Thank you, Chad, and hello, everyone. Thanks for joining us today. Teradata had a solid first quarter of 2025. We delivered public cloud ARR of $606 million, a 16% year-on-year increase in constant currency. We saw total ARR of $1.44 billion, in line with expectations on a constant currency basis. We generated $7 million in free cash flow in the quarter and our non-GAAP EPS was $0.66, an increase of 16% year-on -year. In Q1, we maintained our focus on execution and are seeing benefits from the actions that began in the middle of last year. Our go to market team is executing well against the pipeline we carried into 2025. We are seeing positive effects from the team’s increasing focus on advanced analytics and industry use cases, both in cloud and on-prem. Cloud is now 42% of our total ARR and we are also seeing that our hybrid capabilities are very relevant in times of macro volatility. We are meeting customers in the environment that best addresses their needs now and into the future and believe that our cloud and hybrid capabilities will resonate in the market. Many of our customers rely on insights from their Teradata environments to help them operate their businesses efficiently even in times of uncertainty. We are monitoring the dynamic market and are working closely with customers to help them get the most out of their data and analytics as they address the uncertain climate. We’ve assessed the direct impact from the dynamic tariff situation and it is expected to be immaterial to our business in 2025. As we look ahead, we are taking a more prudent stance with respect to our services business, which is more subject to discretionary spending. As the world explores use cases of AI, it is imperative that the data behind the AI is secure, appropriately governed, and trusted. Trusted data is critical to success with AI and Agentic or Autonomous AI depends on massive amounts of trusted data across both structured and unstructured sources. This integration of diverse data types at any scale is Teradata’s core strength. To succeed with Agentic AI, you need not just trusted data, but high-performance vector processing capabilities that can deliver the right information in the moment so that agents can take action in real time, whether someone is in a chat session, on the website or on the phone. These actions will increasingly be performed by AI agents that will need to seamlessly access both structured and unstructured data to derive the best answer for customers. In early March, we announced Teradata Enterprise Vector Store. That end database solution brings the speed, power and multidimensional scale of our hybrid analytics platform to vector data and management, a crucial infrastructure component for building trusted effective AI systems. It is designed to help customers move beyond basic generative AI implementations towards sophisticated Agentic AI and autonomous business processes. Our Enterprise vector store, which will integrate with NVIDIA’s NeMo Retriever microservices can enable enterprises to solve multidimensional complex problems by combining structured and unstructured data with accelerated compute to optimize Rag applications, which we believe will create a single source of truth for all of a company’s AI initiatives. We’re enthusiastic about the interest we are seeing and I’ll talk about some of the examples of use cases we are working on with our customers. This quarter, we plan to introduce innovations designed for enterprises that need more control and flexibility over their AI deployments, particularly in today’s dynamic and often uncertain environment. Many of our customers operate in regulated industries with strict requirements for data sovereignty and security and we believe that our forthcoming AI on-prem capabilities will be uniquely positioned to enable independent and secure AI operations without compromising EDW service levels, a critical differentiator in today’s hybrid cloud landscape. We are continuing to build and execute robust partnerships that position us well in the open ecosystems we see customers increasingly adopting. In the quarter, our teams were collaborating at customer engagements with AWS, Google Cloud, Microsoft Azure, NVIDIA and more. I’ll cover a few examples of how our teams are helping customers trial and implement their strategies for AI with our foundation of managing trusted data. A global Telco’s fraud prevention team leveraged our ClearScape analytics and machine learning to detect targeted fraud and is achieving a 50% increase in fraud detection accuracy. Their model enhances explainability, enabling analysts to make informed decisions with 95% accuracy, while reducing manual effort. A large customer in Asia Pac is evolving its responsible gambling models with help from us. Using our model ops, the customer monitors and manages its machine learning models. They use Clearscape analytics for native analytical models, as well as the bring your own model capability for machine learning models. Their most advanced models are deployed and scored in Teradata Vantage Cloud enabling scalability and lowering costs. We supported a major European airline and elevating analysis of customer feedback, leveraging our vector store and our hugging face model, we help the customer analyze text messages to detect trends and sentiments. This integrated approach is designed to help the customer ensure data protection, enhance performance, and deliver reliable results. We also helped a large grocery retailer demonstrate significant business value by categorizing customer complaints using vector embeddings and bring your own language model functionality. The customer was impressed with the Gen AI integration capabilities of our platform, which streamlined the classification and response process for text-based complaints, thereby enhancing service quality and efficiency. A key aspect was the high performance processing at scale of our differentiated massive parallel processing capability. Also, a top five US healthcare company significantly expanded its Teradata environment as it migrated to the cloud and works to enhance resilience against cyber threats and ensure continuity in healthcare services. It is also implementing a Gen AI solution with us to automate large amounts of audit processes and significantly improve productivity, making the healthcare system work better for everyone. These customer examples are supported with industry reports as well. Teradata was recently named a leader in the Forrester Wave on data management for analytics platforms. We’re pleased to receive this recognition of the strength of our strategic vision and performance in delivering AI-powered enterprise-grade analytics at scale. We believe this report reflects our strong analytic platform capabilities, particularly for hybrid cloud deployments where reliability and scalability are essential. With our solid performance in Q1, our ongoing focus on execution and accelerating innovation that brings trusted AI to our customers, we continue to believe that we will return to growth in 2025. We believe that our differentiated ability to support customers’ data and analytics needs, whether in the cloud, on-prem or hybrid environments, serves us well during these times of uncertainty. As I hand over to Charles, I want to provide an update on our most recent executive appointments. Yesterday, we announced our new CFO, John Ederer, who will be starting with us next week. John is currently the CFO at Model N, a provider of revenue management solutions for life sciences and high-tech. He is a seasoned financial executive and has successfully led a number of companies through SaaS transitions. I’m looking forward to working with John. I also want to thank Charles for serving as Interim CFO during this quarter of transition. I am also pleased to introduce to you today our new Chief Product Officer, Sumeet Arora, who just joined us. Most recently, Sumeet was the Chief Development Officer at ThoughtSpot. Sumeet has extensive experience in leading engineering and product management for AI-driven analytics and a proven track record in building solutions that generate significant revenue. I’ve asked Sumeet to make a few comments on the opportunity he sees as he joins Teradata. Sumeet, over to you.