Thank you, Chad, and hello everyone. Thanks for joining us today. In 2024, we delivered $609 million in Cloud ARR and $1.474 billion of total ARR, as we advanced in our strategy with our hybrid cloud platform for Trusted AI. As we discussed on the last call, we see that companies everywhere are exploring how to best leverage the potential of AI and Gen AI, and they are realizing the requirement for managing massive volumes of data that will grow exponentially. Before we get into the details of our results, we also announced that Claire Bramley is moving on from Teradata, to take a Chief Financial Officer position at another company outside of our industry. We have a search process underway and Charles Smotherman, our Chief Accounting Officer, will assume the Interim CFO position. Charles will continue to work closely with Claire to ensure a seamless transition until her departure on March 31st. Claire has been instrumental in supporting the company’s transformation to a cloud leader. We are grateful for her operational excellence and outstanding financial leadership in driving durable profitability and free cash flow during her tenure. Claire, on behalf of everyone at Teradata, we wish you the best in your new role. Shifting back to our results, despite a challenging year, we took significant actions in 2024 that position us to return to total ARR growth this year. We named a new CRO, restructured our go-to-market organization, and executed cost actions that reduced expenses across the business. We also reoriented the organization to win with AI and introduced a sweeping set of innovations designed to strongly position us with our hybrid trusted AI platform. As we pivoted to AI, we also launched new partnerships, with, for example, Nvidia, and strengthened partnerships with the major CSPs. We are firmly focused on returning the company to growth in 2025, and execution is job number 1. Our go-to-market organization has settled in from the mid-year restructuring, and we are expecting continued improvement in execution from our go-to-market teams. As an example, the Financial Services team we created is allowing us to pursue emerging AI-based industry use cases that we believe our technology best enables. We also have proof of concepts underway for Generative AI for CX, a major Gen AI use case. Additionally, we are releasing a series of Customer Experience AI use cases that customers can quickly implement and are designed to drive improved results around customer churn, next best action, customer journey and hyper-personalization. Our customer success team is doubling down on delivering Innovation Days curated to each customer’s needs and helping to extend the deployment of our technology across our base. In 2025, we are expecting a meaningful improvement in retention rates over 2024, for both total and on-prem ARR. We started to see improvement in retention rates in the second half of 2024, and are looking to carry that forward this year. With these initiatives taking hold, we believe we are well positioned to execute and return to growth this year. Just as we made a pivot in 2020 to cloud-first, we started the pivot in 2024 towards being the trusted hybrid AI platform at enterprise scale. Companies have data both in the cloud and on-prem, and we see them becoming more sophisticated in how they think about leveraging and balancing hybrid capabilities. It is not about choosing between environments anymore, it's about effectively operating across both in order to meet diverse business needs and drive faster decision-making, at the scale they require. Our teams are taking our hybrid cloud platform and Trusted AI positioning to our customers. We believe our hybrid capabilities of cloud and on-prem, along with our open and connected approach are unmatched. We are continuing our disciplined approach to managing our financial plan, investing in extending our technology strengths and promoting Teradata as a leader in data analytics, Trusted AI, and hybrid cloud technology, while prudently managing costs. In 2025, we are adding to our strong tech stack, building upon the broad set of innovations we delivered in 2024. As more companies look to hybrid compute environments of both cloud and on-prem, increasingly adopt technologies to support AI, and embrace the industry move to open table formats, we believe we are well positioned. On our last call, I talked about the innovations we introduced last quarter. Among those were new bring your own large language model capabilities designed to help customers take advantage of small or mid-sized open LLMs, including domain-specific models to deploy Gen AI use cases, while minimizing expensive data movement, integration of NVIDIA’s AI accelerated compute platform to accelerate AI workloads and our Customer Complaint Analyzer solution, designed to help companies leverage AI to improve customer experiences. We introduced rapid-start Gen AI use cases with the integration of our VantageCloud platform with Amazon Bedrock. With this integration, customers gain access to more than 60 Gen AI use cases that can help them deliver exceptional customer experiences, boost productivity, and streamline business processes. Additionally, Teradata was one of the early vendors with AI solutions offered in the new Microsoft Fabric Workload Hub. We also announced API integration with Google Cloud Gemini models designed to take advantage of more data for better Gen AI outcomes. As we start 2025, our focus is on the future as we work to bring out significant new capabilities designed to help companies bring trusted AI to enterprise scale, in the cloud and in the hybrid environments customers need. Let’s look at our new Enterprise Vector Store as one example. To get the most value out of generative AI and Agentic AI applications, enterprises are looking to extract insights from both structured and unstructured data. Unstructured data has been difficult to leverage in traditional data management practices, yet is growing three times faster than other data types. Teradata supports vectors in our Vantage system today, for AI applications that are built on our bring your own large language model capabilities. Now, we are bringing it to full enterprise scale. Our Teradata Enterprise Vector Store is in private preview this quarter and brings a scalable, in-database solution that supports the full lifecycle of vector data management at Enterprise Scale. From embedding generation and indexing to metadata management and intelligent search, all processes are seamlessly integrated within our existing Vantage environment. Here, we are also partnering with Nvidia to provide GPU-accelerated document processing or autonomous AI agent use cases, such as augmented call centers. You will be hearing more in the coming weeks about this exciting addition that we believe will kickstart RAG and Agentic AI applications. Then, coming shortly afterwards, we are planning to bring our on-prem customers new ways to accelerate AI opportunities, providing them with an easy way to enable AI/ML capabilities, including large-scale AI RAG pipelines, while honoring data sovereignty requirements. We have many customers in regulated industries that have strict requirements for data security, and our new capabilities are designed to enable independent AI without impacting their EDW service levels. We believe our deep analytics, our open and connected platform, and bring your own model integrations are the foundation enterprises will demand and we have these now. Our strong capabilities were recently recognized in the 2025 Gartner Critical Capabilities report for Cloud Database Management Systems for Analytical Use Cases. We placed among the top 5 companies across every evaluated use case. Now, I’ll walk you through a few examples that illustrate how our customers are investing in Teradata to help address new AI and analytics use cases. One of the largest life insurance companies in India signed a multi-year deal for our platform and consulting services. This new customer selected Teradata because of the comprehensive AI capabilities included in ClearScape Analytics, such as model lifecycle management with ModelOps, the enterprise feature store and in-database language models, as well as our strongly competitive pricing. A large Japanese bank has shown it can successfully reduce costs and improve processing times by replacing a legacy HPC cluster used to perform Monte Carlo simulations at huge scale with a system that relies on the native massive parallelism of our Vantage platform in conjunction with NVIDIA GPUs. A global technology leader spent significant time and millions of dollars trying to implement competitive offerings. After demonstrating our VantageCloud and ClearScape capabilities, this large enterprise decided to focus on a hybrid environment of cloud and on-prem. We have a fast start in 2025 to help them establish their new data and AI capabilities, including taking advantage on our Gen AI capabilities. As I close, I want to emphasize that we are laser focused on returning to Total ARR growth. Building upon our technology and innovation foundation in the cloud, we believe we have the trusted hybrid AI platform at the enterprise scale that the world’s leading organizations require. We are excited about our capabilities in delivering AI and Agentic AI solutions at scale, especially in the hybrid environments customers need now. We are seeing positive traction from our go-to-market restructuring and improvement in pipeline quality. The pace of technology innovations, both organically and with partners, has increased and we look forward to monetizing these advancements this year. In 2025, we expect to achieve Cloud ARR growth of 14% to 18% and flat to 2% growth in Total ARR, as we build our future. Now, I’ll turn the call over to Claire.