Data management teams require new capabilities to effectively harness and extract value from expansive volumes of data culled from a growing number of sources. The goal is to reach a maturity level where insights are delivered in real time to keep pace with the operational needs of the business, innovate faster, and build competitive advantages.
Learn more about these trends with the infographic, Data Platforms: The Path to Achieving Data-driven Empowerment.
Teradata and Microsoft have long played a major role in the advancement of data and analytics. An example of this is their new collaboration announcement to bring Teradata VantageCloud Lake and ClearScape analytics to the Microsoft Azure cloud. This partnership aims to provide enterprises with the ability to leverage AI and machine learning (ML) at scale across their organizations to extract value from data, which helps to empower data-driven decision-making and may lead to faster future innovations.
A recent research survey by TechTarget’s Enterprise Strategy Group found that organizations widely recognize the value of data analysis. When asked how they would assess the impact of data analysis for decision-making or as a competitive advantage, an amazing 99% of respondents said the impact was positive (66%) or extremely positive (33%).[1]
The integration of Teradata’s cloud-native platform and ClearScape Analytics with Microsoft Azure services, including Azure Machine Learning, offers customers enhanced analytics capabilities and the opportunity to explore generative AI.
We have seen interest in generative AI gaining significant traction across industries. If fact, TechTarget has seen a 2,699% growth in generative AI editorial and content consumption over the past 6 months.[2] Recognizing this growing demand, Teradata and Microsoft are leveraging their expertise and innovative technologies to help organizations harness the power of generative AI to drive improvements in business performance and customer experiences.
There are two important solutions that Teradata and Microsoft are bringing to market. The first is Teradata’s VantageCloud Lake on Azure, which serves as a foundation for delivering AI and ML. In the recent Enterprise Strategy Group research survey, organizations reported that they overwhelmingly procure their data repository tools in public clouds like Azure.[3] VantageCloud Lake on Azure provides a modern cloud-native architecture that separates compute and storage to offer independent, elastic, and multicluster compute capabilities against Azure Data Lake Storage. This combined solution enables Azure customers to execute a wide range of analytic workloads, including AI/ML, with harmonized data across their organizations. The offering also includes an exclusive high-availability feature that enhances cloud availability and optimized system sizes for improved overall uptime.
The second solution is ClearScape Analytics, coupled with Azure Machine Learning. This combination of technologies is designed to deliver analytics capabilities for AI, ML, and generative AI use cases. Teradata’s ClearScape Analytics and Microsoft Azure ML provide end-to-end analytic pipelines, encompassing data preparation, model training, and operationalization at scale.
When combining data from VantageCloud Lake with ClearScape Analytics and Azure ML, businesses can activate analytics across the enterprise and explore new generative AI use cases. This collaboration between Teradata and Microsoft demonstrates their continued commitment to advancing data and analytics and empowering organizations to embrace cutting-edge technologies to drive innovation at an enterprise scale.
[1] Source: Enterprise Strategy Group Research Report, Data Platforms: The Path to Achieving Data-driven Empowerment, June 2023.
[2] Source: Core Topic Activity Growth Report (Worldwide, TTGT only, All Segments, July ’22-Dec ’22 vs. Jan ’23-Jun ’23).
[3] Source: Enterprise Strategy Group Research Report, Data Platforms: The Path to Achieving Data-driven Empowerment, June 2023.
Increased IT complexity and the need to focus resources on strategic initiatives are pushing IT leaders to embrace product options that support technology convergence and platform consolidation. Integrated solutions from multiple vendors are a viable option to achieve those goals. Research from TechTarget’s Enterprise Strategy Group found that boosting IT team productivity is the leading business driver for buying integrated solutions and that business expectations are being fully met or exceeded in a majority of cases.
Various challenges complicate the process of researching, evaluating, purchasing, and deploying integrated solutions from strategic vendor partners. Research by TechTarget’s Enterprise Strategy Group found that current users encounter unique challenges in each stage—and for each stage, only about one-fifth of survey respondents said they didn’t experience any challenges. The often self-guided education that occurs during the research stage of the buyer’s journey is critical not only for solution selection, but also for project success and follow-on investments with the providers of the integrated solution. Buyers need to push solution vendors to address common challenges, while partnering vendors must take a unified approach in doing so.
To assess the current and future landscape for data platforms, including supportive technologies and processes, Enterprise Strategy Group surveyed 354 IT professionals in North America (US and Canada) involved with decisions for data and analytics, modern tooling, data technologies, and data-centric processes in their organization.
This study sought to answer the following questions:
Data protection has never been as challenging as it is today, thanks to the continuing adoption of virtualization and private cloud architectures, the specter of ransomware, the unfettered growth in unstructured data, increased compliance regulations, consolidation initiatives, and aggressive service-level agreements.
Data protection is evolving to adjust to new IT infrastructure driven by digital transformation, cyber threats, legal mandates, and the risk of data loss.
Data protection software and services are essential for preventing downtime, ensuring IT continuity, and facilitating system and data recovery. They are also crucial in the fight against ransomware.
Enterprise Strategy Group’s Data Protection analysts and demand-side research cover the technologies and services available, both in the data center and in the cloud, including:
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Artificial intelligence (AI) is transforming the world of backup and recovery, bringing new opportunities and challenges for organizations that want to protect and leverage their data assets for business value. AI can help automate backup and recovery processes, improve data security and resilience, enable data reuse and insights, and optimize costs and performance. However, AI […]
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A significant shift toward the use of data for real-time decision-making is becoming a reality for all sizes of companies, as technology in this market has innovated and matured over the past few years.
Digital transformation and digitizing data have brought things like data governance, stewardship, observability, and ITOps into the spotlight.
High-quality data is a prerequisite for reliable and trusted analytics and AI results. Analytics initiatives won’t pay off as expected unless the underlying data is aligned with them.
Enterprise Strategy Group’s Data Platforms analysts and demand-side research cover every aspect of an organization’s data platform strategy and technology framework, including:
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This Complete Survey Results presentation focuses on data user trends, data classification and lineage, drivers behind data governance strategies, challenges with data governance adoption, the impact of AI on data governance, the importance of data governance elements, and investment plans. Already an Enterprise Strategy Group client? Log in to read the full report. If you are […]
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Infographic | September 18, 2024
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To find more value from constantly growing data sets and to become more data-driven, organizations are prioritizing investments in big data and data analytics initiatives.
Companies must quickly, easily, reliably, and securely process, merge, transform, and transact with data to derive value and insights at the speed of business.
Organizations must improve data management efficiency to effectively leverage their data.
According to our research, two-thirds of organizations are turning to automation to gain efficiency: The second-most researched automation-related topic among IT buyers whose purchase research we observe is Business Intelligence and Analytics. Our Data Analytics & AI analysts and demand-side research help tech vendors succeed in this rapidly evolving market by covering essential topics that include:
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Artificial intelligence (AI) is transforming the world of backup and recovery, bringing new opportunities and challenges for organizations that want to protect and leverage their data assets for business value. AI can help automate backup and recovery processes, improve data security and resilience, enable data reuse and insights, and optimize costs and performance. However, AI […]
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In today’s data-driven world, the power of artificial intelligence (AI) and advanced analytics is undeniable. They have the potential to revolutionize industries, drive innovation, and unlock valuable insights. However, behind every successful AI and analytics initiative lies a crucial foundation: excellent data management capabilities.
In a recent research survey from TechTarget’s Enterprise Strategy Group, Data Platforms: The Path to Achieving Data-driven Empowerment, when they were asked about the most important areas of their data platform, 31% of organizations ranked data management, including databases, at the top. In the same survey, 50% of participants identified faster business decision-making as the leading driver and goal for their modern data platform strategies, with 19% focused on creating competitive advantage. Database performance is critical to reaching the data-driven outcomes desired by organizations.
Oracle has introduced its latest addition to the Exadata database machine family, the Exadata X10M, which is powered by AMD’s EPYC server processors. This release marks a significant milestone for Oracle and its database performance capabilities. The Exadata platform is known for its co-engineered hardware and software, specifically designed to support enterprise data management. It offers a complete stack system with optimized processors, memory, and storage, as well as system software for efficient data storage, indexing, and movement. With the Exadata X10M, Oracle continues its commitment to delivering high-performance database servers by leveraging AMD’s EPYC CPUs, incorporating up to 96 multithreaded cores, DDR5 memory, and RDMA over Converged Ethernet (RoCE) for low-latency, high-bandwidth connectivity.
Oracle’s optimization efforts extend beyond hardware to its software stack, ensuring linear scalability and maximum performance across multiple cores. The Exadata X10M stands out with its high performance, surpassing its predecessor, the X9M, in terms of OLTP performance, analytics, and database consolidation. Oracle’s decades-long expertise in both enterprise database software and hardware solutions enables the company to provide a tailored data management platform that combines performance, value, and cost-effectiveness.
Customers can deploy Exadata on-premises, in the cloud, or as a hybrid solution, benefiting from Oracle’s collaboration with public cloud providers and high-speed interconnectivity options. Overall, Oracle’s focus on innovation and customer-centric solutions positions Exadata X10M as a compelling choice for organizations seeking high performance in their data management and analytics initiatives.