Blend’s Post

🚀 Exciting News from the Snowflake Summit! 🚀 Snowflake has just launched a new feature: the Snowpark pandas API, allowing you to run your pandas code directly on Snowflake! Enjoy the same pandas experience with the added scalability and security of Snowflake. Here’s why this is a game-changer: 1) Seamless Integration: Just change the import statement and a few lines of code to lift and shift your pandas code to Snowflake. 2) Scalability: Work with much larger datasets without porting to other big data frameworks or using expensive machines. 3) Performance: Runs workloads natively in Snowflake through transpilation to SQL, benefiting from parallelization. 4) Familiar Interface: Offers a pandas-compatible layer that feels natural to Python developers. 5)Security & Governance: Data stays within Snowflake’s secure platform, ensuring consistent access and easier auditing. 6) No Extra Infrastructure: Leverages the Snowflake engine, eliminating the need for additional compute setup and management. check out the docs here - https://lnkd.in/gPWxZvTP Move from prototype to production seamlessly and harness the power of Snowflake with your favorite pandas workflows! 🐼✨ #DataScience #BigData #Python #Pandas #Snowflake #DataEngineering #DataSecurity #SnowflakeSummit #KipiAtSnowflakeSummit #KipiXSnowflake

Hello, community! 👋 I’ve been a long-time user of Databricks and always appreciated how it simplifies working with data through notebooks and PySpark. Recently, I started exploring Snowflake and came across some features that I’d love to see in Databricks as well. A notable one is Streamlit - an open-source tool that allows you to manage dashboards via code directly inside Snowflake. With Streamlit, you can easily craft attractive applications using Python in just a few minutes. Excellent work, Snowflake! This feature is truly commendable. #Databricks #Snowflake #Streamlit #DataAnalytics #DataScience

I completed a Snowflake quickstart on Data Engineering Pipeline with pandas on Snowflake ! Through this quickstart, I was able to showcase how to use Snowflake Notebooks, pandas on Snowflake, Git integration, and Serverless Tasks to build an end-to-end data engineering pipeline. What I Learned : ✍ How to build a Python data pipeline with Snowflake Notebooks ✍ How to aggregate and transform data to create new features with pandas on Snowflake ✍  How to version control and collaborate with Git integration ✍  How to create a Serverless Task to schedule the feature engineering #datascience #dataengineer #Snowflake #DataEngineeringTools

❄️ Headed to Snowflake Data Cloud Summit? ❄️ Join #DataSuperhero Sudhendu Pandey at Dev Day's Lightning Talks for a rapid-fire discussion covering Advanced LLM MLOps, a comparison between Snowflake Cortex ML and Snowpark Python, Smart Meter Data Analytics, and metadata-driven ingestion with schema inference and dynamic tables. 👉 Register here: #kipibi #snowflake #snowflakesummit #datacloud #llm #cortex #KipiAtSnowflakeSummit #KipiXSnowflake

🎉 Exciting Update! 🎉 I'm thrilled to share that I've successfully merged my latest code update into the main branch! 🚀 I fixed a critical issue in the _process_message function where the SQL type check wasn't correctly implemented. Now, the function safely handles SQL responses, ensuring smooth and accurate query processing. Issue Explanation: The problem was with the SQL type check in the _process_message function. Initially, the function was incorrectly checking for the SQL type in the response, leading to errors during query processing. This caused issues in handling SQL responses properly and impacted the overall functionality. Solution: To resolve this, I modified the type check to use the get method for safely accessing the type key in the response dictionary. This ensures that the function correctly identifies and processes SQL responses. After making this change, the function now works seamlessly, improving the reliability and accuracy of query handling. This is my second contribution to open source, and I'm incredibly proud of this milestone. Each project brings new challenges and learning opportunities, and I'm excited to continue contributing to the community! #CodeUpdate #Programming #TechInnovations Snowflake #ProudMoment #OpenSource #CodingLife #SoftwareDevelopment

🚀 I just embarked on my Databricks journey! 📊 Loving how it seamlessly integrates various programming languages, making data analysis smoother and more efficient. 🌟 Excited to leverage its powerful features to streamline workflows and extract actionable insights. 💡 #Databricks #DataAnalysis #WorkflowOptimization #ActionableInsights

Learn Databricks in detail with recorded video lectures I have covered almost all the hot topics of databricks ✅ Spark Architecture ✅ PySpark Tutorial ✅ Dbutils ✅ Notebooks ✅ Workflows ✅ Delta tables ✅ Unity Catalog ✅ Delta Live Tables ✅ LLM Here is the course link: https://lnkd.in/daGsXPFb #databricks #llm #dlt #jobs #catalog

🔴 Day - 62 of Databricks Learning❗️ If you want to sort your DataFrame in ascending order, but you want the NULL values to appear at the end, this function is your go-to option. ➡️ By using asc_nulls_last(), you'll get your data sorted in ascending order, with any NULL values pushed to the end, making it easier to focus on the actual data first. 📍There's no major performance difference between asc() and asc_nulls_last(). It's just a neat way to clean up your sorting without affecting performance. #Databricks #Dataengineer #LinkedIn #Learning #Careers #Coding #Developer

Did you get your hands on Snowflake Notebooks yet? Experiment with your data, run end to end data engineering pipelines, train ML models, and build cool Streamlit apps all in one place. No more hassle of creating and managing python environments, dependencies, and more! Notebooks support: RBAC to manage access to underlying data assets Native Git integration to version control your code changes Snowflake Copilot integration One-click scheduling How to get started: 📓 Getting started with your first Snowflake Notebook: https://okt.to/ZynYX8 📓 Create and manage Snowflake objects like a pro: https://okt.to/gGSZc1 📓 Data analysis and churn prediction using Notebook: https://okt.to/dOEpUu 📓 Data engineering pipelines using Snowpark: https://okt.to/NgMEJH 📓 End to end ML with Snowpark ML: https://okt.to/pBQbwk

I had the chance to go attend Snowflake Northstar conference, and I am very glad to share that I have completed the Snowflake NorthStar Data engineering Workshop successfully. This workshop was an incredible opportunity deepening knowledge and skills in Snowflake's snowpark. Snowpark API enables querying and processing data at scale in Snowflake and supports libraries for Python,Java and Scala languages. Looking forward to explore more this API and leveraging these new skills. #Snowflake #Snowpark #DataEngineering