Why Omni over Power BI?
Give your team true self-service with faster workflows — all in a modern platform built for data teams.
Governed self-service for all: Confidently scale access across your internal and external users with consistent metric definitions, join paths, and AI context guiding everyone through their analyses — whether they prefer spreadsheets, a point & click UI, SQL, or AI.
AI you can trust: Build confidence with AI answers based on vetted business context and human-in-the-loop reviews.
One UI, any OS: Work, edit, and develop in one unified interface. No desktop app required.
Speed without the spend: Omni’s intelligent caching delivers faster insights — without inflating your compute bill.
First-class customer experience: Get white-glove support and a user-friendly UI built for modern data teams.
Omni’s AI answered like a consultant and provided recommendations that aligned with a proposal our team was already pursuing. It validated the AI’s capabilities and helped us build stakeholder confidence — giving our stakeholders confidence and strengthening alignment around SWBC’s AI vision.”- Austin Aranda, Director of Data Solutions
Consolidated use cases from multiple tools and launched Omni as a unified, AI-powered analytics platform in under six months
Read case studyHow Omni & Power BI compare
Omni offers your users self-service freedom backed by a flexible, built-in semantic layer — without a steep learning curve.
Power BI locks development to a desktop app, lacks a central semantic layer, and requires advanced users to learn a proprietary syntax. The result? Siloed metrics, frustrated teams, and no true self-serve.
Anyone can explore and visualize data, regardless of proficiency. Users can build analyses using AI, Excel formulas, SQL, or a point & click UI — all in the same interface.
The data team is a bottleneck. You need to learn the proprietary DAX language to be effective in Power BI.
Previously, the Revenue Operations team had to learn SQL or custom coding languages to create joins, but now they can do it through Omni's UI, and that has massively sped up their process. Omni has been transformative for them.
– Cody Pulliam, Senior Manager of Business Analytics, Aviatrix (read the case study)Data transformation is difficult as you need to learn M and DAX languages, which aren't intuitive and easy to learn.
– Power BI customerOmni's built-in shared semantic layer helps everyone use consistent metrics while doing ad-hoc analysis and running AI queries.
Power BI doesn’t have a truly central semantic layer, making it difficult to ensure consistent metrics and AI results across analyses.
Build your semantic layer as you go using Omni's “just-in-time” approach.
Exploration and data modeling are separate. Metrics cannot be promoted outside of individual reports, and any data modeling must be done before starting to analyze data in a workbook.
Omni gives you change management controls and a robust dbt integration — no more clunky legacy workflows.
Power BI still requires a Windows-only desktop app and offers limited support for version control and dbt. Omni is built from the ground up for modern data workflows.
Develop on any OS with Omni’s intuitive web-based application, a single place to run analyses, build dashboards, manage Omni’s semantic layer, author dbt changes, and more.
Power BI’s web version is limited. Core development tasks still require the desktop app, which only runs on Windows.
The disconnect between the desktop app and online is super frustrating. And it's not like you can just use one or the other—you have to use both, but remember where your latest edit is. Overall a terrible experience.
– Power BI customerUse Omni’s 2-way dbt integration to ingest metadata and push new metric definitions to dbt to make them universally accessible and optimize performance.
Power BI creates a data silo. Metrics developed in Power BI cannot easily be pushed to dbt, making them inaccessible for other use cases and tools.
Omni's dbt integration just worked. We set it up once, and it's been working seamlessly since.
– Jack Colsey, Analytics Manager at incident.io (read the case study)Test the impact of changes to underlying data sources via Omni’s dynamic schemas. Update your schema and references in bulk with a few clicks using Omni’s content validator.
Power BI has no easy way to safely test schema changes. Any changes to underlying data sources need to be manually reflected in every single query to prevent content from breaking.
One of Omni's best features is the ease of updating your schema whenever it changes. In other BI tools, this requires several steps in several places that are multiplied by the number of schema changes; with Omni you just click refresh.
– Omni customerSafely manage model changes and develop collaboratively through Omni’s git integration and intuitive version control interface.
Power BI’s rudimentary version control doesn’t enable robust development workflows without third-party tools.
If you like dbt, you'll love Omni's dbt integration
Omni's dbt integration is robust and supports real analyst workflows: switching between dev & prod schemas, creating dbt models from your BI layer, automatically using dbt metadata for AI, and more.
Power BI’s integration doesn’t go further than pulling in metrics and basic metadata from dbt.
See how changing a dbt model impacts content in Omni vs. Power BI
With Omni, you don't have to compromise on speed or data freshness.
Power BI makes you choose between imports (stale data) or DirectQuery (long load times). Omni’s intelligent cache ensures you’re getting fresh data without the wait.
Omni’s intelligent cache combines the speed of extracts and the data freshness of direct queries, without added costs.
Power BI’s simple caching means the database gets frequently queried directly, resulting in long load times.
It’s so nice that Omni’s caching doesn't have to execute a query every single time someone clicks something on a dashboard.
– Cody Pulliam, Senior Manager of Business Analytics at Aviatrix (read the case study)Power BI is not suited towards enterprise customers, as it's [sic] handling of large data volumes is particularly poor. The product lacks scalability in this regard, as it can take hours to load.
– Power BI customerOmni’s AI is grounded in business context from your semantic layer, providing trustworthy answers.
Power BI’s lack of a central data model makes it difficult to ensure accurate AI answers. Omni’s AI uses the same semantic layer you build and trust for your users — same metrics, same definitions, same context.
Omni’s AI is available to all users with sufficient permissions and reliably provides trustworthy answers thanks to vetted metric definitions and business context in the semantic layer.
Power BI’s Copilot is only available with Premium or Fabric capacity, not with standard Pro licenses — making AI querying an expensive add-on. And without a unified semantic layer, ensuring AI answers are accurate and consistent is difficult.
Omni’s AI answered like a consultant and provided recommendations that aligned with a proposal our team was already pursuing. It validated the AI’s capabilities and helped us build stakeholder confidence — giving our stakeholders confidence and strengthening alignment around SWBC’s AI vision.
– Austin Aranda, Director of Data Solutions, SWBC (read the case study)Omni’s MCP server allows users to ask data questions in natural language in their preferred AI chat interface, opening up access to governed insights beyond the BI layer.
Microsoft does not offer an official MCP server for Power BI. Conversational querying is delivered through Copilot in Fabric/Power BI, which is tightly integrated with Microsoft’s ecosystem (Fabric, OneLake, Power BI) and not designed for open, tool-agnostic access.
Unlock advanced use cases like forecasting and classification directly in Omni through integrations with Snowflake Cortex and Databricks Mosaic AI.
Access to advanced AI features directly in Power BI is limited (e.g. predictive analytics requires modeling in Microsoft Fabric or Azure ML).
While Power BI offers basic reporting capabilities, its [sic] may be less appealing for those seeking more advanced analytics features.
– Power BI customerOmni offers hands-on support in real-time — for free.
Omni’s team is here to support you at every step of the way, all included in your contract without any extra costs. With Power BI, you’ll be waiting hours for generic email responses.
Omni provides white-glove Slack support for every customer, helping you solve problems as they come up.
Support is severely limited unless you purchase a pricey premium plan from Microsoft.
Omni offers a truly incredible level of personal service where competitors seemingly offer little to none. Their team is constantly available in real time for anything from troubleshooting tricky issues to just helping you make your dashboards look better.
– Omni customer[...] Microsoft has opted not to provide premium support beyond the standard ticket-based system. This omission is a significant constraint, and it limits the ability of data teams to receive the necessary white-glove assistance.
– Power BI customerCustomer love
"Omni Analytics is a sweet spot between Looker and Mode. It's easy for your team to use, like Looker, but also lets tech-savvy folks dig into data with SQL queries. Plus, the Omni team is super quick to support and brainstorm on new ideas."
Read full review"I am not a BI tool user nor a data engineer but am able to model data and create dashboards much easier than other tools we tried. The tool is fast and responsive. The team is helpful and supportive and if you want get under the hood it's very easy to do so"
Read full reviewA super powerful BI tool. Omni addresses many of the struggles in legacy BI tools with novel approaches. The team has built with the analyst in mind so well. With Omni, data engineering can end a step or two earlier and rest of the magic is taken care of by the Omni UI. I also love how quickly Omni iterates and launches new features. Customer support of the finest levels too."
Read full reviewFAQs
Omni is a relatively new tool. Does it have the same features as Power BI?
Power BI has a wide range of features, but it requires users to learn proprietary DAX syntax to be effective. This creates a major hurdle for self-service adoption and makes the data team a bottleneck. At the same time, it lacks a true shared semantic model, making it difficult to ensure consistent metrics or AI results.
Omni has the same core features as Power BI, and it’s also built around a central semantic layer that ensures governance and metrics consistency, without slowing you down. It meets users where they are, letting them query with a point/click UI, Excel formulas, SQL, and AI, regardless of their technical proficiency.
In addition, Omni’s intelligent caching leads to faster queries and dashboards than in Power BI, and the bi-directional dbt integration seamlessly integrates with your existing data engineering workflows, helping your data team move faster as well.
Finally, Omni’s product team releases new features every week, and you can follow along with our engineering product development demos.
Why do I need a semantic layer in Omni if I’m using dbt? Business logic shouldn’t sit in the BI layer.
While in theory you could have all business logic confined to dbt, in practice this creates bottlenecks.
To keep up with the pace of business, users constantly need new measures or dimensions. With Omni, your teams are empowered to explore the data and get the answers they need. If any of these ad-hoc metrics should be used by the broader organization, you can push them to Omni's semantic layer or to dbt to close the loop.
Omni's semantic layer also creates a foundation for AI to deliver trustworthy responses. You can leverage descriptions, AI-specific context, and other metadata from your semantic layer to inform AI answers.
We want to enable self-serve analytics for our business users. Which tool should I choose?
Both Omni and Power BI are designed to provide self-serve access to data and enable quick insights.
However, in reality, Power BI’s lack of a central semantic model can easily lead to chaos due to inconsistent metric definitions across the company. In addition, business users will quickly feel limited in what they can do without deep knowledge of the proprietary DAX language.
Adding AI won’t automatically solve this problem. Without a central semantic model acting as a source of truth for definitions and context, it’s difficult to guarantee reliable and consistent answers from chatbots.
Omni, on the other hand, enables self-service by meeting every user where they are. You can use the point/click UI, Excel formulas, SQL, or AI. And with the shared semantic layer, users work off the same metrics foundation, but they’re free to explore data independently and contribute to the semantic model as they do analysis.
Many of our BI users don’t know how to write SQL. Which tool is a better fit for our situation?
Both Power BI and Omni let you explore data and create visualizations in a UI without using SQL.
However, in Power BI, you need to learn the proprietary DAX syntax if you want to create metrics that haven’t been pre-defined in the data model, severely restricting the ability of business users to analyze data and generate insights independently.
In Omni, using SQL or another coding language is not required — every user has the option to work in the way that they prefer. When exploring data, defining metrics or building dashboards, you can seamlessly switch between the point/click UI, Excel calculations, AI, and SQL. In the background, Omni is translating all queries into SQL, so you can always switch to SQL mode if you prefer.
We have a small data team with limited bandwidth. Which tool is a better fit for us?
Both Power BI and Omni allow for self-service data access for business users, which is great for busy data teams.
However, the lack of a central semantic model in Power BI means your data team has to field requests from business users who are confused by inconsistent metric definitions. In addition, business logic developed in Power BI cannot easily be pushed down to dbt or the data warehouse, making it inaccessible for other applications and creating duplicative work.
Change management in Power BI is also difficult, leading to more work for your data team. Rudimentary version control features make it difficult to stay on top of changes or develop collaboratively, and any change to the underlying data requires manual updates to every reference across queries to prevent dashboards from breaking.
Omni, in contrast, is built to free up bandwidth for your data team. The shared semantic layer helps ensure metrics consistency and governance, resulting in fewer questions about discrepancies from business users.
In addition, Omni’s architecture streamlines your everyday workflows. You can push metrics developed in Omni to dbt to make them universally accessible and improve performance, test changes before they land, and update your schema and references in bulk with Omni’s content validator.