Latest news with #CarlPerry
Business Wire
6 days ago
- Business
- Business Wire
Sigma Launches Native Semantic Layer Integration and AI SQL Capabilities on Snowflake AI Data Cloud
SAN FRANCISCO--(BUSINESS WIRE)--Sigma, the industry-leading analytics platform with unique cloud data platform writeback capabilities, today announced at Snowflake Summit 2025, two major platform innovations in partnership with Snowflake: a first-class integration with Snowflake Semantic Views and support for AI SQL, Snowflake's breakthrough feature for querying unstructured data. Together, these advances enable governed semantic exploration and file-based AI-powered analysis—directly in Sigma's intuitive, spreadsheet-like interface. The combined innovations mark a leap toward unified analytics where both structured metrics and raw human context—contracts, images, PDFs, and text—are queryable side-by-side in a single governed system. 'Sigma is building toward a future where every layer of the data stack speaks the same language—defined once, executed everywhere.' Query Semantic Views Directly in Sigma With this integration, Sigma unlocks warehouse-defined metrics, dimensions, and relationships for downstream analysis, dashboards, and apps – cementing the data warehouse as the single source of truth for semantics. This new integration offers joint customers the most seamless, warehouse-native analytics experience on the market. By partnering with Snowflake, the AI Data Cloud company, Sigma is helping to fully realize a long-held industry vision: semantic logic defined once, governed centrally, and accessed directly in the warehouse—no duplication, no drift. Together, the companies are mobilizing the world's data to help organizations operate in an environment where semantic logic lives natively in the warehouse, not duplicated across disconnected tools. 'Sigma's integration with Snowflake Semantic Views isn't just compatible — it's truly native, built for flexibility, scale, and the next generation of analytics,' said Mike Palmer, CEO of Sigma. 'By meeting the semantic layer where it belongs, we're giving business teams instant access to governed metrics and logic without compromise. And this is just the beginning. From bi-directional syncs to visual semantic exploration, Sigma is building toward a unified modeling experience that brings clarity and control to every layer of the data stack.' 'The integration between Sigma and Snowflake's Semantic Views marks an important step forward in enabling enterprises to leverage the state-of-the-art AI solutions available with Snowflake Intelligence and Cortex Analyst,' said Carl Perry, Head of Analytics, Snowflake. 'This advancement helps our customers maximize the value of their data within Snowflake's AI Data Cloud through AI and BI experiences, creating more efficient and powerful workflows for their teams.' 'This is a major leap forward in delivering a consistent, governed experience powered entirely by Snowflake,' added Palmer. 'Sigma is building toward a future where every layer of the data stack speaks the same language—defined once, executed everywhere.' Bringing Structure to Unstructured Data - Powered by Cortex AISQL Also announced today at Snowflake Summit 2025, is the news that Sigma is among the first analytics platforms to fully support Snowflake AI SQL, a new capability that lets users query unstructured data—like contracts, receipts, product specs, and image files—as if it lived in a table. This news comes on the heels of Sigma's recent launch of its new File Column Type feature, allowing end users to connect unstructured content with structured data for the first time, making complex, real-world workflows fully executable inside Sigma. Teams can upload files with Sigma, run them through Snowflake's powerful LLM-based functions, and analyze the structured results alongside traditional datasets—no pipelines and no special tools required. 'For decades, legacy BI tools assumed your data was clean, structured, and waiting politely in rows and columns,' said Palmer. 'But some of the most important business decisions are made with the messy stuff: legal documents, compliance PDFs, screenshots, receipts, product specs, and annotated images. Historically, those formats required a human in the loop: to read, interpret, and manually extract insights. That's the bottleneck AI SQL removes. Sigma and Snowflake turn human knowledge into scalable systems, unlocking entirely new types of analysis across industries and teams.' 'Every organization recognizes the potential of AI. But too often, harnessing AI means overcoming complex infrastructure, performance limitations, high costs, and a reliance on engineers to build custom pipelines,' said Perry. 'We're removing those barriers, whether it's enabling anyone to analyze and act on all their data with Cortex AISQL or accelerating migrations off legacy systems through SnowConvert AI. By empowering teams to move faster, work smarter, and turn data into real impact, we're reimagining analytics for the AI era.' Snowflake's AI SQL functions analyze the content using LLMs, and Sigma picks up the structured output and renders it live in dashboards or workflows. This unlocks transformative use cases: Process thousands of vendor contracts Review receipts as part of claims workflows Extract key clauses from dense legal agreements Attach evidence to operational data for full-context analytics There's no need for custom pipelines, reformatting, or manual review. Just files in, answers out. Governed, traceable, and ready to use. Joint customers can start using the semantic layer integration immediately through their existing Snowflake and Sigma environments as well as the full support for Cortex AISQL. For more information on Sigma's integration with Snowflake Semantic Views, click here and for more information on Snowflake's AI SQL function, read here. ABOUT SIGMA Sigma is business intelligence built for the cloud. With a spreadsheet UI, business users can work in the formulas and functions they already know, while more technical users can write SQL and apply AI models to data. Sigma queries the cloud warehouse directly, making it incredibly fast and secure—data never leaves the warehouse, and Sigma can analyze billions of rows in seconds. Beyond dashboards and reports, teams use Sigma to build custom data apps, which integrate live data with end user input. Sigma is the first analytics platform to enable data writeback, and continues to lead the market with innovation across AI, reporting, and embedded analytics.
Techday NZ
7 days ago
- Business
- Techday NZ
Snowflake unveils AI tools for data analytics, migration
Snowflake has revealed new artificial intelligence (AI) products aimed at simplifying data analytics and accelerating migration from legacy systems for organisations across Canada and globally. The company announced its expansion of enterprise-grade AI with the introduction of Cortex AISQL and SnowConvert AI, designed to enable customers to extract insights from diverse data types while reducing operational costs and complexity. Cortex AISQL incorporates generative AI directly into database queries, allowing teams to analyse and act on multiple kinds of data—ranging from structured numbers to text, images and audio—while using the SQL syntax familiar to data professionals. The solution is intended to bring what Snowflake describes as "industry-leading performance and up to 60% cost savings when filtering or joining data." Organisations such as Hex, Sigma, and TS Imagine are among those already leveraging the capabilities of Cortex AISQL. SnowConvert AI addresses a common challenge faced by enterprises: moving data from existing warehouse and analytics platforms to modern systems. The tool uses AI automation to ease migrations from providers such as Oracle, Teradata, and Google BigQuery, reducing the need for manual re-coding and lowering the risks typically associated with large-scale data projects. "Every organization recognizes the potential of AI. But too often, harnessing AI means overcoming complex infrastructure, performance limitations, high costs, and a reliance on engineers to build custom pipelines. We're removing those barriers, whether it's enabling anyone to analyze and act on all their data with Cortex AISQL or accelerating migrations off legacy systems through SnowConvert AI. By empowering teams to move faster, work smarter, and turn data into real impact, we're reimagining analytics for the AI era," Carl Perry, Head of Analytics at Snowflake, commented on the new developments. "In capital markets, speed and precision are everything. For years, SQL has been the gold standard for transforming data — and now, with Cortex AISQL, we're extending that power to unstructured text. With AISQL, our teams can analyze documents, extract insights, and build intelligence directly in the language they already know — all without complex engineering workflows. It's a game-changer for how fast we can respond to markets and deliver value to clients, while leveraging the Snowflake architecture for high performing SQL processing," Thomas Bodenski, Chief Operating Officer of TS Imagine, said, sharing his perspective as a customer. Snowflake's Cortex AISQL harnesses generative AI—powered by models from providers such as Anthropic, Meta, Mistral, and OpenAI—to introduce advanced query functions into standard SQL. The result is that data analysts can use AI-powered functionalities within the security perimeter of the existing data cloud, without requiring specialist coding or external tools. According to Snowflake, ongoing performance optimisations have demonstrated between 30% and 70% improvements depending on the dataset, and up to 60% cost savings for certain operations. The integration enables organisations to break down traditional data silos. For example, analysts can merge structured customer data with unstructured data like chat transcripts, images, or social media content, and perform tasks including image classification, call transcript analysis and anomaly detection entirely through SQL queries. SnowConvert AI, meanwhile, is designed to make IT infrastructure upgrades more efficient, automating code conversion, report migration and data validation to streamline the transition to new platforms. By accelerating the code conversion and testing phases by two to three times, the tool is aimed at reducing the overall timeline and resource demands associated with digital transformation. Alongside these tools, Snowflake also announced updates to its platform to further support analytics on open source data formats such as Apache Iceberg tables, and launched Standard Warehouse - Generation 2, which introduces hardware and software improvements to boost analytics performance by 2.1 times over previous editions. With the introduction of these AI-powered features, Snowflake is positioning its data cloud as a central platform for enterprises seeking to modernise analytics and data handling capabilities, and to extract actionable business insights from both structured and unstructured sources.
Business Wire
7 days ago
- Business
- Business Wire
Snowflake Introduces Cortex AISQL and SnowConvert AI: Analytics Rebuilt for the AI Era
SAN FRANCISCO--(BUSINESS WIRE)-- Snowflake (NYSE: SNOW), the AI Data Cloud company, today announced at its annual user conference, Snowflake Summit 2025, major innovations that expand on Snowflake Cortex AI, Snowflake's suite of enterprise-grade AI capabilities, empowering global organizations to modernize their data analytics for today's AI landscape. Snowflake is unveiling SnowConvert AI, an agentic automation solution that accelerates migrations from legacy platforms to Snowflake. With SnowConvert AI, data professionals can modernize their data infrastructure faster, more cost-effectively, and with less manual effort. Once data lands in Snowflake, Cortex AISQL (now in public preview) then brings generative AI directly into customers' queries, enabling teams to extract insights across multi-modal data and build flexible pipelines using SQL and AI — all while providing best‑in‑class performance and cost efficiency. "Every organization recognizes the potential of AI. But too often, harnessing AI means overcoming complex infrastructure, performance limitations, high costs, and a reliance on engineers to build custom pipelines,' said Carl Perry, Head of Analytics, Snowflake. "We're removing those barriers, whether it's enabling anyone to analyze and act on all their data with Cortex AISQL or accelerating migrations off legacy systems through SnowConvert AI. By empowering teams to move faster, work smarter, and turn data into real impact, we're reimagining analytics for the AI era." 'In capital markets, speed and precision are everything. For years, SQL has been the gold standard for transforming data — and now, with Cortex AISQL, we're extending that power to unstructured text,' said Thomas Bodenski, Chief Operating Officer, TS Imagine. 'With AISQL, our teams can analyze documents, extract insights, and build intelligence directly in the language they already know — all without complex engineering workflows. It's a game-changer for how fast we can respond to markets and deliver value to clients, while leveraging the Snowflake architecture for high performing SQL processing." Snowflake Provides Generative AI-Powered SQL Functions to Help Analysts Do More, Faster Snowflake helps customers leverage generative AI through familiar SQL queries, redefining how organizations analyze data. Snowflake Cortex AI has already enabled customers to build and deploy advanced AI models, apps, and agents within the security perimeter of the AI Data Cloud. Now, Cortex AISQL marks the next leap forward by leveraging generative AI to create powerful new query capabilities, effectively turning every data analyst into an AI engineer. Cortex AISQL is powered by leading models from Anthropic, Meta, Mistral, OpenAI, and others, coupled with core functionality and performance optimizations already built directly into Snowflake's SQL engine. With Cortex AISQL performance optimizations (now in private preview), enterprises now gain performance improvements ranging from 30-70% depending on datasets, with up to 60% cost savings when filtering or joining data across thousands of records, empowering them to scale their analytics capabilities for strategic decision-making. Traditionally, SQL has been limited to structured and semi-structured data, leaving analysts dependent on developers to access insights from unstructured sources. Cortex AISQL changes this by enabling teams to query all data types — from traditional rows and columns of numbers to text, images, audio, and more — all while using SQL, the universal language they already know and love for managing data. By harnessing SQL with AI-powered functions in Snowflake, analysts can now readily access and analyze multi-modal data at scale, eliminating data silos, consolidating tools, and combining traditional structured data with unstructured sources. This includes enriching customer tables with chat transcripts, correlating sensor readings with inspection photos, and merging sales figures with social media sentiment — enabling analysts to classify images, extract insights from call transcripts, and detect anomalies with ease. The result is a fully integrated SQL experience across all data, unlocking deeper insights, faster decisions, and accelerated innovation without the need for specialized AI skills or external services. Cortex AISQL delivers unified intelligence across the entire organization. Snowflake Accelerates Time to Value with AI-Powered Migrations With SnowConvert AI, Snowflake is making one of the most tedious and time-consuming parts of digital transformation — data warehouse migrations, business intelligence (BI) migrations, and ETL migrations — faster and smarter, without introducing additional risk factors. With data ecosystem migration agents powered by Snowflake Cortex AI, SnowConvert AI enables organizations to quickly and easily move from legacy data warehouses like Oracle, Teradata, Google BigQuery, and other cloud data platforms to Snowflake. By automating the conversion of code, BI reports, ETL tools, and validating the converted code and migrated data efficiently, SnowConvert AI streamlines the migration process for data engineers. SnowConvert AI goes beyond just database migrations, allowing customers to migrate their entire data ecosystem, while staying seamlessly supported and without disrupting critical workflows — ultimately reducing risk, costs, and complexity at every step. SnowConvert AI makes the code conversion and testing phases 2-3 times faster, significantly reducing time-to-delivery and speeding up modernization efforts. By accelerating the path to modernization, Snowflake shortens the time between intention and insight, so organizations can minimize migration timelines and start generating insights that drive results sooner. Global Enterprises Unlock Comprehensive Analytics Across All Data Snowflake's unified approach to analytics represents a fundamental shift in how organizations analyze their data. Snowflake is also unveiling innovations to Snowflake's unified platform that enables enterprises to process all their data, including open formats like Apache Iceberg ™ tables 1, with remarkable efficiency. In addition, Snowflake announced Standard Warehouse - Generation 2 (now generally available) with next-generation hardware and software optimizations to deliver 2.1x 2 faster analytics performance and 1.9x 3 faster analytics performance than Managed Spark. Snowflake customers can now unlock faster AI-powered insights from all their data — wherever it lives. Learn More: Dive deeper into how Snowflake Cortex AISQL is bringing the power of AI directly to data analysts in this blog post. Explore more of the ways Snowflake is expanding its analytics capabilities in this blog post. Check out all the innovations and announcements coming out of Snowflake Summit 2025 on Snowflake's Newsroom. Stay on top of the latest news and announcements from Snowflake on LinkedIn and X, and follow along at #SnowflakeSummit. 1 "Apache Iceberg' is a registered trademark or trademark of the Apache Software Foundation in the United States and/or other countries. 2 Snowflake improvements based on performance of core analytics workloads measured as of May 3, 2024 using Standard Warehouse and May 2, 2025 using Gen2. 3 Performance results based on core analytics workloads on 2XL Gen2 warehouse and comparable warehouse on Managed Spark as of May 2, 2025. Forward Looking Statements This press release contains express and implied forward-looking statements, including statements regarding (i) Snowflake's business strategy, (ii) Snowflake's products, services, and technology offerings, including those that are under development or not generally available, (iii) market growth, trends, and competitive considerations, and (iv) the integration, interoperability, and availability of Snowflake's products with and on third-party platforms. These forward-looking statements are subject to a number of risks, uncertainties and assumptions, including those described under the heading 'Risk Factors' and elsewhere in the Quarterly Reports on Form 10-Q and the Annual Reports on Form 10-K that Snowflake files with the Securities and Exchange Commission. In light of these risks, uncertainties, and assumptions, actual results could differ materially and adversely from those anticipated or implied in the forward-looking statements. As a result, you should not rely on any forward-looking statements as predictions of future events. © 2025 Snowflake Inc. All rights reserved. Snowflake, the Snowflake logo, and all other Snowflake product, feature and service names mentioned herein are registered trademarks or trademarks of Snowflake Inc. in the United States and other countries. All other brand names or logos mentioned or used herein are for identification purposes only and may be the trademarks of their respective holder(s). Snowflake may not be associated with, or be sponsored or endorsed by, any such holder(s). About Snowflake Snowflake is the platform for the AI era, making it easy for enterprises to innovate faster and get more value from data. More than 11,000 companies around the globe, including hundreds of the world's largest, use Snowflake's AI Data Cloud to build, use, and share data, apps and AI. With Snowflake, data and AI are transformative for everyone. Learn more at (NYSE: SNOW).
Yahoo
18-02-2025
- Business
- Yahoo
State Senate panel foresees easy path for bill to protect Uber, Lyft from product liability lawsuits
State Sen. Carl Perry, R-Aberdeen, speaks on the South Dakota Senate floor on Jan. 21, 2025. (Makenzie Huber/South Dakota Searchlight) PIERRE — A bill to shield ride-hailing companies from product liability lawsuits earned unanimous support from a South Dakota legislative committee. The Senate Judiciary Committee took up that legislation, Senate Bill 166, on Tuesday at the Capitol. The idea, according to Republican Sen. Carl Perry of Aberdeen, is to make sure companies like Uber or Lyft aren't held accountable under civil law in a manner that matches the standard applied to products like toothpaste, coffee makers or car seats. The one-sentence bill says product liability 'may not be maintained' against a 'digital network.' In a South Dakota law, that means ride-hailing companies. Under a bill passed in 2016 with the support of app-based taxi companies like Uber and Lyft, a 'digital network' is defined as 'any online-enabled application, software, website, or system offered or utilized by a transportation network company that enables a prearranged ride with a transportation network company driver.' In 2022, state lawmakers passed a bill clarifying that drivers for such companies are independent contractors, not employees. That put the state on the side of tech companies in an issue that's divided state legislatures and voters for years. California voters, for example, passed a measure in 2020 to classify such drivers as independent contractors in a campaign that received financial backing from tech companies. A lawsuit from labor groups attempted to overturn the law and won in a lower court, but the state's supreme court overturned the lower court's decision last summer. Minnesota lawmakers, however, advanced worker protections for Uber drivers last year. Washington state and New York also have minimum pay provisions for such drivers. Perry called his legislation 'a common sense bill to further clarify the rule in an already regulated industry.' Uber Industries lobbyist Grace Beck told committee members the ride-hailing business is fundamentally different from one that makes things. 'These companies do not manufacture, design or sell physical products,' she said. 'It's only a phone app. Uber operates a digital platform that offers an important service to South Dakotans.' SUPPORT: YOU MAKE OUR WORK POSSIBLE Brad Nail, a public policy lobbyist for Uber, pointed out that state law requires a ride-hailing company to carry $1 million in liability insurance to cover 'death, bodily injury, and property damage' to cover potential issues that might arise during a ride. 'The bill before you does not change that, and does not decrease the amount of insurance required,' Nail said. The bill isn't tied to a South Dakota case, but to what Nail called 'a novel situation that has arisen in other states' where plaintiffs have tried to sue under product liability laws. Nail didn't elaborate, but a case filed last fall in California alleges that the company failed to design an app that considers or adequately protects against the possibility of sexual assault by a driver. Nail told lawmakers the $1 million liability coverage required by state law renders product liability lawsuits unnecessary. The committee heard no opposition testimony. It voted unanimously to send SB 166 to the Senate floor. It then certified the bill for the consent calendar, meaning the Senate will vote for or against it without debate as part of a package of uncontroversial bills, unless any senator asks for the bill to be moved to the regular calendar. Sen. Amber Hulse, R-Hot Springs, said the bill 'makes sense.' 'Obviously there wasn't any opposition testimony,' Hulse said. 'If there was a problem, I would assume somebody would be up here saying it.' SUBSCRIBE: GET THE MORNING HEADLINES DELIVERED TO YOUR INBOX
USA Today
11-02-2025
- Health
- USA Today
Aberdeen GOP Sen. Carl Perry introduces bill to cap fluoride in water in South Dakota
Aberdeen GOP Sen. Carl Perry introduces bill to cap fluoride in water in South Dakota Show Caption Hide Caption The truth about fluoride Fluoride is present in dental products like toothpaste, protecting teeth from cavities and preventing bacteria in the mouth. It is also added to public water supplies. unbranded - Lifestyle A South Dakota bill, SB 133, would give municipalities control over fluoride levels in their drinking water. Proponents of the bill cite potential changes in federal fluoridation policy and concerns about excessive fluoride consumption. A bill that would make fluoridation of drinking water optional for South Dakota cities is headed to the Senate chamber. Cities add fluoride to tap water to prevent tooth decay and strengthen teeth, in South Dakota and throughout the United States. Research shows that community water fluoridation reduces cavities by around 25%, and the Centers for Disease Control and Prevention calls water fluoridation one of the top 10 public health achievements of the 20th century. Senate Bill 133, introduced by Aberdeen Republican Sen. Carl Perry, would allow municipalities controlling a public water supply or a person controlling a private water supply to determine the amount of fluoride in their drinking water. Currently, the South Dakota Department of Agriculture and Natural Resources regulates fluoride levels and testing methods. The bill would cap water fluoridation at 4 milligrams per liter, the limit already imposed by the U.S. Environmental Protection Agency. South Dakota cities would not be required to include any fluoride in the municipal drinking water, so some could discontinue the practice. Coming to historic Ward Hotel: LaRue's offers authentic French pastries, cuisine Skeptics of fluoridation benefits have raised concerns about excessive fluoride consumption for years. President Donald Trump tapped outspoken water fluoridation opponent Robert F. Kennedy Jr. to lead the U.S. Department of Health and Human Services. The U.S. Senate has yet to confirm his nomination. Perry told lawmakers that the federal government could change fluoridation policy under Kennedy's influence, so South Dakota 'should be ahead of that.' Several dental and medical organizations opposed the bill, saying it would lead to more health problems in the state. South Dakota Municipal League, South Dakota Association of Rural Water Systems, South Dakota Department of Health, and South Dakota Department of Agriculture and Natural Resources also opposed the bill. Sub sandwiches, hot and cold: Jersey Mike's opens new sub shop in Aberdeen Ensuring access to safe and reliable drinking water is the 'primary' public health initiative for the state Department of Agriculture and Natural Resources, said Mark Mayer, water director for the department. 'We feel that community water system fluoridation is one of the safest, most beneficial and cost effective ways to prevent tooth decay,' Mayer said. The legislation passed out of the Senate Health and Human Services Committee 6-1 'without recommendation' after an attempt to defeat the bill failed. That means that a majority of senators must agree to place it on the calendar before it's debated, said Brookings Republican Sen. Tim Reed, otherwise the bill dies. South Dakota Searchlight is part of States Newsroom, the nation's largest state-focused nonprofit news organization.
