not a tech wizard? Let me break it down: 1️⃣ Easier Data Lake Integration Dynamic Iceberg Tables allow you to store massive amounts of data cost-effectively while still being able to analyze and transform it within Snowflake. It's like having a huge, organized warehouse for your data that you can easily access and work with. 2️⃣ Always Up-to-Date Information Imagine having a magic notebook that automatically updates itself with the latest information. That's what Dynamic Iceberg Tables do for your data. No more manual updates or outdated reports! 3️⃣ Flexible Data Processing Whether you need to process data in large batches or handle it as it comes in real-time, Dynamic Iceberg Tables have got you covered. You can switch between these modes with a simple command. 4️⃣ Cost-Efficient Updates Instead of refreshing all your data every time there's a change, Dynamic Iceberg Tables only process what's new or different. This means faster updates and lower costs. 5️⃣ Play Nice with Others These tables use a format that's compatible with other data tools, making it easier to share and collaborate across different platforms. In simple terms, Dynamic Iceberg Tables make handling big data easier, faster, and more cost-effective. It's a big step forward in making data more accessible and useful for businesses of all sizes. Are you excited about this new feature? How do you think it could benefit your organization? #Snowflake #DataInnovation #BusinessIntelligence #TechMadeSimple

Data loading methods in Snowflake are crucial for optimizing performance and efficiency. One bold assertion made in a recent article is that the choice of loading strategy can significantly impact overall data warehousing success. This is an important consideration for developers and data scientists alike. Are some methods really more beneficial than others, or does it all depend on the specific use case? I invite everyone to share their thoughts and experiences on this topic. Let’s spark a conversation about best practices in data loading. What methods have you found most effective? #DataScience #Snowflake #CloudComputing #DataLoading #DataEngineering https://lnkd.in/gKKY4Enp

A few months ago Snowflake released its own native data quality monitoring framework called ... Data Quality Monitoring. 😊 Using Snowflake's native data quality monitoring can be very powerful - it's faster, more efficient, and a lot more secure, but it may also seem daunting to set up and maintain against hundreds and thousands of tables. So, we wrote a guide! Read Barak Fargoun's Guide to Snowflake Data Quality to understand how to set up your first data metric functions (DMFs), allowing you to boost data quality for your Snowflake data. Find the guide here: https://lnkd.in/gi-qtkYk #snowflake #dataquality #dataqualitymonitoring #datacontracts

#DataSuperhero Daan Bakboord shares how Snowflake has made data governance a few clicks easier. Check out his blog post and see how you can set up classifying functionalities directly from #Snowsight.

Immuta Introduces Granular Data Policy Support for Snowflake Iceberg Tables https://lnkd.in/dZhn8z_A #BigData #dataecosystem #event #GranularDataPolicy #Immuta

Data is everywhere, but having it is like owning Legos without any instructions 🤔 You’ve got the pieces, but it's on you to figure out how to put them together to create something meaningful. Gigasheet can help you snap those pieces into place 🙌 https://buff.ly/4dRBOJp #dataprep #bigdata #dataops