❄️🏔️🗺️Less than 2 WEEKS until #SnowflakeSummit2025, resident Snowflake Data Superhero, Piers Batchelor, has already mapped out the top parties.

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Astrato’s LLM Comparison App brings AI and analytics together in a seamless, interactive experience—powered by Snowflake Cortex. 🎥💡Here’s what you can explore:1️⃣ LLM Prototyping: Test and compare outputs from Anthropic's Claude Sonnet, Snowflake Arctic, and Llama 3 side-by-side. Adjust model settings like temperature and system prompts directly in the app.2️⃣ Use Case Tuning: Simplify complex parameters with intuitive BI controls, allowing easy experimentation to find the best model for your use case.3️⃣ Airbnb Review Analysis: Dive into a dedicated sheet to analyze Airbnb review data. Harness the power of LLMs to derive actionable insights directly from customer feedback.Whether it’s picking the right LLM for your budget or tying AI prompts to your warehouse data, this app shows the possibilities of embedded analytics meeting AI.Built to showcase the best of Astrato + Snowflake Cortex, this app is your all-in-one tool for interactive AI experiences. Ready to elevate your data storytelling? 🚀

This is a sample - setup this workbook now,https://help.astrato.io/en/articles/10248639 This workbook provides comprehensive insights into user engagement by tracking active users, session lengths, and workbook usage trends. It enables organizations to monitor daily activity, identify high-usage content, and uncover gaps in adoption to optimize onboarding, improve content strategies, and enhance resource allocation.

Dive into this interactive map showcasing the global community of Snowflake Data Superheroes! Using Cortex, we enriched location data with Longitude & Latitude, bringing the Superheroes' worldwide presence to life.Built in Astrato, the visualization leverages our native heatmap and point map layers to deliver a seamless, dynamic experience. See the power of live data connections and intuitive storytelling in action!Created by our very own Snowflake Data Superhero, Piers Batchelor. Join the ranks, apply here: https://www.snowflake.com/en/data-superheroes/https://www.snowflake.com/en/data-superheroes/

Create, Schedule & Share Paginated Reports and Data Exports

⏰Deliver Business-Critical Insights | Provide users with essential insights precisely when they need it📃Generate, schedule, and distribute reports and data exports seamlessly.✨Leverage AI from Astrato Insights, simplify complex data into actionable summaries.

This People Analytics and Feedback demo dashboard is enhanced with essential capabilities, including writeback functionality and AI-powered sentiment analysis using Snowflake Cortex LLM & ML from Snowpark.The sentiment sheet displays drivers and keyword segmentation to provide deeper insights into employee feedback. The integration of sentiment analytics allows for a nuanced understanding of employee performance and morale.With the ability to easily update data in real-time, this dashboard is a powerful tool for tracking employee engagement, retention efforts, and growth signals, enabling proactive decision-making based on actionable insights.

Having a hard time coming up with a creative name for your signature color? Astrato's GenAI Co-pilot functionality powered by Snowflake and Mistral AI got you covered!

Ask complex questions, get simple answers quickly, without sharing data ⚡Business users ask really challenging questions of their data, LLMs can retrieve answers to those questions superfast. Bring the AI to the data, build powerful Data Apps with AI, using Astrato & Snowflake.

Load data right into Snowflake using this Astrato Data App demo. Reading directly from APIs into Snowflake, presented and initiated, right in Astrato. This Astrato Data App brings you data on demand, froom the Zoopla API, searching the UK property market in real time, storing the data in Snowflake and visualising it instantly in Astrato.Built for you, by Snowflake Data Superhero & Astrato Senior Product Manager, Piers Batchelor.See the full blog, with code: https://medium.com/snowflake/python-data-ingestion-with-snowpark-in-5-steps-d5dbd305ad69

This tool isn't just a dashboard; it's a strategic asset for proactive churn management, making it indispensable for any subscription-based business focused on sustainable growth.Maximize your revenue retention with our cutting-edge Churn Subscription Modeling Data App. Designed for meticulous subscription management, this dynamic tool offers real-time insights into Monthly Recurring Revenue (MRR), customer counts, and Average Revenue Per User (ARPU), all while tracking changes month over month.Visualize MRR distribution across churn risk buckets and gauge churn risk by account manager with our intuitive graphs. The app highlights crucial metrics like Risk Adjusted MRR and Preserved MRR, ensuring you can quickly pivot strategies to bolster customer retention.

This "Snowpark for Python" powered data app runs budget allocations against a linear regression model to predict future ROI (Return On Investment) of variable advertising spend budgets across multiple channels including search, video, social media, and email using Snowpark for Python and scikit-learn.

This app uses an input form and Snowpark to deliver advanced forecasting. Simply enter the product category and measure that you want to forecast, along with the time frame you are looking for.Behind the scenes, a Snowpark UDTF with the forecasting procedure 'Prophet' (by Facebook) calculates an advanced forecast. Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well.

Easily identify hotspots in time using gradient color scales. See the lows and highs of consumption, and filter down for more detail on specific time periods for in-depth insights!