Snowflake Cortex: AI-Powered Data at Your Fingertips
Snowflake Cortex provides access to industry-leading AI models, including large language models (LLMs) and vector search functionality. These serverless tools simplify everyday analytics and AI development, all within a single line of SQL or Python.
Source: https://www.snowflake.com/en/blog/use-ai-snowflake-cortex/
Key benefits include:
• Instant Access to AI Models: Snowflake users can leverage specialized machine learning and LLM models without managing expensive infrastructure. • Enhanced Data Insights: With Cortex, users can analyze vast datasets using Snowflake’s powerful AI capabilities, unlocking strategic insights to improve decision-making. • Simplified AI App Development: By removing technical barriers, Cortex democratizes AI access, enabling users of all skill levels to build AI applications.
LLM-Based Models for Unstructured Data (in private preview):
• Answer Extraction: Extract key information from unstructured datasets. • Sentiment Detection: Identify the sentiment in textual data. • Text Summarization: Create concise summaries of lengthy documents for quicker insights. • Translation: Perform large-scale text translation efficiently.ML-Based Models (available soon):
• Forecasting: Automatically forecast time series based on historical data, adjusting for seasonality and scaling. • Anomaly Detection: Detect outliers in time series data, useful for monitoring data pipelines. • Contribution Explorer: Identify key factors contributing to changes in metrics between two time intervals. • Classification: Categorize data into predefined classes to offer recommendations based on trends.
General Purpose Models for Broader Use Cases:
• Complete: Generate text completions using state-of-the-art open-source LLMs like Llama 2. • Text2SQL: Convert natural language queries into SQL, powered by Snowflake’s LLM, similar to the Snowflake Copilot feature. These serverless functions offer out-of-the-box capabilities that can be integrated into analytics workflows and app development in Snowflake. For example, with just a few lines of code, developers can embed these functions into chatbots using Streamlit. This allows Python-savvy users to build secure and powerful LLM applications quickly, often within hours.
Document AI
Document AI (currently in private preview) leverages large language models (LLMs) for seamless data extraction. By utilizing a pre-trained model and a user-friendly interface, customers can process various document types—such as PDFs, Word files, text files, and even screenshots—to quickly obtain answers to their queries. This capability can be scaled to build pipelines that automate data extraction, significantly reducing manual effort and saving time.
Source: https://www.snowflake.com/en/blog/use-ai-snowflake-cortex/
Snowflake Copilot: Your AI-Powered SQL Assistant
Snowflake recently introduced Snowflake Copilot, an AI-driven solution that makes SQL query generation faster and more efficient. With Snowflake Copilot, users can ask data-related questions in plain English, and the AI will generate SQL queries to deliver the desired insights.

Key Features of Snowflake Copilot:
• Text-to-SQL: Users can interact with their data using natural language, eliminating the need for complex SQL coding. • Enhanced Accuracy: The AI continuously refines its understanding of user queries, providing more accurate SQL code suggestions. • Data Exploration: Ask open-ended questions about your data and receive detailed insights without writing complex queries.
The Future of Generative AI with Snowflake
Snowflake is pushing the boundaries of Generative AI with its continuous development of AI tools like Snowflake Cortex AI and Snowflake Copilot. These innovations pave the way for a future where natural language becomes the primary interface for data analysis, enabling businesses to extract more value from their data while maintaining robust governance.
By integrating AI capabilities directly into the data platform, Snowflake empowers users to streamline workflows, reduce processing times, and unlock new levels of productivity—all without needing deep AI expertise.
A Transformative Partnership for the Future
Generative AI, coupled with Snowflake’s powerful data platform, is a game-changer for businesses looking to innovate and scale. Whether it’s enhancing productivity, improving decision-making, or driving customer engagement, Snowflake’s AI solutions are built to transform how enterprises interact with their data.
As AI continues to evolve, so will Snowflake's offerings, bringing more capabilities, deeper insights, and greater efficiencies to businesses worldwide. Ready to experience the future of data analysis with Snowflake and AI? The journey has just begun!
Snowflake + Beinex Partnership
Beinex is a Snowflake Services Partner Premier Tier, and the partnership reaffirms Beinex’s commitment to delivering exceptional data solutions and positions the company at the forefront of industry advancements. Harnessing the true potential of the data, partnership drives innovation and success in the digital era.
Belonging to Snowflake Services Partner Premier Tier, Beinex leverages Snowflake’s advanced capabilities and seamlessly integrates them into its comprehensive data solutions. This enables Beinex to accelerate the pace of Digital Transformation for its clients, providing them with the tools necessary to extract maximum value from their data and thrive in an increasingly data-centric world.
Connect with us for a free demo: https://beinex.com/contact-us/
As a leader in cloud data platforms, Snowflake is at the forefront of integrating AI capabilities. Staying in sync with the latest AI trends, Snowflake is advancing its generative artificial intelligence capabilities by introducing features that do not necessitate specialized AI expertise or the management of a complex infrastructure.
Apparently, Snowflake has recently introduced Snowflake Cortex, which brings powerful AI capabilities that allow businesses to build and deploy AI applications directly within Snowflake’s secure environment. With access to industry-leading AI models, LLMs, vector search, and LLM-powered features, Snowflake Cortex allows users of any skill level to leverage generative AI for valuable, secure insights, simplifying the journey from data to action.

So, whenever I open the workbook or the extract is refreshed, Tableau displays the unique values within the range specified, giving more control over the parameter values displayed.
Multiple Marks Layer Support for Maps
This is an exceptional feature to bring multiple spatial layers and context together to better understand and analyze geospatial data and map views. I will be able to include multiple marks layers from a data source to map visualizations and enhance the geospatial analysis. I can present more context in a single map view and perform further analysis with this feature.
Block Comments in Calculations
Block comments is a simple yet one of the most useful features for me, which Tableau has announced in 2020.4. I often used to add comments in complex calculations for easy understanding in future references. Earlier, only single-line comments were possible, limiting the description I could add. But from now on, I can add comments of any length to calculation windows with block comments by simply starting the comment with /* and ending with */.
What makes it unique is that the new multi-line block comment feature is consistent with other popular programming languages. This feature is an example of Tableau’s on-going effort to provide its customers with an intuitive user experience.
Tableau Server
Web Authoring Enhancements
Starting from Tableau 2020.4, it is possible to author dashboards from the browser just like how we design it in Tableau Desktop. With this web authoring enhancements, I can include Highlight actions, Format Mark Labels, apply filters to worksheets, create fixed sets, and even create extract in my workbooks from the browser itself. I no longer have to make changes from Tableau Desktop and publish it to the server. I can directly do it from the browser itself.
Offline Map Support for Tableau Server
Rendering dashboards with maps is now faster compared to previous versions. Now, I can create maps using the offline map style in web authoring, ensuring the performance of map views in Tableau Server. Offline map support is a great deal for organizations with strict internet access restrictions, assuring that map view access to all its users.
Tableau Server Management (TSM) Improvements
Tableau Server Administration activities like installation, upgrade and backup are now easy like never before. I can retry installation or upgrade from the last checkpoint in case of an unexpected issue or error during installation or upgrade, saving my efforts to obliterate tableau server.
Backups can be performed twice as fast as previous versions, and I can monitor the progress with the new progress bar giving visibility into what step the backup is on and how much time is remaining.
Backups can also be scheduled using TSM command starting from 2020.4 and that is awesome. I no longer need to prepare batch script and depend on the windows task scheduler to schedule the backups on regular intervals; instead, I can schedule it with just a single command.
Multiple Key Activation on Tableau Server Prior to TSM Initialization
During Tableau Server installation, it is now possible to activate multiple license keys prior to TSM initialization. I will be able to save a lot of time by eliminating the need to restart after the installation is completed to activate multiple licenses and experience a smoother installation.
Analytics Extension for Tableau Online
The power of the Analytics extension is now unlocked in Tableau Online too. The feature was already available in Tableau Server, and it helped us dynamically perform advanced analysis with models and functions in R, Python and other platforms.
Analytics extension in Tableau Online significantly enhances the scope of using Advanced Analytics by the common users.
Merge Duplicate External Assets
Earlier, the Database or Table with similar names used to appear as multiple assets within Tableau Catalog. But, the new feature helps me to merge those multiple assets into a single one. I can manage assets easily and keep an organized view of External assets by merging the common ones.
Tableau Prep
Tableau Prep Builder in the Browser
Prepare the data for visualizations from anywhere using a browser! Starting from 2020.4, Tableau is bringing the data prep process into one integrated platform on the web. Now I can easily prepare and manage prep flows from anywhere using a browser.
Conclusion
Tableau is progressively evolving as a single platform for data preparations, visualization, and collaboration with every update and version release.
Author : Firdous Maqbool
Images Courtesy : Tableau

