Best Semantic Layer Tools for Microsoft Excel
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Compare the Top Semantic Layer Tools that integrate with Microsoft Excel as of July 2026
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This a list of Semantic Layer tools that integrate with Microsoft Excel. Use the filters on the left to add additional filters for products that have integrations with Microsoft Excel. View the products that work with Microsoft Excel in the table below.
What are Semantic Layer Tools for Microsoft Excel?
Semantic layer tools provide a unified, business-friendly view of data across multiple sources, translating complex data models into easily understandable concepts and metrics. They allow business users to query, explore, and analyze data using consistent definitions without needing deep technical knowledge of databases or query languages. These tools sit between data storage and analytics platforms, ensuring alignment and accuracy in reporting. By standardizing key metrics like revenue, customer churn, or retention, they eliminate inconsistencies across dashboards and reports. Semantic layers empower organizations to democratize data access while maintaining governance, transparency, and trust. Compare and read user reviews of the best Semantic Layer tools for Microsoft Excel currently available using the table below. This list is updated regularly.
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1
Kyvos Semantic Layer
Kyvos Insights
Kyvos is a semantic layer for AI and BI. By standardizing how data is defined and understood, Kyvos gives organizations a single, consistent, business-friendly view of their entire data estate. The result: AI agents reason with governed context, BI tools report consistent metrics, and the business gets answers it can trust. Built for enterprise scale, Kyvos provides the speed, scale, and trust that production-grade AI and enterprise BI demand. It also maximizes analytics investments by reducing token consumption and cloud compute costs. -
2
Microsoft Fabric
Microsoft
Reshape how everyone accesses, manages, and acts on data and insights by connecting every data source and analytics service together—on a single, AI-powered platform. All your data. All your teams. All in one place. Establish an open and lake-centric hub that helps data engineers connect and curate data from different sources—eliminating sprawl and creating custom views for everyone. Accelerate analysis by developing AI models on a single foundation without data movement—reducing the time data scientists need to deliver value. Innovate faster by helping every person in your organization act on insights from within Microsoft 365 apps, such as Microsoft Excel and Microsoft Teams. Responsibly connect people and data using an open and scalable solution that gives data stewards additional control with built-in security, governance, and compliance.Starting Price: $156.334/month/2CU -
3
Boost.space
Boost.space
Boost.space is a no-code agentic database designed to give AI agents and automations the structured business context they need to operate effectively. It centralizes scattered data from CRM, ecommerce, billing, and support systems into a unified Single Source of Truth. The platform enables continuous two-way synchronization across tools, ensuring that information remains accurate and up to date. With built-in AI enrichment, users can classify records, normalize attributes, and generate structured metadata at scale. Boost.space also supports workflow automation through integrations with platforms like Make, Zapier, and n8n. Through its Model Context Protocol (MCP), AI agents can query live data and execute actions across connected systems without relying on static exports. Trusted by thousands of teams globally, Boost.space transforms fragmented datasets into actionable AI-ready infrastructure.Starting Price: $15/month -
4
Timbr.ai
Timbr.ai
Timbr is the ontology-based semantic layer used by leading enterprises to make faster, better decisions with ontologies that transform structured data into AI-ready knowledge. By unifying enterprise data into a SQL-queryable knowledge graph, Timbr makes relationships, metrics, and context explicit, enabling both humans and AI to reason over data with accuracy and speed. Its open, modular architecture connects directly to existing data sources, virtualizing and governing them without replication. The result is a dynamic, easily accessible model that powers analytics, automation, and LLMs through SQL, APIs, SDKs, and natural language. Timbr lets organizations operationalize AI on their data - securely, transparently, and without dependence on proprietary stacks - maximizing data ROI and enabling teams to focus on solving problems instead of managing complexity.Starting Price: $599/month -
5
Brewit
Brewit
Make data-driven decisions 10x faster with self-service analytics. Integrate with your databases and data warehouses all-in-one place (Postgres, MySQL, Snowflake, BigQuery, and more). Brewit can write SQL queries and create recommended charts based on your data questions. It also helps you drill down on the analysis. Chat with your database, visualize insights, & perform analysis. Ensure answer accuracy and consistency with a built-in data catalog. An automated semantic layer that ensures Brewit answers with correct business logic. Easily manage your data catalog & data dictionary. Building a beautiful report is as easy as writing a doc. Data without a story is useless. Our Notion-style notebook editor allows you to create reports & dashboards easily, turning raw data into actionable insights. All organized data products are usable by anyone who has a data question, regardless of their technical skills. -
6
CData Connect AI
CData
CData’s AI offering is centered on Connect AI and associated AI-driven connectivity capabilities, which provide live, governed access to enterprise data without moving it off source systems. Connect AI is built as a managed Model Context Protocol (MCP) platform that lets AI assistants, agents, copilots, and embedded AI applications directly query over 300 data sources, such as CRM, ERP, databases, APIs, with a full understanding of data semantics and relationships. It enforces source system authentication, respects existing role-based permissions, and ensures that AI actions (reads and writes) follow governance and audit rules. The system supports query pushdown, parallel paging, bulk read/write operations, streaming mode for large datasets, and cross-source reasoning via a unified semantic layer. In addition, CData’s “Talk to your Data” engine integrates with its Virtuality product to allow conversational access to BI insights and reports. -
7
SSAS
Microsoft
Installed as an on-premises server instance, SQL Server Analysis Services supports tabular models at all compatibility levels (depending on version), multidimensional models, data mining, and Power Pivot for SharePoint. A typical implementation workflow includes installing a SQL Server Analysis Services instance, creating a tabular or multidimensional data model, deploying the model as a database to a server instance, processing the database to load it with data, and then assigning permissions to allow data access. When ready to go, the data model can be accessed by any client application supporting Analysis Services as a data source. Models are populated with data from external data systems, usually data warehouses hosted on a SQL Server or Oracle relational database engine (Tabular models support additional data source types). -
8
Strategy Mosaic
Strategy Software
Strategy Mosaic is an AI-powered universal semantic data layer and analytics foundation that sits on top of an organization’s existing data systems to unify, govern, and accelerate access to business data for analytics, AI, and reporting without costly restructuring. It creates a single source of truth with consistent business definitions, metrics, and security policies across tools and sources, harmonizing data from hundreds of systems so insights are reliable and comparable everywhere. Built with AI-assisted data modeling (Mosaic Studio), Mosaic automates data preparation, cleansing, enrichment, and modeling, reducing the time and effort needed to build robust data products and semantic models. Its universal connectors let users access governed data via SQL, REST, Python, or through popular BI and productivity tools like Power BI, Tableau, Excel, and Google Sheets, while an in-memory acceleration engine delivers fast query performance across diverse sources.
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