BigDATAwire’s Post

Went for the repeat and secured another chip 🏆 dbt Labs wrapped up another great year at Snowflake Summit by being named Snowflake’s 2024 Data Integration Partner of the Year! 🎉 👑 If that wasn't enough to celebrate, we're excited to announce dbt Cloud is now available on the Snowflake Marketplace via their Native App! Whatever you build on dbt can now be deployed and extended to the Snowflake UI. This includes integration of our Semantic Layer capabilities with Snowflake Cortex AI 🧠 Three key data & AI experiences that users will not be able to access on the Snowflake UI: -dbt Explorer: equip your developers with this visual and interactive data catalog to help them understand, troubleshoot, and optimize data pipelines to deliver trustworthy insights.  -Ask dbt: Ask company-relevant questions to this chat bot in natural language to receive accurate and contextual responses provided by dbt Semantic Layer and Cortex AI. -Orchestration observability: enhanced visibility to data analysts to address data freshness issues proactively. Read about all this goodness and more here: https://lnkd.in/gHqPZk_V Learn more about dbt + Snowflake: https://lnkd.in/gENeK5KV Always happy to chat if you’re interested in learning more about dbt Cloud and building your AI roadmap with dbt + Snowflake. 🙌🏾 #dbt #snowflake #DataPipeline #AI #DataManagement

After being amazed by Google Gemini for big query, AWS Sagemaker JumpStart, Microsoft Fabrics, and Databricks AI assistant, today, I found Snowflake Copilot - another AI assistant that supports SQL generation and intelligent data exploration based on the analysis context: https://lnkd.in/g8xBTXUG. We can foresee how LLM will be closely bound with the data analysis process in the near future.

This week I have been having a close look at Snowflake's suite of products. If we had this platform available to us while we were bootstrapping Bodhala, it would have made our lives much easier! There is a lot to like in their products. The Hybrid Table feature looks extraordinarily promising. It composes a transactional table with an analytics table. Data is synced between the row orientated store to the columnar orientated store in a more or less seem less manner. The benefit is OLTP transaction are minimized to a handful of miliseconds. While analytics queries are blazing fast. Also there is no pain synchronizing between your OLTP datsbase and OLAP database. In my opinion this is an extremely powerful feature. Also this presentation by the company behind Mistral is an innovative use of the Mistral LLM to improve data quality in your tables. Quite an impressive use of LLM for such tasks. https://lnkd.in/em6rKaK6

👀Still suffering from data silos😭 ♻️Synchronizing or sharing data through Snowflake or Iceberg tables can unlock new AI and BI capabilities that depend on interlinked data. ⛓️ These capabilities benefit from immediate access to essential data, as well as enhanced governance, virtually unlimited scalability, a variety of programming language options, and an extensive ecosystem of partner solutions compatible with Snowflake. https://okt.to/UZtJjy

This is a good overview of the Google Cloud announcements from Next ‘24 - straight from the source! The post-modern data stack, bundling trend in #data, #analytics, & #AI continues kicked off by Microsoft with Fabric. ▪️What does this mean for Snowflake and Databricks? ▪️What’s up at AWS? ▪️What about the hundreds of data startups? I have thoughts but that’s for another time. 𝐎𝐧𝐞 𝐭𝐡𝐢𝐧𝐠 𝐢𝐬 𝐜𝐥𝐞𝐚𝐫: Everyone 𝐢𝐬 𝐩𝐨𝐬𝐢𝐭𝐢𝐨𝐧𝐢𝐧𝐠 𝐭𝐨 𝐛𝐞 “𝐀𝐈-𝐫𝐞𝐚𝐝𝐲”

don't miss this post from Irina Farooq, BigQuery keeps improving (there is always room for improvement ... even if you're the best analytics service out there). I'll be posting about the new features during the next few weeks. Stay tuned!! #gcp #google #bigquery #dw

Happy to contribute to Deutsche Telekom's perspective in this blog. Please read this blog for a comprehensive overview on BigQuery announcements at Google Next!

#SnowflakeCortex is officially going GA and there couldn't be better timing for my latest blog article 😏 Check out how easily I: 1. Pull data from #Databricks into Snowflake with ease 2. Run sentiment analysis on Yelp reviews using native #SnowflakeCortex sentiment functions 3. Generate new output tables (and aggregate views) in Snowflake for end user consumption All powered through Matillion's Data Productivity Cloud in under 3 minutes 🤯 This is a great walk through for anyone who has a multi-cloud environment but struggles to get data into the right place, or if you are curious on how to use Snowflake's Cortex functions. Let me know what you think! And if you want to know more, feel free to reach out 🤙 https://lnkd.in/gbzxEKaG #Snowflake #Matillion #Data #AI #sentiment #analysis

What is your definition of a data catalog? Recent announcements from industry leaders Snowflake and Databricks have sparked a significant debate - both companies have introduced their open-source catalogs, Polaris and Unity Catalog, respectively, which are set to redefine how we think about data and AI governance across various platforms and formats. In the latest Metadata Weekly installment, Atlan co-founder Prukalpa ⚡ breaks down the different types of data catalogs, shedding light on what each one looks like and how they can best work together within the data estate. Check out the full article here! https://lnkd.in/efkXBpCJ #DataCatalog #OpenSource #DataManagement #Snowflake #Databricks #MetadataManagement

🚀 Discover the latest updates in #AzureDatabricks, including enhanced data governance with #UnityCatalog, data warehousing with #DBSQL and seamless #PowerBI integration, zero-management computation with serverless, and end-to-end AI solutions with #MosaicAI.