The autumn conference season has been packed with events showcasing advancements in enterprise data technology, and here I want to highlight the latest from Teradata, AWS, Infor and LogicMonitor. Each of these companies has a distinct data management approach, yet all convey a core message that can sometimes get lost amid all the AI hype in the market today: data is central to innovation and business transformation.
Companies like these come from different perspectives to advance the scope and quality of data management as a foundation for everything from IT integration and analytics to real-time monitoring and AI-driven insights, and this focus on data management will only grow more important as their customers’ data estates and use of AI expand. Let’s recap these four events and consider how each company’s approach ties into this data management theme.
Teradata Possible 2024 Explores Intersection Of Data and AI
Teradata Possible 2024 in Los Angeles focused on the importance of effective data management in AI, particularly when integrating LLMs with existing enterprise data to enable more comprehensive analysis. This can reveal previously unseen patterns and trends, leading to a better understanding of the data and improving company processes.
At the event, Teradata highlighted its VantageCloud platform, focusing on its features for AI and machine learning, data management and cloud environments. The company has designed VantageCloud to provide a unified cloud environment for managing the entire AI/ML workflow, from data preparation to model deployment and monitoring. This could allow businesses to develop and implement AI solutions more efficiently. A key announcement at the show was a new partnership with Nvidia to develop an on-premises AI solution that integrates with cloud-based AI tools. The partnership allows users familiar with tools from the likes of AWS (SageMaker Studio), Google (Vertex AI Studio), Microsoft (Azure Machine Learning Studio) or OpenAI (Playground) to work within those environments while leveraging Teradata’s platform.
Teradata emphasized how its platform accelerates data preparation, model training and deployment for faster time-to-value. The company also stressed its commitment to open data ecosystems. Such ecosystems enable businesses to combine data from different sources for a more complete view, but ideally they also make data management easier by reducing integration tasks; ultimately, this should lead to better AI models and better insights from them. Teradata also discussed the role of responsible AI development, highlighting the ethical considerations of data management.
Teradata’s focus on AI integration for data management is a necessary step to stay competitive. The Nvidia partnership and open ecosystem strategy are positive moves, but success depends on how well VantageCloud meets the evolving demands of enterprises. The emphasis on responsible AI is essential, but Teradata must also innovate faster and adapt to the rapidly changing AI landscape to remain relevant.
AWS Generative AI Analyst Summit Emphasizes Data Management
The AWS Generative AI Analyst Summit held in Seattle provided valuable information about AWS’s strategy and vision for generative AI. There was a lot of focus on the importance of data quality, management, accessibility, security and privacy for maintaining the accuracy and reliability of AI models, both during training and in generative AI applications. For example, AWS highlighted the need for encryption and access control measures to protect sensitive information. The discussions also addressed Amazon’s approach to responsible AI, emphasizing fairness, transparency and accountability.
The summit also showed how AWS is integrating generative AI across its own offerings. This includes enhancing existing services such as Amazon S3 with improved data handling and storage, and by introducing new purpose-built tools for managing data specifically for generative AI applications to improve efficiency and innovation. Speakers also highlighted additional cloud-based tools, including AWS Glue for data preparation, Amazon Redshift for analytics and Amazon SageMaker for building AI models.
The event concluded with a Seattle Seahawks football game, highlighting AWS Sports’ work with the NFL. AWS announced it will continue as the Seahawks’ cloud provider for machine learning, AI and generative AI. The team plans to use AWS technologies including Bedrock to automate content distribution by transcribing, summarizing and sharing press conferences in multiple languages. My colleague Melody Brue and I recently featured Julie Souza, AWS’s global head of sports strategy, in an episode of our Game Time Tech podcast to discuss how technology can improve fan engagement—with applications that extend to other industries.
This week’s AWS re:Invent 2024 conference is anticipated to deliver improvements to data management tools with a focus on AI/ML. Expect enhancements to core services such as Amazon S3 and SageMaker, possibly including automated data classification and improved data discovery. AWS Glue may see advancements in data integration and ETL capabilities, including improved data quality features and tighter serverless integration. For Amazon Redshift, anticipate new features focused on performance, scalability and advanced analytics. Beyond core services, AWS might also introduce some new ways to leverage generative AI for data management tasks and unveil industry-specific data management solutions.
AWS has put its attention toward data quality, security and responsible AI practices to address the challenges of the competitive AI market. The partnership with the Seahawks is a great example of using AI in the sports industry, and it shows the potential for broader industry-specific applications. The expected updates to data management tools at re:Invent 2024 are in line with AWS’s existing efforts to address the demands of AI-driven workloads while adapting to quickly evolving customer and industry requirements.
Infor’s Velocity Summit Addresses Data Management Modernization
The Infor Velocity Summit in Las Vegas emphasized data management, generative AI, process mining and industry-specific solutions, highlighting how all of these support enterprises in modernizing their ERP systems—and how they apply to Infor’s own cloud ERP system, CloudSuite. This modernization is an important theme across the ERP space, because it is essential for connecting data across the business, providing real-time insights, enhancing collaboration, supporting better decision making and ultimately improving operations. ERP modernization also helps companies scale to accommodate growth and enables the adoption of emerging technologies to remain competitive and adapt to changing industry demands.
The event detailed how AI-powered data management can simplify complex data tasks. For example, AI and robotic process automation capabilities provided from the Infor OS platform can automate repetitive data entry while reducing errors by extracting information directly from documents such as invoices. It can also improve data quality by identifying and correcting inconsistencies, such as variations in customer names or date formats. AI can process large datasets to identify trends and patterns, and deliver value through summarizations, comparisons, content creation and translation. These functions can be used in a wide variety of enterprise scenarios, for example to improve master data quality.
Infor emphasized the role of tailored industry solutions in improving data management and process mining. CloudSuite is designed to enable businesses to connect data from diverse sources specific to their industries. For example, healthcare providers can integrate patient records with billing and clinical data to create a more comprehensive dataset. These solutions also address regulatory compliance by supporting industry-specific standards such as HIPAA or SOX. Furthermore, they allow the creation of reports and dashboards focusing on key industry metrics, which should simplify performance monitoring and evidence-based decision making.
Infor’s strategy of incorporating AI-powered data management into its industry-specific ERP solutions holds significant value. This approach could be a key differentiator for it in the ERP market. From my experience, the true measure of success will lie in effectively implementing these solutions and Infor’s ability to drive tangible benefits. As with any ERP, successful adoption hinges on effective change management and ensuring high-quality data. As the ERP landscape evolves, Infor must maintain its innovation efforts to stay competitive while continuing to support its customers in embracing ERP modernization.
LogicMonitor: Data Management For Hybrid Observability
LogicMonitor’s Analyst Council 2024 in Austin centered on “hybrid observability,” a strategy for managing complex IT environments spanning on-premises systems, cloud services and edge devices. A key highlight was the discussion of Edwin, LogicMonitor’s generative AI-powered assistant for IT observability. Edwin automates routine tasks, analyzes large datasets and delivers insights to help IT teams address issues and make informed decisions.
The LogicMonitor platform centralizes observability data from diverse sources, contextualizes it for analysis and integrates with tools such as ERP, CRM and monitoring systems to provide a unified operational view. Its AI-powered features aim to prioritize critical issues, reduce alert fatigue and use predictive analytics and automated root cause analysis to prevent and resolve problems efficiently.
Following LMAC24, LogicMonitor announced that it received an $800 million investment to integrate AI into datacenter operations and strengthen its role in the hybrid observability sector, focusing on reducing costs, increasing efficiency and scaling AI capabilities. With a valuation of $2.4 billion, the company is addressing challenges such as managing complex cloud environments, improving cost efficiency and promoting sustainability. As it competes with firms such as Datadog and Dynatrace, LogicMonitor’s ability to succeed will depend on global expansion, ongoing innovations in data management and delivering measurable results. For customers, these efforts could lead to reduced downtime, better resource allocation and enhanced security, allowing IT teams to shift from reactive tasks to driving innovation and improving service delivery.
Strong Data Management Is Vital For Everything Enterprises Want To Achieve In IT
Attending these events was a good reminder of the diverse approaches to data management being taken today. Teradata’s focus on AI integration and open ecosystems, AWS’s broad range of cloud-based tools and generative AI advancements, Infor’s industry-specific solutions and focus on ERP modernization and LogicMonitor’s hybrid observability platform each present innovative ways to leverage data for business value. The common thread was clear: effective data management is crucial for navigating the complexities of modern enterprise technology, and even more so when it comes to getting the most out of AI. Collectively, these companies show that data as more than a resource—it’s a catalyst for innovation.
I have spent a lot of time voicing my advice that every enterprise needs a strong data management strategy to take advantage of technologies that will help it grow and have a competitive advantage. Effective data management builds trust and reliability, enabling businesses to grow while addressing challenges in scalability, security and data accessibility. The ability to harness the power of data, whether through AI, cloud technologies or specialized solutions, will be key to unlocking new insights and optimizing operations. For these reasons, data management will continue to be a critical need for organizations across all industries.
