SoftServe, a premier IT consulting and digital services provider, today released its findings of the latest study commissioned to evaluate current Generative AI (Gen AI) use across global businesses conducted by research and advisory firm Forrester Consulting. After more than 18 months since the release of ChatGPT and growing availability of Gen AI products, solutions, and services, the study revealed businesses are still experiencing less value than executives expected with only 22% of organizations reported effectively using the technology across all business functions.

Despite falling short of expectations, Gen AI enthusiasm grows unabated according to the global survey of 777 technology purchasing decision-makers involved with their organization’s use of Gen AI. Their responses indicated organizations continue to invest and pursue many use cases in search of ones that will deliver the biggest impact while simultaneously struggling with internal data readiness, governance, and skill development.

Key findings include:

• More than half of decision-makers say their company established business goals for using Gen AI, yet 79% or more are concerned with their organization’s ability to execute those goals with current levels of internal or external expertise.
• Despite 75% or more experiencing Gen AI skill readiness challenges, organizations continue to pile up use cases as most have implemented at least three use cases and will expand the use of two more, including plans to pilot at least one more use case in the next 12-18 months.
• Just 51% of leaders are extremely confident their current strategy will allow them to reach maximum Gen AI value from future use cases, while concurrently, 77% are concerned with their company’s potential to realize business value in either the short or long term.
• Only 42% of organizations have the capabilities to train Gen AI models and a staggering 89% face difficulties preparing business data for Gen AI use.
• Less than one-fourth (24%) have governance plans in place, even though 90% agree adopting a governance plan is imperative to ensuring the responsible use and risk mitigation of Gen AI.

“Despite a swift start to the Gen AI race, many initiatives get stuck in the piloting stages as more organizations realize their data infrastructure isn’t ready to adequately deploy Gen AI technologies beyond the proof-of-concept,” said Alex Chubay, SoftServe’s CTO. “Gaps in skills and knowledge of emerging Gen AI technologies, technical feasibility, and data readiness hinder companies from moving beyond tactical wins in pilot mode to full-scale deployments enabling novel business capabilities and experiences. To make that qualitative leap to the next level, a holistic approach is required to orchestrate business priorities, use cases, and data across the technology ecosystem from the initial strategy down to the final execution.” 

Gaps in Expectations vs. Reality
While respondents agree data is paramount to effective Gen AI strategies, only 3% said their organizations’ models can leverage a full range of six or more types of business data (operational, customer, employee, source code, public, and partner data), which was double the respondent average of three data types used. Moreover, a gap in technical skills persists as 88% say deeper technical expertise is becoming increasingly important for data integration, model optimization, use case development, and further application development.

Crucial External Expertise Needed
Despite the over-abundance of use cases, 80% of decision-makers claim their employees are currently struggling with use case awareness and general understanding of Gen AI complexity and 90% say their organizations need a partner with more advanced technical capabilities to see transformative value in future use cases.
According to the study, companies are looking for partners with accelerated deployment support (89%) and a better understanding of their industry (88%) to help with execution and implementation.

Notable Trends in Gen AI Results
The study revealed organizations reaping substantial value from Gen AI prioritized data, governance, and skill development with help from technical partners and experts. Of four countries surveyed, the U.S. took the lead in unlocking Gen AI value, followed by the UK, Singapore, and Germany, respectively.

Among industries, retail was most likely to harness Gen AI value and train their organization’s models on owned data, while FSI (financial services and insurance) reported more likely to encounter challenges before yielding any Gen AI gains. FSI leaders also reported releasing fewer governance plans than retail and other sectors. Companies across healthcare, life sciences, oil and gas, manufacturing, ISVs, and enterprise technology depicted an even divide in achieving Gen AI value. Separately, larger businesses with revenues greater than $5 billion were less likely to show Gen AI successes due to difficulties organizing the required capabilities needed across expansive hardware, software, and infrastructure landscapes.

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ZettaBlock, an industry-leading, institutional-grade Web3 data infrastructure platform, is proud to announce a new collaboration with the Stellar Development Foundation, the organization that supports the development and growth of the Stellar network, known for facilitating open and accessible financial transactions. This integration is set to redefine the landscape of blockchain development, offering a streamlined path for developers to create not just any Web3 application, but powerful data-driven applications on Stellar, with ease and efficiency.

ZettaBlock and the Stellar Development Foundation are joining forces with a shared goal: to make the blockchain space more accessible and powerful for developers and to open up new possibilities for how financial systems can operate globally. This is about providing the tools and support needed to create applications that are not just scalable and secure, but also truly efficient.

“SDF is excited to work with ZettaBlock in giving our community more intelligence tools to build best-in-class dapps,” said Justin Rice, VP of Ecosystem of the Stellar Development Foundation. “We’re committed to making Stellar the highest quality network for developers to build on, and this integration with ZettaBlock furthers this initiative.”

By leveraging ZettaBlock’s advanced indexing, real-time data, and analytics capabilities alongside Stellar’s robust network for financial transactions, this integration promises to revolutionize the way developers build and deploy dapps.

Developers now have access to a fully managed backend, with rich, actionable on-chain data –  both historical and real-time – but also the ability to seamlessly integrate with private data sources. ZettaBlock empowers developers to swiftly create custom APIs tailored to their specific business needs or dapp logic. With the ability to generate GraphQL endpoints from SQL queries in one click, without the burden of infrastructure overhead, developers can now bring their innovative dapps to the Stellar ecosystem more than 90% faster. 

“We’re thrilled to join forces with Stellar,” said Chi Zhang, CEO and Co-Founder of ZettaBlock. “This collaboration mirrors our mutual dedication to unlocking the full potential of blockchain data for everyone. We’re excited to see the innovative applications that developers on Stellar will create using our comprehensive data platform.”

Get Started with ZettaBlock and Stellar: Build powerful, data-driven applications on Stellar using ZettaBlock’s advanced tools, or discover how our integration can revolutionize your business.

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Tessell, the leading next-generation database-as-a-service (DBaaS) that helps startups and enterprises accelerate data and application modernization journeys at scale, today announced it has been named to the 2nd Annual Redpoint InfraRed 100. This prestigious list highlights the 100 up-and-coming private companies in Cloud Infrastructure, showcasing the future leaders set to revolutionize the market.

Tessell is a cloud-native DBaaS that revolutionizes data infrastructure and management for cloud-born and cloud-defining enterprises and unlocks open source to solve the issue of rising cloud costs. It operates on AWS and Azure to provide high-performance storage capabilities for demanding production workloads. This multi-cloud capability allows customers to bring their own cloud accounts, identities, licenses, and keys to eliminate vendor lock-in.

Tessell also provides self-service access based on policies, DevOps integration, complete production monitoring, and lifecycle management for Oracle, PostgreSQL, MySQL, Microsoft SQL Server, Milvus, and MongoDB database engines. Leveraging the high-performance NVMe cloud storage capabilities, Tessell excels in handling demanding production workloads and optimizing database consolidation for maximum economic efficiency.

This recognition highlights Tessell’s innovative approach to database services and emphasizes its commitment to providing flexible, high-performance, and secure data management solutions. The InfraRed 100 list by Redpoint Ventures identifies companies poised to make significant impacts in the cloud infrastructure space, and Tessell’s inclusion is a testament to its rapid growth and technological advancements.

“We are honored to be recognized by Redpoint Ventures as one of the top private companies in cloud infrastructure,” said Bakul Banthia, Co-founder of Tessell. “This accolade reflects our team’s dedication to delivering exceptional database services that meet the evolving needs of our customers. As we continue to innovate and expand, we remain committed to helping businesses of all sizes modernize their data and applications.”

To commemorate this achievement, Bala Kuchibhotla, Co-founder and CEO of Tessell, will join Redpoint at Nasdaq with other InfraRed 100 leaders to discuss the evolving landscape of cloud infrastructure.

Other recent achievements by Tessell include the AWS Migration and Modernization Competency status and recognition on CRN’s 2024 Big Data 100 and Stellar Startups 2023 lists.

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Intuit Inc. (Nasdaq: INTU), the global financial technology platform that makes Intuit TurboTax, Credit Karma, QuickBooks, and Mailchimp, today previewed its new revenue intelligence (RI) technology, a system of always-on predictive and generative artificial intelligence (GenAI) models designed to proactively give marketers opportunities to win more revenue.

Building on the launch of Intuit Assist last year, Mailchimp’s revenue intelligence will soon deploy Intuit’s powerful and relevant data through cutting-edge AI technology to benchmark customers’ marketing against billions of industry-specific financial inputs from Intuit QuickBooks and marketing performance data points, recommend the right time to target customers, and generate more personalized and revenue-driving content. This technology was unveiled today at Mailchimp’s annual From: Here, To: There London customer event. Additionally, Mailchimp is announcing the continued expansion of SMS features in the UK, after the initial US launch last June*.

“Predicting what will spur different customers to explore, to spend, and stay loyal remains one of the most complicated challenges for marketers—and simultaneously one of their biggest growth opportunities,” said Rania Succar, SVP and General Manager of Mailchimp. “By building on our AI-driven innovations within Intuit’s data-rich platform, our customers can make smarter, more integrated business decisions that simultaneously grow their customer base and put more money in their pockets.”

For years, Intuit has been at the forefront of AI, including releasing Intuit Assist for Mailchimp in 2023—designed to help marketers and business owners save time, send more effective marketing campaigns, and make smarter marketing decisions. Mailchimp’s new RI system will integrate seamlessly with marketers’ daily workflow, turning over 60 petabytes of user interactions across the Intuit ecosystem into tools that can create personalized action plans that increase marketing effectiveness without creating additional learning curves for marketers.

Introducing Revenue Intelligence

With revenue intelligence capabilities in Mailchimp, marketers will be able to maximize their ROI by:

• Leveraging Financial Data from QuickBooks: Mailchimp customers will soon be able to tap into AI that’s trained on financial metrics from QuickBooks and third-party commerce integrations, in addition to performance data from Mailchimp, to proactively point out where they’re missing opportunities—whether that’s benchmarking their marketing against businesses within similar industries, getting ahead with planning for key seasonal campaigns, or recommending the optimal discounts to drive conversion and profitability.
• Experiencing AI Natively in the Platform: Using AI should be frictionless and integrated into marketers’ day-to-day workflow. By seamlessly weaving RI into the app experience, Mailchimp customers will be able to direct their focus elsewhere, while revenue intelligence analyzes data and provides ways for businesses to create more automated, personalized marketing without having to leave the platform or learn a new technology.
• Predicting Revenue Based on Segmentation: RI will recommend segments of onboarded and existing customers for marketers to target by predicting their conversion rates and potential revenue opportunity, anticipating when they’re ready to buy, and then generating branded email and SMS content to target those customers.
• Targeting Repeat Purchases: RI will help marketers engage new customers for repeat purchases using predictive models to show marketers when to send an email or text message and generate multichannel automations to dynamically predict the ideal time to remarket to customers based on the typical buying window for their industry.
• Generating Branded Content That Performs: Mailchimp customers will experience an improved brand kit that includes voice, tone, imagery, and logo, so that the communication is on-brand. When generating content, Mailchimp customers will be able to stay true to the business’s brand style, products & services, and their customers’ buying habits to make their content more personalized.
• Visualizing Revenue with Marketing Funnel: RI’s marketing funnel will give marketers a bird’s-eye view of their segmented customer base, with categories like potential customers, new customers, repeat customers, and VIPs organized by revenue estimates and predicted lifetime value. This helps time-strapped marketers prioritize the most valuable growth opportunities.

“We’ve been quite good at customer acquisition, and we want to focus more on customer loyalty and retention. Email is a big part of helping us to achieve that,” explains Charlotte Howell, digital marketing and ecommerce manager at Grafton International, during an early preview of Mailchimp’s revenue intelligence system last month. “Utilizing AI to help with analytics and finding out more about customers—really getting a clear idea of who they are and what their shopping habits are—is key for us.” Howell will be among the first users putting this tech to work as a part of an exclusive test group.

“It’s kind of what we’ve been waiting for,” she explained, citing the potential increase in revenue and time saved as benefits to look forward to. “Rather than having to dig through pools of data, the tool will push me to make decisions easier and quicker and more effectively.”

Expanding SMS Functionality

Following last year’s release of SMS for US-based customers, Mailchimp also announced plans to expand SMS functionality to the UK—equipping UK-based customers with a 360-degree subscriber view that pulls all data sources into one place, allowing businesses to maximize engagement, track ROI, and streamline analytics reporting.

“SMS marketing has grown to become a critical component to engaging consumers,” said Michelle Taite, Chief Marketing Officer at Mailchimp. “Our US customers are seeing up to 16x ROI in the first 3 months after launching their first SMS campaign**, and with over 93% deliverability rates***, Mailchimp’s SMS is an incredibly reliable tool for building a meaningful relationship with your customers and a powerful way to drive engagement, conversion, and brand loyalty.”

SMS and email are among businesses’ most effective omnichannel marketing strategies when used together. The combination provides a direct and immediate way for businesses to reach their audience with time-sensitive promotions or reminders, as most consumers carry their mobile phones with them at all times.

Availability

Marketers worldwide can sign up for the revenue intelligence early access updates to apply AI to optimize their targeting and content strategy in practical, meaningful ways soon.

Expanded SMS functionalities are now available to UK customers.

Learn More

This announcement was debuted at Mailchimp’s conference, From: Here To: There London today. The event features world-class panels, talks, Q&A sessions with industry-leading marketing, AI, and e-commerce experts, and one-on-one sessions with Mailchimp specialists. Featured speakers include Steven Bartlett, host of “The Diary of a CEO,” brand consultant Mark Ritson, and Ameca, an advanced AI humanoid showcasing cutting-edge human-robotics technology.

Next month, Mailchimp will host its first flagship conference in Australia,From: Here To: There Sydney, on July 23, 2024. Register today for invaluable insights on branding, innovation, and customer engagement from Janine Allis, founder of Boost Juice Bars and author of The Accidental Entrepreneur.

To find out more about Mailchimp’s AI products, click here.

For media kit and visuals, please reach out to pr@mailchimp.com. Follow us on social media: TikTok, LinkedIn, and Instagram.

*SMS is available as an add-on to US or UK paid plans only. Application and agreement to terms is required before purchasing credits. Messages can only be delivered to contacts in the country selected. SMS credits are added to your account after purchase and approval. Credits are issued monthly and unused credits expire and do not roll over. MMS only available when sending to US contacts with US Standard and Premium plans. Pricing varies. See terms for details.

**Based on U.S. SMS users’ e-commerce revenue attributable to SMS campaigns within 90 days of launch during September 2023 through April 2024.

***Mailchimp SMS average deliverability rate: Limited user base due to launch of SMS Marketing in March 2023 and is based on US SMS messages sent by US users from 3/31/23 to 9/28/23. Deliverability measured by percentage of SMS messages successfully delivered to intended recipients.

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Airbyte, creators of the leading open-source data movement infrastructure, today announced the launch of its Snowflake Cortex destination, a new data connector that is the first for Snowflake users who are interested in building Generative AI (GenAI) capabilities directly within their existing Snowflake accounts.

In a recent survey, 93% of chief data officers agreed that data strategy is crucial for getting value out of generative AI.

With no coding required, users can create a dedicated vector store within Snowflake (compatible with OpenAI) and load data from more than 300 sources.

“We are removing barriers to AI integration and making it easier than ever for businesses to harness the potential of Generative AI within their existing data infrastructure,” said Michel Tricot, co-founder and CEO, Airbyte. “We’re removing the complexity and time investment typically associated with setting up AI infrastructure.”

The Snowflake Cortex destination empowers users to create an Airbyte pipeline in minutes. By simplifying the process of building and maintaining a vector store within Snowflake, Airbyte is enabling organizations to unlock new insights and drive transformative outcomes.

Key features of the new Snowflake Cortex destination include the following:

• No coding required: Users can easily set up and manage their vector store directly within Snowflake, eliminating the need for specialized programming skills.
• Rapid deployment: Create a new Airbyte pipeline in just a few minutes, enabling quick and efficient data loading and processing.
• Automatic incremental processing: The Airbyte protocol handles incremental processing automatically, ensuring that data is always up-to-date without manual intervention.

Airbyte makes moving data easy and affordable across almost any source and destination, helping enterprises provide their users with access to the right data for analysis and decision-making. Airbyte has the largest data engineering contributor community – with more than 800 contributors – and the best tooling to build and maintain connectors. Airbyte is the first company to build a bridge between data movement platforms and artificial intelligence (AI) now supporting eight vector databases, in addition to unstructured data sources.

For more information about the Snowflake Cortex destination and to get started with your own AI-powered data integration, visit Build End-to-end RAG applications using Airbyte and Snowflake Cortex.

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Opaque Systems today released the first and only Confidential AI Platform for securely accelerating general-purpose AI workloads into production. Unveiled at the second annual Confidential Computing Summit, Opaque’s platform now supports machine learning (ML) pipelines as well as popular languages and frameworks for AI, such as Python and Spark. With Opaque, enterprises can run a wide range of AI workloads, including SQL analytics and ML inference, on encrypted data with no re-engineering required.

Generative AI holds immense business potential, but security and privacy concerns abound. As a result, the most valuable enterprise data is trapped in red tape, and existing techniques to operationalize that data securely—like anonymization—have proven error-prone and inadequate. Enterprises are forced to choose between innovation and security, preventing AI projects from coming to fruition. Opaque is the first and only company to help overcome these challenges and unlock the full value of organizations’ data.

“Enterprises have long been forced to choose between data security and extracting value from their data. With Opaque, that dichotomy ends,” said Aaron Fulkerson, CEO of Opaque. “Our platform ensures complete data sovereignty while allowing seamless deployment of AI workloads, unlocking business insights securely and efficiently–often enabling the use of sensitive data that couldn’t be used before.”

Now integrated with Confidential VMs as well as Kubernetes, Opaque supports popular AI workloads for high-performance, cloud-scale deployments. These new capabilities expand on Opaque’s unique ability to facilitate secure collaboration with cryptographic verification of privacy. Organizations across industries are empowered to unlock sensitive data, yield richer insights, and drive tangible business value because AI workloads can be deployed on data while encrypted. Use cases include:

• High Tech: Unblock AI projects by securing data pipelines for analytics and ML workloads, ensuring sensitive and customer data is kept private, and dynamically training models with customer data while encrypted.
• Financial Services: Enable secure data sharing and collaboration across business units and partners, ensuring privacy and regulatory compliance. Remove the need for insecure and time-consuming data prep and masking, delivering fast time to value and better-quality insights, ultimately enhancing data-driven decision-making.
• Manufacturing: Manufacturers deploying Generative AI use Opaque as a confidential control plane to enforce data governance rules. This provides verifiable evidence that data policies, privacy, and sovereignty were maintained.
• Human Resources: HR departments across industries use Opaque to securely share and analyze employee data across multiple data silos. This enables workforce analyses to improve recruitment, retention, compensation, and talent development while ensuring compliance with data privacy regulations like GDPR. Data-driven decisions are made without compromising employee confidentiality.

“Opaque offers a breakthrough for organizations struggling with the tension between innovation and security. By embedding privacy and security into every step of the ML pipeline, we enable enterprises to accelerate AI adoption confidently,” said Chester Leung, co-founder and Head of Platform Architecture at Opaque. “Our confidential AI platform uniquely enables the processing of encrypted data without a noticeable performance hit at cloud scale. With Opaque securing entire data workloads, companies can unlock new business opportunities and manage risks effectively, all while maintaining absolute control and privacy of their data.”

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Snowflake (NYSE: SNOW), the AI Data Cloud company, today announced at its annual user conference, Snowflake Summit 2024, Polaris Catalog, a vendor-neutral, open catalog implementation for Apache Iceberg — the open standard of choice for implementing data lakehouses, data lakes, and other modern architectures.Polaris Catalog will be open sourced in the next 90 days to provide enterprises and the entire Iceberg community with new levels of choice, flexibility, and control over their data, with full enterprise security and Apache Iceberg interoperability with Amazon Web Services (AWS), Confluent, Dremio, Google Cloud, Microsoft Azure, Salesforce, and more.

“Organizations want open storage and interoperable query engines without lock-in. Now, with the support of industry leaders, we are further simplifying how any organization can easily access their data across diverse systems with increased flexibility and control,” said Christian Kleinerman, EVP of Product, Snowflake. “Polaris Catalog extends Snowflake’s commitment to Apache Iceberg as the open standard of choice, and signals the intent from industry leaders in enabling customers and the wider Iceberg community to harness their data through an open and neutral approach, empowering cross-engine interoperability on that data.”

Polaris Catalog Introduces New Levels of Interoperability for Apache Iceberg

Apache Iceberg emerged from incubation to a top-level Apache Software Foundation project in May 2020, and has since surged in popularity to become a leading open source data table format. With Polaris Catalog, users now gain a single, centralized place for any engine to find and access an organization’s Iceberg tables with full, open interoperability. Polaris Catalog relies on Iceberg’s open source REST protocol, which provides an open standard for users to access and retrieve data from any engine that supports the Iceberg Rest API, including Apache Flink, Apache Spark, Dremio, Python, Trino, and more.

Organizations can get started running Polaris Catalog hosted in Snowflake’s AI Data Cloud within minutes (Snowflake-hosted in public preview soon), or self-host it in their own infrastructure using containers such as Docker or Kubernetes. Since Polaris Catalog’s backend implementation will be open source, organizations can freely swap the hosting infrastructure while eliminating vendor lock-in.

Leading Organizations Join the Polaris Catalog Community

A part of what makes Apache Iceberg so powerful is its vibrant community of diverse adopters, contributors, and commercial offerings. To ensure Polaris Catalog can meet the evolving needs of the wider community and landscape, Snowflake is collaborating with the Iceberg ecosystem to drive the project forward.

This comes on the heels of Snowflake and Microsoft’s recent partnership expansion, which creates more seamless interoperability between Snowflake and Fabric. This interoperability is possible because of Snowflake’s and Microsoft’s commitment to supporting the industry’s leading open standards for storage formats – Apache Iceberg and Apache Parquet. Now with Polaris Catalog, both organizations continue to partner with a joint mission of enabling all users to harness their enterprise data, regardless of where it is stored, to create AI-powered applications at scale.

“From day one at Microsoft, we’ve been focused on empowering every user on the planet to achieve more, and this starts with a strong data foundation. Through our support and contributions to open data standards, including Delta Parquet, Apache Iceberg, and Apache XTable, we’re furthering this mission by enabling organizations with a new level of open data interoperability, so they can do more with their data,” said Arun Ulagaratchagan, Corporate Vice President, Azure Data, Microsoft. “Snowflake continues to serve as a strategic partner of ours, and we’re excited by their willingness to work with the Iceberg community on an open catalog to empower our joint customers and the wider open-source community with more flexibility and control over their open Iceberg data.”

With Snowflake’s expertise, serving as the data foundation powering thousands of global customers’ cross-cloud data and AI workloads, and the rapidly growing Iceberg community’s innovation and open source skill sets, they will continue to simplify the interoperability of data across engines together.

Snowflake Continues to Extend Open Source Commitments

Polaris Catalogfollows a slew of recent open source commitments from Snowflake, including its investments in Iceberg Tables, which allow Snowflake customers to work with data in their own storage in the Apache Iceberg format, while still benefiting from Snowflake’s ease of use, performance, and unified governance.

Snowflake also recently announced Snowflake Arctic, one of the most open, enterprise-grade large language models (LLM) on the market. As part of Snowflake’s commitment to open source, it not only released Arctic’s weights under an Apache 2.0 license, but also extensive details of how it was trained through a series of cookbooks. In addition, Snowflake supports the Streamlit open source community, which now has over 275K monthly active developers and over 6 million monthly application views. Since Snowflake acquired Streamlit in March 2022, the open source community has continued to flourish, growing over 500 percent in the past two years, as Snowflake and Streamlit continue to invest in cutting-edge open source advancements for developers.

Comments On the News from Data Platform Experts

“AWS is committed to working with partners, such as Snowflake, on open source solutions that can accelerate choice for customers,” said Chris Grusz, Managing Director, Technology Partnerships, Amazon Web Services. “We’re pleased to work with Snowflake to continue to make Apache Iceberg stay interoperable across our engines.”

“At Confluent, we’re on a mission to break down data silos to help organizations power their businesses with more real-time insights,” said Shaun Clowes, Chief Product Officer, Confluent. “With Tableflow on Confluent Cloud, organizations will be able to turn data streams from across the business into Apache Iceberg tables with one click. Together, Snowflake’s Polaris Catalog and Tableflow enable data teams to easily access these tables for critical application development and downstream analytics.”

”Customers want thriving open ecosystems and to own their storage, data and metadata. They don’t want to be locked-in,” said Tomer Shiran, Founder, Dremio. “We’re committed to supporting open standards, such as Apache Iceberg and the open catalogs Project Nessie and Polaris Catalog. These open technologies will provide the ecosystem interoperability and choice that customers deserve.”

“We are actively involved in the open source community, particularly across the data space,” said Neema Raphael, Chief Data Officer and Head of Data Engineering at Goldman Sachs. “We open sourced our data platform, Legend, which enables us to work with open source table formats like Iceberg that will provide more interoperability across query engines like Snowflake. The launch of an open source Iceberg Catalog like Polaris is an exciting next step in furthering that commitment to interoperability.”

“Apache Iceberg’s popularity has established an open storage standard that simplifies zero copy data access for organizations across their ecosystem,” said Raveendrnathan Loganathan, Executive Vice President of Software Engineering at Salesforce. “Our Salesforce Data Cloud has been built from the ground up with Open Standards Apache Parquet for files & Apache Iceberg for tables, fostering zero copy innovations to unlock trapped data, derive insights, and orchestrate actions across the Customer 360. We’re thrilled to have Snowflake as a member of our Zero Copy Partner Network, and we’re excited to see how this new open catalog standard will further zero copy access in the enterprise.”

Learn More:

• Learn more about Polaris Catalog by registering for this webinar.
• Dive into Polaris Catalog’s unique differentiation in this blog post.
• See how you can get started with Polaris Catalog hosted on Snowflake’s AI Data Cloud within minutes, here.
• Stay on top of the latest news and announcements from Snowflake on LinkedIn and Twitter / X.

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.

© 2024 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).

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SAS, a leader in data and AI, today announced at Snowflake’s annual user conference, Snowflake Data Cloud Summit 2024, that it has begun the private preview of SAS Data Maker in Snowflake Marketplace. In the latest addition to SAS Data Maker previews, the offering as a Snowflake Native App will provide powerful synthetic data generation experiences that users can trust, natively within joint customers’ Snowflake accounts. 

“SAS Data Maker uses SAS’ cutting-edge, reliable AI models to create statistically accurate data points that truly augment existing data and can capture countless different scenarios, helping customers better forecast outcomes so they can anticipate their businesses’ changing needs,” said Shadi Shahin, Vice President of Product Strategy at SAS. “This is particularly valuable in instances where specific real-world data is hard to come by or when there’s a need to detect rare case scenarios in highly regulated areas like healthcare, finance and fraud.”

SAS and Snowflake are working together to mobilize the world’s data with Snowflake’s Data Cloud, helping joint customers unlock the value of their data. SAS Data Maker improves customer data quality and productivity by generating synthetic data that closely mirrors real-world data, producing visual and statistical evaluation metrics that are fully automated to protect sensitive existing data. This in turn helps customers innovate faster with tangible outcomes that can scale across their organization, while also circumventing costly data acquisition and processing hurdles that come with manual data collection or purchasing of third-party data sets. Furthermore, making SAS Data Maker available on Snowflake Marketplace gives even more customers flexibility and access to leading SAS technology that can deliver real results for their businesses.

“With the Snowflake Native App Framework and its new support for Snowpark Container Services, partners like SAS can bring their complex applications directly to customers, running on their secure and governed data inside Snowflake,” said Prasanna Krishnan, Head of Collaboration and Horizon at Snowflake. “This means partners can deliver valuable capabilities like precise synthetic data generation quickly, securely, and powerfully to customers in the Data Cloud.”

One example being AstraZeneca, a global biopharmaceutical company, who intends to use SAS Data Maker to empower its data scientists through the use of synthetic data to further improve decision-making.

“Synthetic data can enhance our ability to make informed decisions from critical data, and thus has the real potential to help accelerate drug discovery and development, ultimately benefiting patients around the world,” noted Brian Dummann, Chief Data Officer at AstraZeneca. “We look forward to leveraging SAS Data Maker in the Snowflake Marketplace and streamlining how data scientists can access synthetic data for their initiatives.”

Using the combined capabilities of Snowflake Native App Framework and Snowpark Container Services (integration in public preview), developers can build sophisticated applications that run on a range of configurable hardware options, including GPUs, distribute and monetize them on Snowflake Marketplace, and deploy them within their customers’ Snowflake accounts, without requiring data movement. To learn more about SAS Data Maker on Snowflake Marketplace, click here.

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Hon Hai Technology Group (“Foxconn”) (TWSE:2317) today announced that it plans to build an advanced computing center in Kaohsiung, Taiwan, with the NVIDIA Blackwell platform at its core, as the CEOs of the two technology bellwethers reaffirmed their strong partnership at COMPUTEX 2024.

The latest collaboration between Foxconn and NVIDIA signals a deepening commitment by the world’s largest electronics manufacturing service provider and market leader in making AI servers, alongside its world-class partner, to drive intelligent ecosystems covering AI, electric vehicles, smart factories, robotics, smart cities and other fields.

NVIDIA founder and CEO Jensen Huang and Foxconn Chairman and CEO Young Liu caught up with each other on the exhibition floor of COMPUTEX, getting a comprehensive tour about their cooperation at the booth set up by Ingrasys, the Foxconn subsidiary that has been at the manufacturing epicenter of NVIDIA’s GB200 NVL72, MGX, HGX and other innovative products.

Following the tour, Huang noted that NVIDIA and Foxconn have worked closely together on various product development, and the proof of the cooperation is clear, especially with the Blackwell product line-up; Foxconn has excellent vertical integration capabilities and is a vital partner for the GB200.

On the spot, Chairman Liu announced that Foxconn will join hands with NVIDIA to build an advanced computing center in Kaohsiung with the NVIDIA Blackwell platform at its core. The cutting-edge computing center, anchored by the superchip GB200 servers, consists of a total of 64 racks and 4,608 GPUs, is slated for completion by 2026. NVIDIA’s powerful AI technology will drive Foxconn’s three smart platforms: Smart Manufacturing. Smart EV. Smart City. Both companies will continue to deepen cooperation in AI, electric vehicles, smart factories, robots, smart cities and other fields, and demonstrate the strong competitiveness brought by AI through Foxconn’s huge manufacturing scale.

Huang said, “A new era of computing has dawned, fueled by surging global demand for generative AI data centers. Foxconn stands at the forefront as a leading supplier of NVIDIA computing and a trailblazer in the application of generative AI in manufacturing and robotics. Leveraging NVIDIA Omniverse and Isaac robotics platforms, Foxconn is harnessing cutting-edge AI and digital twin technologies to construct their advanced computing center in Kaohsiung.”

The two companies will utilize NVIDIA Omniverse and create digital twins to introduce platforms for smart manufacturing, smart electric vehicles, and smart cities. For smart manufacturing platforms, image recognition technology, combined with the Group’s autonomous mobile robots (AMR), will lead to changes for optimal capacity utilization. The production line planning will encompass existing manufacturing of AI servers and EV assembly plants. 

Toward that goal, the new Qiaotou automotive manufacturing facilities of Foxtron, a Foxconn subsidiary, will become one of the Group’s benchmark AI factories. Currently under construction, the site will utilize digital twin connected to cloud technologies and achieve collaboration between virtual and physical production lines. Digital real-time monitoring will ensure the manufacturing excellence of an award-winning electric bus, which is currently seeing orders outpacing output capacity.

Going forward, the two companies’ collaborative effort in EV ADAS platform will be applied to future EV models designed by Foxconn. Presently, Foxconn is negotiating projects with traditional European and American automakers. Moreover, based on NVIDIA’s new generation of chips, Foxconn and NVIDIA jointly plan a “cabin-driving-in-one” smart travel solution, creating a third living space.

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In-Situ’s new Cloud Collection will make it easier for scientists, researchers, consultants and engineers monitoring water quality and water level in the field to view and manage data files and calibration reports. Rather than download and email files to their destination, users can simply use the VuSitu app to log into their HydroVu account and files will instantly upload to the cloud, where they can be viewed, managed and shared.

With Cloud Connection, calibrations performed using VuSitu will automatically be stored in HydroVu. Users can quickly access a fleetwide calibration history, and files are easily searchable by keyword, instrument type, serial number and date range. The feature also enables graphing of “offline” data alongside telemetered data and notification of users accessing and/or sending files. And HydroVu keeps all data secure with instant redundant backup.

“We know the most important part of our customers’ work is the data they get from our instruments,” says In-Situ Product Owner Tom Koniuta. “This update makes that easier. VuSitu hasn’t changed,” he adds. “We’ve just added the security of automatic file backup in HydroVu, so customers can trust that all their data will be there waiting for them.”

VuSitu HydroVu Cloud Connection is available to everyone with the VuSitu app for iOS and Android and a HydroVu data plan, including the free tier of service. As the only software feature of its kind in the industry, it’s part of a shared ecosystem of rugged water monitoring instrumentation and intuitive software thoughtfully designed to simplify access to decision-quality data.

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