Tech News

Unlock Business Value with GenAI Through a Data Semantic Approach

Published

1 month ago

October 7, 2025

By Robert Thanaraj, Sr Director Analyst at Gartner

Semantic representations of information are crucial for the functionality of large language models (LLMs), which is fuelling a heightened focus on semantics within data and analytics (D&A) and AI.

Data silos become entrenched and limit an organization’s capacity to draw insights from its data. Without understanding the relationships within data, the individual pieces of information become less useful.

Semantic approaches facilitate a shared understanding of business terms and their interrelationships, which is vital for providing the necessary context for generative AI (GenAI). In a Gartner survey on the evolution of data management, 44% of the respondents from AI-ready organizations reported that semantic alignment is a key factor in assessing the AI readiness of their data.

D&A leaders can enhance and expand their semantic understanding by leveraging emerging technologies such as knowledge graphs and augmented data catalogs, thereby unlocking greater value from their information resources.

What is Data Semantics?

Data semantics refers to the meaning and interpretation of data within a business-specific context, as opposed to focusing on the physical representation of data through a data dictionary or a business glossary. It involves understanding what a data element represents, how it should be used, and its relationships with other data elements. Without this understanding, data is of limited use for AI use cases.

Semantic modeling is a practice of connecting technical metadata with business metadata.

A business glossary serves as the foundation for all things “semantic,” documenting the meanings of business-related terms. When the semantics and rules of a business glossary are well-understood, it leads to better data quality, easier integration and greater usefulness, supporting interactions with LLMs. The glossary also supports business goals like reducing costs and managing risks by making definitions clear, consistent and easy to trace back to their sources.

Top Recommendations for D&A leaders

-Upskill your data engineers with semantic modeling techniques such as the use of knowledge graphs in building business ontologies.
-Introduce DataOps practices to “deliver value from data” more easily, quickly and broadly. Take a people-, product- and governance-centric approach.
-Invest in converged data management platforms. Establish a platform engineering team that produces platform services for platform tenants.

Key Benefits of Data Semantics

Leveraging and governing semantics effectively enables:

–Improved Data Understanding: Both people and applications gain a unified view of data and its structure. For example, if several medical e-commerce sites use consistent relationships between terms, applications can extract and aggregate information across these sites to support user queries or serve as input for other applications.
–Knowledge Reuse: Relationships uncovered by one group can be reused or built upon by others for new use cases, allowing previously identified connections to be embedded in future work.
–Enhanced Accuracy with LLMs: Incorporating knowledge graphs into the training and inference processes of LLMs serves as a factual base (i.e., data and metadata source) for mitigating errors and hallucinations.
–Enhanced Interoperability and Innovation: By adopting semantic modeling, organizations open themselves to a wider range of use cases and enable more effective data interchange.

Link Data from Different Sources to Derive Data Relationships

Semantic reconciliation plays a crucial role in effectively linking data from different sources. It is also essential for inferring relationships between disparate datasets. Without a clear understanding of the relationships, correlations and distinctions among the meanings of data from different modalities such as text, videos, images and structured data, organizations cannot fully realize the potential of their data assets.

Modern semantic tools use algorithms to find connections in data. These tools recommend the best ways to clean, organize and analyze information. They also track where data comes from and how it is used for better governance.

With augmented data discovery, algorithms automatically detect correlations, segments, clusters, outliers and relationships, presenting the most statistically significant and relevant results. By using these semantic approaches, organizations can connect information from different sources, uncover relationships and gain valuable insights that drive better decisions.

In business ecosystems, the degree of openness is driven by members’ strategies, common goals and shared interests. For example, governments, nongovernmental organizations, charities and community groups can collaborate on health or public policy issues, or in open-source developer communities. This creates an opportunity for exploiting the knowledge of data and the meaning of data in terms of what can be applied to several digital business moments.

Lastly Think Data Semantics Before Introducing Large Language Models

Organizations are spearheading transformative initiatives to implement large language models in order to transform their operations. However, data and analytics leaders often rush to integrate LLM capabilities without first ensuring these tools are aligned with real business outcomes. To maximize value, it’s essential to connect LLMs with robust semantic frameworks.

Knowledge graphs are a powerful foundation for leveraging LLMs in business contexts. These machine-readable data structures capture semantic knowledge about both physical and digital entities. These worlds include entities and their relationships, which adhere to a network of nodes and links forming the graph data model.

LLMs can streamline the creation of ontologies, which define categories and relationships within data. By using “few-shot” learning prompts—providing just a handful of examples—users can guide LLMs to generate base ontologies in open formats that suit their needs. These initial frameworks can then be refined for greater detail as required.

Additionally, LLMs support ontology mapping by helping users align entities and relationships across different datasets or systems. With targeted prompts and sample mappings, organizations can extract relevant connections from their data and improve accuracy through iterative refinement.

By adopting large language models alongside semantic representations like knowledge graphs and ontologies, organizations position themselves for faster deployment of advanced analytics solutions that deliver meaningful business value.

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SAP and Snowflake Unleash the Power of Data and Enterprise AI Across the Business Data Fabric

Published

16 hours ago

November 7, 2025

Integrator Web-Editor

Snowflake, the AI Data Cloud company, and SAP SE, a global leader in enterprise applications and business AI, today announced a new collaboration to enable organizations to seamlessly leverage Snowflake’s AI Data Cloud and SAP Business Data Cloud (BDC) with semantically rich data. The joint effort will make Snowflake’s data & AI platform available as a SAP solution extension for SAP BDC customers. The new offering, SAP Snowflake solution extension for SAP Business Data Cloud, unites SAP’s deep expertise in mission-critical business processes and semantically rich data with Snowflake’s unified platform capabilities for building AI and machine learning solutions. SAP and Snowflake are also enabling zero copy sharing between SAP BDC and Snowflake to help customers get richer insights, build enterprise-grade intelligent applications and unlock AI-powered innovation that fuels business transformation.

“By tightly integrating SAP and Snowflake, we’re making it simple for enterprises to connect their critical business data with its rich context in SAP with the power of seamless AI app and data agent development at scale in Snowflake,” added Christian Kleinerman, EVP of Product, Snowflake. “Enterprises can now innovate faster with Snowflake and SAP BDC and seamlessly share data between the platforms —zero-copy and fully governed.”

SAP Snowflake brings Snowflake into the open data ecosystem of SAP BDC and the business data fabric–empowering customers with greater openness and choice, while extending SAP BDC with Snowflake’s AI, analytics, data engineering, Marketplace, and collaboration capabilities. Customers can use SAP BDC with SAP Snowflake as a cloud-scale compute and storage option to extend the value of their data. Leveraging bidirectional, zero-copy data access, data and AI teams can work with semantically rich SAP data products in real time, within a unified governance framework. As a result, customers can harmonize SAP and non-SAP data while optimizing total cost of ownership across workloads and build agents and AI applications in SAP Snowflake fueled by trusted SAP data products.

“Bringing Snowflake to SAP Business Data Cloud empowers our customers with openness and choice,” said Irfan Khan, President and Chief Product Officer for SAP Data and Analytics, SAP SE. “Together, we combine SAP’s decades of leadership in mission-critical business applications with Snowflake’s modern data platform to deliver a unified, enterprise-ready, and SAP-supported experience that extends the value of business data across the entire ecosystem.”

With SAP Snowflake, customers can:

Build a trusted, AI-ready data foundation to harmonize SAP and non-SAP data: Unify their data landscape with an integrated business data fabric—enabling more seamless zero-copy sharing, enriched modeling, and a complete, business-ready view of their data in real time for all data engineering, analytics, and AI and machine learning workflows across the enterprise.
Accelerate AI business value with semantically rich data: Simplify AI governance, ground AI in organizational knowledge, and build tailored agents—helping to ensure more secure, context-rich, and intelligent applications across the enterprise.
Develop intelligent applications grounded in mission-critical business data: Build, deploy, and continuously optimize intelligent applications faster with a harmonized and democratized data foundation powered by semantically rich, trusted data products that accelerate the pace of innovation and production.

In addition to SAP Snowflake, the partnership also includes SAP Business Data Cloud Connect for Snowflake, a capability enabling bidirectional, zero copy data sharing with Snowflake. Enterprises already using Snowflake can leverage SAP BDC Connect to integrate their existing instances of Snowflake with SAP Business Data Cloud for more seamless, zero‑copy access, providing Snowflake users with real-time access to semantically rich SAP data products—without duplication.

SAP and Snowflake are supporting thousands of customers, including industry leaders like AstraZeneca, as they transform their industries with this partnership.

“AstraZeneca is constantly pushing the boundaries of science and is pioneering in life-changing medicines,” said Russell Smith, Vice President of ERP Transformation Technology, AstraZeneca. “Data and AI are central to achieving this aim, and our close collaboration with SAP and Snowflake complements our ability to access, process and analyze real-time data. This announcement will accelerate our mission and recognizes that every minute matters to make breakthroughs for patients.”

SAP Snowflake is planned to be generally available in Q1 2026. SAP BDC Connect for Snowflake is planned to be generally available in H1 2026.

Tech News

HONOR Celebrates Everyday Heroes in a Cinematic Tribute to Resilience, Courage, and the Human Spirit

Published

2 days ago

November 5, 2025

Integrator Web-Editor

HONOR, unveils its latest campaign film, “Everyday Heroes” – a cinematic tribute to resilience, courage, and the human spirit. The short film marks the launch of the HONOR X9d – the Unbreakable AI Smartphone – a device designed to endure challenges and keep people connected even in the most demanding conditions.

Through this campaign, HONOR continues its mission to merge innovation with emotion, celebrating individuals who reflect the brand’s belief in human-centric technology and everyday strength. The film tells the story of a high-altitude window cleaner — an unsung hero whose daily work symbolizes perseverance and optimism.

A Tribute to Everyday Strength

“Everyday Heroes” is part of HONOR’s broader storytelling approach, showcasing authentic human experiences that reflect the values of perseverance and hope. The campaign positions HONOR not merely as a technology brand, but as a partner in the human journey — recognizing that the greatest innovations are those that serve people.

From the sunrise that marks the beginning of the worker’s day to the emotional final shot of connection and relief, every frame of the film reflects HONOR’s message: strength, empathy, and innovation belong together. The campaign also honors the invisible heroes of modern cities — those whose contributions often go unnoticed but whose dedication keeps the world running smoothly.

Technology Inspired by Real Life

The HONOR X9d combines robust engineering with thoughtful innovation. Its durable structure and water-resistant design are matched by AI-powered features that make communication seamless and secure. This new device represents HONOR’s continuous efforts to build technology that complements human resilience — technology that keep up with life.

By focusing on real stories and relatable moments, HONOR reaffirms its commitment to creating devices that connect people emotionally, not just digitally. The “Everyday Heroes” campaign builds on the brand’s growing reputation for blending empathy with engineering — bringing to life a message that resonates deeply with consumers across the GCC region.

The campaign film “Everyday Heroes” is available to watch on HONOR Arabia’s official social media channel, accompanied by behind-the-scenes content showcasing the production process and the real-life inspirations behind the story.

Tech News

KINGSTON FURY ADDS ITS LARGEST CAPACITY CLIENT PCIE 5.0 NVME SSD

Published

4 days ago

November 4, 2025

Integrator Web-Editor

Kingston FURY Renegade G5 PCIe 5.0 NVMe M.2 SSD with black heatsink and white branding against blue background with motion light streaks

Kingston Digital Europe Co LLP, the flash memory affiliate of Kingston Technology Company, Inc., a world leader in memory products and technology solutions, today announced it has rounded out the Kingston FURY Renegade G5 line with an 8192GB full capacity option for high-power uses from video editing, 3D rendering, to gaming and more.

Optimized for those who need a system that can keep up with their workflow or gaming needs, Kingston FURY™ Renegade G5 PCIe 5.0 NVMe M.2 2280 SSDutilises the latest PCIe Gen5 x 4 controller and 3D TLC NAND to reach speeds up to 14,800/14,000MB/s read/write¹ and over 2M IOPS to provide extreme performance and endurance, and now with over 8TB to store more of your favorite games and media without losing system responsiveness.

“Whether for work or play, users need more power and space,” said Liny Cheliyan, Business Manager – Prosumer Flash and SSD Kingston EMEA. “We’re happy this 8TB addition to Kingston FURY Renegade G5 SSD can provide high-power users and hardware enthusiasts both.”

Kingston FURY Renegade G5 is available in full capacities² from 1024GB to 8192GB and is backed by a limited five-year warranty³, free technical support, and legendary Kingston reliability.