Latest news with #Teradata
Business Wire
3 days ago
- Business
- Business Wire
Teradata Possible 2025: Experience the Trusted AI and Data Conference
SAN DIEGO--(BUSINESS WIRE)-- Teradata (NYSE: TDC) today announced Possible 2025: the Trusted AI and Data Conference — a global event where decision-makers, influencers, and leaders come together to navigate the evolving landscape of AI innovation, data, and technology. The electric three-day event, taking place in Los Angeles, October 6-8, 2025, is a signature experience for data and analytics professionals that offers direct access to AI thought leaders and practical insights from global experts. Attendees will be able to dive into breakout sessions, dynamic keynotes, and interactive roundtables to uncover how Trusted AI and harmonized data can supercharge value and fuel rapid innovation across organizations. The program features immersive hands-on training, high-impact workshops, and live demonstrations showcasing the capabilities of Teradata's advanced cloud analytics and AI-driven data platform. Attendees will hear from industry luminaries and Teradata customers and partners on how they are driving growth for their businesses, leveraging data analytics and AI/ML to unlock new use cases. Keynote highlights: Our mainstage speakers explore the future of AI and data management. Attendees will hear from innovation leaders, including: Chris Barton, Founder of Shazam Steve McMillan, President and CEO of Teradata Sumeet Arora, Chief Product Officer of Teradata Louis Landry, Chief Technology Officer of Teradata Customer speakers include (non-exhaustive list): Banco Bradesco – José Marcelo Munhoz Fichelli, Data Engineer Manager Comptroller of Maryland – Andrew Schaufele, Chief Deputy Comptroller Delta Community Credit Union – Dr. Sujatha (Su) Rayburn, Vice President – Information Management and Analytics Emirates Integrated Telecommunications Company (du) – Amr Halawa, Manager, Data Management and Mediation OSS GoDaddy, Inc. – Rose Santos, Sr. Director, Finance Innovation HCA Healthcare – Jason Schrader, Director, Data and Analytics Engineering HCA Healthcare – Srinivas Subbarao, Director, Enterprise Data Warehouse Ooredoo – Ali Danish Malik, Assistant Director Analytics PRIO – Alex Mendonça, Head of Internal Audit and Claudio Paiva, Specialist Auditor Raiffeisen Bank International – Mario Stegbauer, Head of Data Warehouse Platform Sicredi – Lucas Kylder, Data Engineer Telefônica Brasil – Rodrigo Primo, Head of Performance and Capacity Planning Telefônica Brasil – Stivie Florio, Head of Cloud Engineering and Infrastructure United Bank Limited – Rehman Hameed, Head of Data & AI (EVP) Vodafone – Ryan Smith, Fraud Prevention Manager 'Possible 2025 is more than just a gathering—it's a catalyst for innovation,' said Steve McMillan, President and CEO of Teradata. 'As AI continues to reshape industries, we are bringing together the brightest minds in data and analytics to explore how Trusted AI and connected data can unlock bold new possibilities, drive faster innovation, and accelerate scalable impact across the enterprise.' For more information on Possible 2025: the Trusted AI and Data Conference in Los Angeles visit About Teradata At Teradata, we believe that people thrive when empowered with trusted information. We offer the most complete cloud analytics and data platform for AI. By delivering harmonized data and Trusted AI, we enable more confident decision-making, unlock faster innovation, and drive the impactful business results organizations need most. See how at The Teradata logo and ClearScape Analytics are trademarks, and Teradata is a registered trademark of Teradata Corporation and/or its affiliates in the U.S. and worldwide.
Forbes
4 days ago
- Business
- Forbes
Best Practices: AI-Powered Code Translation In Cloud Migration
Chetan Mathur is CEO of Next Pathway, the Automated Cloud Migration company. Cloud migration has shifted from a question of "if" to one of "how fast and how well." For today's enterprise leaders, the true differentiator is not just reaching the cloud, but doing so with efficiency, predictability and readiness for an AI-powered future. As digital transformation accelerates, automation of code translation and, in particular, AI-driven code translation, has emerged as a critical enabler for organizations seeking to modernize at scale. The New Imperative: Modernize At Speed Legacy data warehouses and applications, often built on platforms like Teradata or SQL Server with complex data pipelines, pose significant complexity. These systems can contain millions of lines of code, intricate data dependencies and deeply embedded business logic developed over decades. Traditionally, translating this code for cloud-native platforms has been a manual, error-prone process that can stall transformation and exhaust valuable resources. That landscape is rapidly changing. AI-powered code translation and automation now enable organizations to accelerate migrations, minimize risk and achieve rapid cutovers, unlocking the full potential of the cloud and AI. How AI And Automation Are Transforming Migration Modern automation platforms, powered by generative AI, can analyze legacy code, translate it for cloud environments such as Snowflake or AWS and optimize it for performance and compliance. These tools handle SQL, ETL, stored procedures and complex data pipelines, reducing manual effort and compressing migration timelines from years to months or even weeks. (Disclosure: My company, Next Pathway, has a partnership with AWS and Snowflake.) In practice, AI-driven translation platforms ingest legacy codebases, parse and map logic to cloud-native constructs and automatically generate target code. Machine learning models, trained on millions of lines of code, enable these platforms to recognize patterns, optimize queries and suggest architectural improvements. Automated validation and testing frameworks further ensure that translated code is functionally accurate and high-performing in its new environment. According to Forrester, organizations adopting AI-driven automation in cloud migration are achieving faster transitions, greater agility and improved operational efficiency—key advantages for enterprises modernizing at scale. Real-World Proof: Automation In Action Danske Bank, one of Europe's largest financial institutions, migrated 16,600 servers and 25 PB of data to AWS using hyper automation. Automation cut the migration timeline in half, reduced costs by 50% and replaced weeks of manual runbook creation with seconds, enabling rapid, secure and large-scale cloud adoption. Micron migrated 500 TB of data from a legacy data warehouse to Snowflake. Automation was central to the process, enabling rapid data ingestion, transformation and analytics, unlocking new business insights and accelerating scientific innovation. WHOOP transitioned from a legacy data warehouse to Snowflake in just three months. Automation and Snowflake's managed services enabled rapid migration, improved governance and eliminated resource contention, supporting business growth and innovation. Nomura Research Institute leveraged AWS Transform's agentic AI to automate the analysis, documentation and code translation of millions of lines of mainframe COBOL and JCL. This AI-driven approach reduced code analysis and migration time from months to weeks, enabling rapid, accurate modernization with minimal manual effort. Best Practices For AI-Powered Cloud Migration AI-driven automation is transforming cloud migration from a technical hurdle into a strategic opportunity. Here's how leading organizations are rethinking their approach: Start with a sharp focus on business impact. Map migration priorities to outcomes such as accelerating innovation, enabling real-time analytics or supporting new digital business models. This ensures every decision is guided by measurable value and enterprise-wide alignment. Manual processes cannot keep pace with today's complexity. AI-powered crawler systems provide deep visibility into legacy environments, surfacing hidden dependencies and risks. Automated translation and orchestration accelerate timelines and preserve critical business logic. Integrating automated quality assurance (QA) testing throughout ensures accuracy, security and performance before cutover. Break migration into manageable phases to minimize business disruption and risk. Start by automating the migration of pilot workloads to validate your approach and processes. Once your automated approach is proven, progressively migrate larger and more complex workloads in subsequent phases. This structured strategy helps meet critical deadlines and ensures business continuity throughout the migration journey. Automated, continuous testing validates data accuracy and application performance at every stage. Real-time monitoring provides immediate feedback, helping teams address issues proactively and maintain high standards of security and compliance. Invest in training and foster cross-functional collaboration. Empowering teams to work with cloud-native and AI-driven tools ensures your organization can fully leverage new capabilities and sustain innovation over time. By approaching migration as a strategic enabler, organizations can achieve agility, resilience and innovation while minimizing disruption. This positions them to lead in an AI-powered future. Conclusion AI-powered code translation is more than a technical breakthrough—it's a strategic imperative. Enterprises that seize this capability will not only accelerate their migrations, but will also unlock the agility, resilience and innovation required to lead in the AI-driven future. The organizations that act now will shape the standards and set the pace for digital transformation in their industries. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Yahoo
27-06-2025
- Business
- Yahoo
Teradata's Q1 Earnings Call: Our Top 5 Analyst Questions
Teradata's first quarter results for 2025 were shaped by a combination of declining top-line sales and expanding profit margins. Management highlighted ongoing improvements in its advanced analytics and hybrid cloud offerings as key factors underpinning customer retention and growth in cloud annual recurring revenue. CEO Steve McMillan credited the company's focus on industry-specific use cases and its ability to meet customers' needs in both cloud and on-premises environments for sustaining engagement despite a challenging macroeconomic landscape. Management also noted the benefits of cost optimization efforts that helped support profitability, with McMillan stating, 'Our go to market team is executing well against the pipeline we carried into 2025.' Is now the time to buy TDC? Find out in our full research report (it's free). Revenue: $418 million vs analyst estimates of $428.2 million (10.1% year-on-year decline, 2.4% miss) Adjusted EPS: $0.66 vs analyst estimates of $0.56 (17% beat) Adjusted Operating Income: $91 million vs analyst estimates of $82.32 million (21.8% margin, 10.6% beat) Revenue Guidance for Q2 CY2025 is $401.1 million at the midpoint, below analyst estimates of $409 million Management reiterated its full-year Adjusted EPS guidance of $2.20 at the midpoint Operating Margin: 15.8%, up from 10.3% in the same quarter last year Annual Recurring Revenue: $1.44 billion at quarter end, down 2.6% year on year Billings: $457 million at quarter end, in line with the same quarter last year Market Capitalization: $2.08 billion While we enjoy listening to the management's commentary, our favorite part of earnings calls are the analyst questions. Those are unscripted and can often highlight topics that management teams would rather avoid or topics where the answer is complicated. Here is what has caught our attention. Erik Woodring (Morgan Stanley) asked about additional cost-cutting opportunities and the balance between SG&A and R&D. CEO Steve McMillan emphasized the focus on profitable growth and continued optimization of investments, citing recent restructuring in the sales team to prioritize analytics and AI solutions. Yitchuin Wong (Citi) inquired about lessons learned from recent executive transitions and the impact on future execution. McMillan described the evolution toward "Teradata 3.0," focused on business outcomes driven by advanced analytics and AI, and highlighted the company's retooled innovation strategy. Howard Ma (Guggenheim) questioned parallels between current macro uncertainty and previous periods of cloud optimization. McMillan noted that Teradata's sticky customer base and critical workload management provide visibility, while services business headwinds are expected to ease later in the year. Chirag Ved (Evercore ISI) sought clarification on the confidence behind maintaining ARR guidance amid cautious industry commentary. McMillan maintained that pragmatic guidance and improved retention rates support the company's outlook for returning to ARR growth in the second half of the year. Jared Jungjohann (TD Cowen) asked for updates on the impact of AI-related products on near-term revenue. McMillan stated that while the current revenue impact is limited, strong customer interest and growing use cases are expected to drive platform utilization and future growth. In upcoming quarters, the StockStory team will be watching (1) the pace of adoption for Teradata's new AI-enabled products, particularly the Enterprise Vector Store and on-premises AI capabilities, (2) sustained improvements in customer retention rates and the resulting impact on recurring revenue, and (3) evidence that the new executive leadership team can accelerate innovation and operational efficiency. Developments in hybrid cloud adoption and customer expansion within regulated industries will also be important markers. Teradata currently trades at $21.99, in line with $21.95 just before the earnings. At this price, is it a buy or sell? See for yourself in our full research report (it's free). Market indices reached historic highs following Donald Trump's presidential victory in November 2024, but the outlook for 2025 is clouded by new trade policies that could impact business confidence and growth. While this has caused many investors to adopt a "fearful" wait-and-see approach, we're leaning into our best ideas that can grow regardless of the political or macroeconomic climate. Take advantage of Mr. Market by checking out our Top 5 Strong Momentum Stocks for this week. This is a curated list of our High Quality stocks that have generated a market-beating return of 183% over the last five years (as of March 31st 2025). Stocks that made our list in 2020 include now familiar names such as Nvidia (+1,545% between March 2020 and March 2025) as well as under-the-radar businesses like the once-small-cap company Exlservice (+354% five-year return). Find your next big winner with StockStory today.
Yahoo
27-06-2025
- Business
- Yahoo
1 Safe-and-Steady Stock Worth Investigating and 2 to Be Wary Of
Stability is great, but low-volatility stocks may struggle to deliver market-beating returns over time as they sometimes underperform during bull markets. Luckily for you, StockStory helps you navigate which companies are truly worth holding. Keeping that in mind, here is one low-volatility stock providing safe-and-steady growth and two that may not keep up. Rolling One-Year Beta: 0.85 Part of point-of-sale and ATM company NCR from 1991 to 2007, Teradata (NYSE:TDC) offers a software-as-service platform that helps organizations manage and analyze their data across multiple storages. Why Do We Think TDC Will Underperform? Offerings couldn't generate interest over the last year as its billings have averaged 3.4% declines Projected sales decline of 4.2% over the next 12 months indicates demand will continue deteriorating Gross margin of 60.2% is below its competitors, leaving less money to invest in areas like marketing and R&D Teradata is trading at $21.99 per share, or 1.3x forward price-to-sales. If you're considering TDC for your portfolio, see our FREE research report to learn more. Rolling One-Year Beta: -0.12 Founded in 1919 as Nebraska Consolidated Mills in Omaha, Nebraska, Conagra Brands today (NYSE:CAG) boasts a diverse portfolio of packaged foods brands that includes everything from whipped cream to jarred pickles to frozen meals. Why Do We Steer Clear of CAG? Shrinking unit sales over the past two years suggest it might have to lower prices to stimulate growth Sales are projected to tank by 2.6% over the next 12 months as demand evaporates Day-to-day expenses have swelled relative to revenue over the last year as its operating margin fell by 7.9 percentage points At $20.48 per share, Conagra trades at 8.4x forward P/E. Check out our free in-depth research report to learn more about why CAG doesn't pass our bar. Rolling One-Year Beta: 0.80 Founded in 1884 and serving communities from Mendocino County in the north to Kern County in the south, Westamerica Bancorporation (NASDAQ:WABC) provides banking services to individuals and small businesses throughout Northern and Central California. Why Could WABC Be a Winner? 9.7% annual net interest income growth over the last four years surpassed the sector average as its products resonated with borrowers Non-interest operating profits increased over the last four years as the company gained some leverage on its fixed costs and became more efficient Share buybacks catapulted its annual earnings per share growth to 11.4%, which outperformed its revenue gains over the last five years Westamerica Bancorporation's stock price of $48.59 implies a valuation ratio of 1.3x forward P/B. Is now the right time to buy? See for yourself in our full research report, it's free. Donald Trump's victory in the 2024 U.S. Presidential Election sent major indices to all-time highs, but stocks have retraced as investors debate the health of the economy and the potential impact of tariffs. While this leaves much uncertainty around 2025, a few companies are poised for long-term gains regardless of the political or macroeconomic climate, like our Top 6 Stocks for this week. This is a curated list of our High Quality stocks that have generated a market-beating return of 183% over the last five years (as of March 31st 2025). Stocks that made our list in 2020 include now familiar names such as Nvidia (+1,545% between March 2020 and March 2025) as well as under-the-radar businesses like the once-small-cap company Comfort Systems (+782% five-year return). Find your next big winner with StockStory today for free. Find your next big winner with StockStory today. Find your next big winner with StockStory today Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Techday NZ
25-06-2025
- Business
- Techday NZ
Teradata launches on-premises AI Factory for secure private AI
Teradata has announced the launch of Teradata AI Factory, an integrated solution delivering the company's cloud-based artificial intelligence (AI) and machine learning (ML) capabilities to secure, on-premises environments. The AI Factory has been built in collaboration with NVIDIA and unifies key components including data pipelines, algorithm execution, and software infrastructure into a single, scalable system. The solution is intended to accelerate AI development—covering predictive, generative, and agentic AI—through private deployments while facilitating governance, compliance, and security for enterprises. Teradata AI Factory is designed to integrate software, hardware, and a combination of Teradata and third-party tools, aiming to decrease both compliance risks and costs. When paired with Teradata AI Microservices with NVIDIA and customer-provided NVIDIA GPUs, the platform supports accelerated development, including native Retrieval-Augmented Generation (RAG) pipelines, which are increasingly in demand among data-driven organisations. The company has positioned this solution as particularly relevant for industries with high regulatory requirements, such as healthcare, finance, and government, as well as any enterprise needing greater control and autonomy over AI strategy and deployments. Changing requirements According to the company, current global instability and stricter data sovereignty regulations are influencing organisations to seek more control over their AI infrastructure. These factors coincide with financial pressures that can result from both underused GPU investments and variable cloud computing costs, especially within hybrid enterprise environments. The increasing complexity of AI ecosystems is expected to further drive demand for integrated, turnkey solutions that can address both cost and governance issues. "Market dynamics are increasing buyer interest in on-premises solutions," said Teradata's Chief Product Officer, Sumeet Arora. "Teradata remains the clear leader in this environment, with proven foundations in what makes AI meaningful and trustworthy: Top-notch speed (performance), predictable cost (resource efficiency), and integration with the golden data record (which may already live on Teradata). Teradata AI Factory builds on these strengths in a single solution for organisations using on-prem infrastructure to gain control, meet sovereignty needs, and accelerate AI ROI." A recent report from Gartner states: "By 2028, more than 20% of enterprises will run AI workloads (training or inference) locally in their data centers, an increase from approximately 2% as of early 2025." ("How to Determine Infrastructure Requirements for On-Premises Generation AI" by Chandra Mukhyala, Jonathan Forest, Tony Harvey from March 5, 2025) Feature set Teradata AI Factory is structured to provide enterprises with a comprehensive on-premises AI solution incorporating security, cost efficiency, and seamless hardware-software integration. Its feature set includes Teradata's Enterprise Vector Store as well as Teradata AI Microservices, the latter of which leverages NVIDIA NeMo microservices to enable native RAG pipeline capabilities. The platform's architecture aims to address sensitive data requirements by keeping data within the organisation's boundaries, thereby reducing the risks commonly associated with public or shared AI platforms—including data exposure, intellectual property leakage, and challenges with regulatory compliance. Teradata AI Factory supports compliance with established standards such as GDPR and HIPAA, positioning it as an option for organisations where data residency and privacy are priorities. Its localised set-up is designed to facilitate high levels of AI performance while lowering latency and operational inefficiency due to reduced data movement. Customers can choose to deploy AI models on CPUs or accelerate performance using their existing GPU infrastructure. This approach seeks to avoid unpredictable cloud expenses, allowing organisations to maintain consistent operational costs and prepare for scaled private AI innovation going forward. Technical integration Teradata AI Factory presents an integrated, ready-to-run stack for AI applications. It includes: AI Platform for Rapid Innovation: Built on Teradata's IntelliFlex platform, the AI Factory incorporates Teradata Enterprise Vector Store, enabling integration of structured and unstructured data for generative AI applications. Built on Teradata's IntelliFlex platform, the AI Factory incorporates Teradata Enterprise Vector Store, enabling integration of structured and unstructured data for generative AI applications. Software Infrastructure: The AI Workbench provides a self-service workspace with access to analytics libraries, including those from ClearScape Analytics. It also offers model lifecycle management, compliance tools, one-click large language model (LLM) deployment, and supports JupyterHub, ModelOps, Airflow, Gitea, and Devpi. The AI Workbench provides a self-service workspace with access to analytics libraries, including those from ClearScape Analytics. It also offers model lifecycle management, compliance tools, one-click large language model (LLM) deployment, and supports JupyterHub, ModelOps, Airflow, Gitea, and Devpi. Algorithm Execution: The system supports scalable execution of predictive and generative algorithms, facilitating high performance through connections with customer GPUs and delivering native RAG processing. The system supports scalable execution of predictive and generative algorithms, facilitating high performance through connections with customer GPUs and delivering native RAG processing. Data Pipelines: The solution includes data ingestion tools and internal capabilities like QueryGrid, Open Table Format (OTF) compatibility, object store access, and support for NVIDIA utilities for complex data formats such as PDFs. By processing data locally within an organisation's infrastructure, Teradata AI Factory is intended to enhance data security and operational integrity, providing greater control and certainty for those adopting private AI strategies.
