SSAS Description
When deployed as an on-premises server, SQL Server Analysis Services provides comprehensive support for various model types, including tabular models at all compatibility levels based on the version, multidimensional models, data mining capabilities, and Power Pivot features for SharePoint. The standard process for implementation involves setting up a SQL Server Analysis Services instance, designing either a tabular or multidimensional data model, deploying this model as a database to the server instance, processing it to populate with data, and configuring user permissions to facilitate data access. Once the setup is complete, client applications that are compatible with Analysis Services can easily utilize the data model as a source. These models typically gather data from external systems, primarily from data warehouses utilizing either SQL Server or Oracle relational database engines, though tabular models can connect to a variety of additional data sources. This versatility makes SQL Server Analysis Services a powerful tool for analytics and business intelligence.
SSAS Alternatives
AnalyticsCreator is a metadata-driven design application for data warehouse automation and data product engineering across the Microsoft data stack.
Its Governed Control Model connects business meaning, data structures, transformation rules, dependencies, lineage and technical implementation in one controlled project model. Data teams design the required architecture in AnalyticsCreator, then generate native Microsoft assets from that design.
Generated outputs can include SQL Server objects, SSIS packages, Azure Data Factory pipelines, supported Microsoft Fabric components, deployment artefacts and Power BI semantic models. AnalyticsCreator supports dimensional, 3NF and hybrid modelling approaches together with ingestion, transformations, delta loading, historisation, Slowly Changing Dimensions, snapshots and repeatable data-processing patterns.
Because generated outputs are native Microsoft technology, no AnalyticsCreator runtime is required in production. Organisations retain ownership of the resulting implementation and can integrate generated assets into Git, Azure DevOps and CI/CD workflows.
Lineage, documentation and dependency information remain connected to the design, helping teams understand change impact before regenerating affected assets.
Design Intelligence extends this governed project context into AI-assisted data engineering by providing authorised AI tools and agents with structured access to metadata, lineage, dependencies and design rules.
Typical use cases include enterprise data warehouse development, Microsoft Fabric adoption, SQL Server and SSIS modernisation, governed Power BI delivery and repeatable data product engineering.
Learn more about AnalyticsCreator
Denodo is a logical data management platform built to help enterprises unify, govern, and deliver trusted data across complex technology environments. It connects data from cloud, on-premises, SaaS, third-party, and multi-cloud systems without copying or duplicating the information. The platform gives organizations a single trusted view of distributed data, helping analytics teams, business users, and AI agents access current information more efficiently. Denodo supports trustworthy agentic AI by combining live data access with business semantics, centralized governance, compliance controls, and lineage. Its self-service data marketplace allows users to find, prepare, and use governed data while reducing dependence on IT teams. The platform also supports natural language search, personalized data delivery, and role-specific views so users can get data with the right business meaning. Denodo helps organizations improve data lakehouse investments by giving teams optimized access to data beyond a single repository. Its real-time delivery capabilities help operations, analytics, and AI systems make decisions based on current information instead of stale copies. By reducing integration time and improving time-to-insight, Denodo gives enterprises a trusted data foundation for AI, analytics, and digital transformation.
Learn more about Denodo
dbt
dbt Labs is redefining how data teams work with SQL. Instead of waiting on complex ETL processes, dbt lets data analysts and data engineers build production-ready transformations directly in the warehouse, using code, version control, and CI/CD. This community-driven approach puts power back in the hands of practitioners while maintaining governance and scalability for enterprise use.
With a rapidly growing open-source community and an enterprise-grade cloud platform, dbt is at the heart of the modern data stack. It’s the go-to solution for teams who want faster analytics, higher quality data, and the confidence that comes from transparent, testable transformations.
Learn more about dbt
Kyvos Semantic Layer
Kyvos is a semantic layer for AI and BI. It gives organizations a single, consistent, business-friendly view of their entire data estate.
By standardizing how data is defined and understood, Kyvos eliminates metric drift across BI tools and ensures that LLMs and AI agents work with governed business semantics rather than raw tables.
Kyvos also delivers lightning-fast analytics at massive scale and high concurrency — including granular multidimensional analysis on the cloud — without the sluggish query times and escalating cloud costs that typically come with it.
What Kyvos Solves?
Organizations today operate across multiple data platforms, analytics tools, and AI interfaces. Without a unified semantic foundation, the same business question can return different answers depending on the tool, query logic, or dataset used.
And as data volumes grow into billions of rows, querying the full breadth and depth of an organization's data becomes slow and expensive — forcing teams to work with limited slices rather than the complete picture.
Kyvos addresses both by creating a universal semantic layer across the data estate — standardizing how business data is defined and understood — while delivering high-performance analytics that remain fast and cost-efficient regardless of data scale and user concurrency.
The result is “one view, one meaning, one truth” of enterprise data, while delivering fast, scalable analytics across LLMs, AI agents and BI tools.
Learn more about Kyvos Semantic Layer
Integrations
Company Details
Company:
Microsoft
Year Founded:
1975
Headquarters:
United States
Website:
docs.microsoft.com/en-us/analysis-services/ssas-overview
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