Real-time Analytics News for the Week Ending March 8

Keeping pace with news and developments in the real-time analytics and AI market can be a daunting task. Fortunately, we have you covered with a summary of the items our staff comes across each week. And if you prefer it in your inbox, sign up here!

This week’s Gartner Data & Analytics Summit shed light on many of the issues organizations face today as they expand their use of advanced analytics and AI. A theme throughout the conference was that, through 2025, poor data quality will persist as one of the most frequently mentioned challenges prohibiting advanced analytics and AI deployment. Because of this, Gartner believes data and analytics (D&A) leaders must focus on three interdependent journeys to advance enterprises’ AI initiatives. These journeys include business outcomes, D&A capabilities, and behavioral change.

Gartner speakers at the summit made specific recommendations about what organizations can do with respect to each of these three areas. They include:

Journey to Business Outcomes

Gartner advises D&A leaders to prioritize value in demonstrating AI’s business outcomes. Specifically, D&A leaders can take the following actions to best affect business outcomes:

• Establish trust models: Trusted, high-quality data is key to enabling a data-driven enterprise, yet many AI initiatives fail because of poor data quality. Trust models look at the value and risk of data and provide a trust rating based on lineage and curation.
• Monetize productivity improvements: D&A leaders must consider the value and competitive impact as it relates to total cost, complexity, and risk.
• Communicate value of D&A: Consider all costs, including data management, governance, and change management.

Journey to D&A Capabilities

D&A leaders must ensure they are using a range of tools and technologies to build their technology stack when it comes to AI solutions. To achieve this adaptability, D&A leaders must:

• Create a modular and open ecosystem: Update or replace architecture components to address new requirements and rapidly changing technologies.
• Make data AI-ready and reusable: Integrate trust into FinOps, DataOps, and PlatformOps to transition from a tech stack to a trust stack.
• Explore AI Agents: Utilize dynamic agents that adapt to changes using an AI-ready data ecosystem powered by active metadata.

Journey to Behavioral Change

Focusing on data governance, value communication, and analytics augmentation is vital, but addressing the human aspect is crucial for AI success. To lay the foundation for the proper culture to best adopt and utilize AI, D&A leaders should take the following steps:

• Establish repeatable habits: Prioritize training and education with an emphasis on data and AI literacy.
• Embrace new roles and skills: Develop roles that facilitate adaptation to GenAI’s change management requirements.
• Collaborate with others: Work with diverse teams, including security and software engineering, for seamless integration.

See additional RTInsights coverage of the summit:

Real-time analytics news in brief

Alation announced the launch of its Agentic Platform. This reinvention of the data catalog for the AI era introduces the use of agents to automate and guide data discovery, governance, and compliance management. In addition, Alation also announced its AI Agent SDK, with support for Anthropic’s Model Context Protocol (MCP), enabling partners and customers to build agents and applications leveraging the data intelligence capabilities of the Alation Platform.

In other Alation news, the company introduced Alation Data Quality (DQ), an AI-native solution that restores trust in data by identifying and proactively monitoring critical data assets and automatically applying relevant quality rules.

Actian, the data division of HCLSoftware, announced advancements to the Actian Data Intelligence Platform (formerly known as the Zeenea Data Discovery Platform). The platform, which follows the acquisition of Zeenea last year, centralizes data catalog, active metadata management, data quality and lineage, data governance, and enterprise data marketplace capabilities. With its ability to automate data discovery and support governed data usage, enterprises can make confident, informed decisions while ensuring security and compliance.

CData Software announced the expansion of its collaboration with Google Cloud, further extending data access capabilities for Google Cloud users. This collaboration enables users to connect Google Cloud services with many common external data sources, including SaaS applications, NoSQL databases, legacy systems, and more. As such, CData Embedded Connectors simplify data access, accelerating time-to-value for data-driven initiatives.

Ceramic.ai emerged from stealth with software for foundation model training infrastructure that enables enterprises to build and fine-tune their own generative AI models more efficiently. The software platform’s model can train with long contexts and any cluster size, enabling enterprises to develop, train, and scale their own AI models faster than traditional methods. For smaller models, Ceramic.ai is up to 2.5x faster on NVIDIA H100 GPUs than current state-of-the-art platforms, and for large-scale long-context models, Ceramic.ai is the only viable choice for fast training.

Chainguard, a Sequoia-backed unicorn that helps organizations build secure code from scratch, announced Federal Information Processing Standards (FIPS) image builds for Apache Cassandra, a first-of-its-kind achievement in the open-source community. Chainguard created Cassandra-FIPS to help enterprises build FIPS compliance at the start of their software supply chains so they can meet compliance requirements from the beginning and provide their end customers with stronger assurance of product security.

Cirrascale Cloud Services announced the availability of an Inference Cloud powered by the Qualcomm AI Inference Suite, a solution designed to streamline the deployment of AI models and applications with a single click. Built to meet the growing demand for generative AI, this suite enables businesses to harness efficient, scalable AI from the cloud. With the Inference Cloud powered by the Qualcomm AI Inference Suite, customers pay only for their AI model usage, seamlessly accessing models through API endpoint interfaces. This approach ensures affordability and simplifies integration, bringing cutting-edge AI capabilities to businesses of all sizes.

Couchbase launched Couchbase Edge Server, an offline-first, lightweight database server and sync solution designed to provide low latency data access, consolidation, storage, and processing for applications in resource-constrained edge environments. Couchbase Edge Server is built on the Couchbase Lite core engine, an AI-ready embedded database that customers rely on for running critical applications on hundreds of thousands of client devices.

data.world announced the public beta launch of Archie Chat, an AI-powered catalog assistant that enhances how users interact with their enterprise data catalog. The solution combines the power of knowledge graph technology with modern language model architecture to create a more intuitive data discovery experience. Additionally, Archie Chat helps users find answers to their questions quickly through natural language conversation, driving catalog adoption and enhancing data discovery across organizations.

Data Ramp announced the launch of its latest patented version of fetchcx, which is purpose-built for regulated industries like banking, insurance, and healthcare to optimize data within their own cloud, Azure, AWS, or GCP. fetchcx embraces Lakehouse methodologies, providing a foundational, low-friction first step in progressively improving the quality of raw data. By deploying within the client’s cloud, the service ensures that sensitive data remains under the organization’s control while benefiting from advanced data optimization techniques.

H2O.ai announced a Model Risk Management (MRM) framework for Generative AI, bringing rigorous validation, compliance, and transparency to Generative AI applications in financial services, banking, and other highly regulated sectors. The solution provides a structured evaluation framework that integrates automated testing and evaluation with human calibration, model weakness and failure identification, bias detection, and explainability tools, offering enterprises the ability to validate and mitigate AI-related risks before deployment.

Immuta announced Immuta AI, a new foundational layer within the Immuta Platform, designed to infuse AI across the platform to enhance data governance at scale, including seamless integration with Immuta’s Data Marketplace to further streamline access to governed data. As the first capability within Immuta AI, the company is also introducing Immuta Copilot, an AI-powered policy creation and automation tool that helps data governance teams streamline governance and accelerate secure data access.

Lenovo introduced the ThinkEdge SE100, an entry-level AI inferencing server designed to bring AI capabilities to the edge for SMBs and enterprises. The SE100 is positioned as a cost-effective and scalable option for businesses looking to extend AI processing beyond traditional data centers. Its compact size makes it ideal for constrained spaces without compromising performance. The server is designed to handle AI workloads, like real-time inferencing, video analytics, and object detection across telco, retail, industrial, and manufacturing environments.

Nexla announced a major update to the Nexla integration Platform, expanding its no-code integration, RAG pipeline engineering, and data governance capabilities to make enterprise-grade GenAI accessible to everyone. Nexla uses AI to connect, extract metadata, and transform source data into human-readable data products, called Nexsets, that enable true data reuse and governance. Its agentic RAG framework lets companies implement RAG for agents and assistants without coding and uses LLMs during each stage to improve accuracy. This latest release introduces several capabilities that, combined, help companies deliver enterprise-grade GenAI without having to rely on specialized AI developers.

Precisely announced Data Link, a partner program designed to streamline the integration of the Precisely data portfolio with data from trusted providers via pre-linked datasets. The new Data Link program transforms the traditionally complex and time-consuming process of mapping disparate third-party datasets into a seamless customer experience. Inaugural partners include Precisely, GeoX Analytics, Overture Maps Foundation, and Regrid, with additional partners coming soon.

Qdrant introduced new enterprise capabilities in Qdrant Cloud that are designed to remove operational bottlenecks and empower large-scale AI deployments. The latest updates include single sign-on (SSO), cloud role-based access control (RBAC), granular database API keys for granular RBAC, advanced monitoring and observability with Prometheus/OpenMetrics to connect external monitoring systems and a cloud API for seamless automation.

R Systems International (a Blackstone portfolio Company) announced the launch of its IoT Smart C2C Connector. Built on Amazon Web Services (AWS), the IoT Smart C2C Connector solves challenges faced by service providers in managing and integrating a diverse range of smart home devices. The R Systems IoT Smart C2C Connector, built with AWS IoT Device Management capabilities, enables secure bidirectional communication between smart home devices and OEM clouds, delivering a simplified, secure, and scalable approach to smart device management.

SIOS Technology announced that SIOS LifeKeeper and SIOS DataKeeper clustering software have been validated for use with Cimcor’s cybersecurity solution, the CimTrak Integrity Suite. This collaboration allows Cimcor customers to seamlessly integrate high availability and disaster recovery into their CimTrak environments, ensuring continuous protection against cyber threats and minimizing downtime in critical cybersecurity operations.

Teradata announced Teradata Enterprise Vector Store, an in-database solution that brings the speed, power, and multi-dimensional scale of Teradata’s hybrid cloud platform to vector data management, which is a crucial element for Trusted AI. Featuring the ability to process billions of vectors and integrate them into pre-existing enterprise systems, with response times as quick as in the tens of milliseconds, Enterprise Vector Store is designed to cost-effectively deliver the sophistication required for getting real value out of complex, multifaceted business challenges.

VDURA announced the launch of its V5000 All-Flash Appliance, engineered to address the escalating demands as AI pipelines and generative AI models move into production. Built on the VDURA V11 data platform, the system delivers GPU-saturating throughput while ensuring the durability and availability of data for constant operating conditions, setting a new benchmark for AI infrastructure scalability and reliability.

If your company has real-time analytics news, send your announcements to [email protected].

In case you missed it, here are our most recent previous weekly real-time analytics news roundups: