Why Omni over Sigma?
Use a spreadsheet interface with a shared data model, unlocking scalable self-service analytics with consistent metrics.
Metrics consistency: Leverage a shared data model to drive consistent metrics & joins while letting everyone freely explore data in workbooks
Bi-directional dbt integration: Push Omni metrics to dbt, test dbt model changes before you ship them, and more – helping you move faster with dbt than in Sigma
Flexibility: Seamlessly switch between a point/click UI, Excel calculations, AI, or SQL, all in the same query
Speed: Get answers fast while ensuring you have the freshest data with Omni’s intelligent caching
— Omni customer on G2[T]here have been very specific (and successful) analytics tools that cater to a governed model, iterative SQL analysis, or workbook BI.
Omni supports all of these workflows simultaneously, which unlocks all departments within an organization to be empowered as data analysts.
How Omni & Sigma compare
Omni adapts to how YOU work – not the other way around.
Sigma requires you to learn tool-specific syntax and choose between using the UI or SQL. Omni meets users where they are — whether that’s in the point/click UI, Excel formulas, SQL, or AI.
Seamlessly switch between your preferred methods: point/click UI, Excel calculations, SQL, or AI.
Spreadsheet interface and SQL are separate experiences. Switching between them means starting over.
Omni’s Excel calculations match Excel syntax exactly. Using Omni is instantly familiar – no need to learn another language.
Calculations in Sigma differ from Excel syntax. This creates confusion and requires analysts to learn another tool-specific language.
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.
- Anya Osen Barnett, Senior Analytics Engineer at TrintIn my opinion, [Sigma] is a poor tool for those that actually want to see the source code behind visualizations.
- Sigma customerOmni eliminates metrics chaos without slowing you down.
Governed self-service is core to Omni, leading to consistent metrics and joins across the organization. Sigma makes it hard to ensure consistency and creates data silos instead.
Omni’s built-in semantic layer ensures that everyone uses consistent metrics while also being able to explore data and do ad-hoc analysis.
Sigma’s data model is optional, which makes it difficult to ensure consistency as your organization scales.
Contribute to the shared model as you do analysis through Omni’s just-in-time data modeling approach.
Exploration and data modeling are separate. Metrics developed in Sigma workbooks can’t be shared easily with the organization.
Push new metric definitions to dbt via a bi-directional integration to make them universally accessible and optimize performance.
Sigma creates a data silo. Metrics developed in Sigma can’t 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.iodbt integration is almost non-existent, outside of surfacing column descriptions in a few select areas of the UI. These columns [sic] descriptions will not persist, however, if you use Sigma's dataset or data model functionality.
- Sigma customerSafely test the impact of changes to underlying data sources. Use Omni’s dynamic schemas to switch between dev & prod environments and update your content in bulk with the content validator.
There’s no easy way to safely test schema changes. Any changes to underlying data sources need to be manually reflected in every single workbook in Sigma.
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 customer[T]here is no unified view to surface errors in Workbooks – you have to search through every single workbook page and look for red X's on each table/chart to identify what's wrong. Instead of being able to proactively resolve errors, you'll constantly have business stakeholders raising these issues since the tool doesn't surface these to your data team members in any meaningful way.
- Sigma customerWith Omni, you don’t have to compromise on speed or data freshness.
Sigma has limited caching, which means data is usually pulled directly from your database, resulting in long dashboard load times. Omni’s intelligent cache ensures you’re querying fresh data without the long wait.
Omni’s intelligent caching combines the speed of extracts and the data freshness of direct queries without added costs.
Sigma often queries the database directly when users interact with a dashboard, even when the necessary data is already present.
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, AviatrixBecause Sigma has to re-pull data every time you open a sheet, it is incredibly slow. Certain reports can take multiple minutes to load, and once any filters are applies [sic], it has to re-pull the report, causing those minutes to be lost again. Because of this, it's often easier to just download all the data and then do the filtering/etc in excel/google sheets.
- Sigma customerIf 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 logic in your BI platform, and more.
Sigma’s integration only lets you pull in metrics and basic metadata from dbt.
See how Omni’s dbt integration compares to Sigma's
The implementation was incredibly straightforward and very fast. We were able to build a dashboard on the very first day.
— Martin Zerbib, Head of Product at Sifflet
Customer 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 Sigma?
At first glance, Sigma has a lot of features you’d want in a self-serve BI tool: a spreadsheet interface, drill-down functionality, etc.
Omni has those same core features, too, and it’s also built around a central data model that ensures governance and metrics consistency, without slowing you down. Sigma lacks a true central data model; users can define metrics and join in many individual models, which makes it hard to ensure a consistent source of truth as your organization scales.
In addition, Omni offers a bi-directional dbt integration that seamlessly integrates with your existing data engineering workflows. Omni’s intelligent caching also leads to faster queries and lower costs than in Sigma.
Maintaining a shared data model sounds like a lot of work. In Sigma, I can just start to explore data.
You don’t have to maintain a semantic layer in Omni; you can query straight from raw tables or dbt models.
But self-serve analytics without governance can quickly lead to chaos. With Omni’s shared data model, you can ensure that key metrics are consistent across the entire company. Sigma’s lack of a true centralized shared model means that dashboards are based on a variety of data sources that don’t necessarily share the same metrics, leading to inconsistencies and confusion.
Setting up your data model in Omni doesn’t take a lot of time. One Omni customer, for example, was able to configure the data model and create their first dashboards in less than a week. Plus, you can lean on our support team for help as you set up your model.
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 can have all business logic confined to the dbt semantic layer, 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; and if any of these ad-hoc metrics should be part of the shared data model and used by the broader organization, you can push them to Omni’s shared model or dbt to close the loop.
We want to enable self-serve analytics for our business users. Which tool should I choose?
Sigma makes it easy to get started and explore data. However, this can quickly lead to chaos: Sigma doesn’t have a shared data model that ensures metrics consistency, so you’ll find yourself trying to reconcile numbers between dashboards built on different data sources.
While governance & consistency in Sigma is an afterthought, Omni is built from the ground up to provide governed, self-serve analytics. Users can freely explore data in a way that works best for them (point/click UI, Excel calculations, SQL, or AI), and any metrics they develop can be promoted to the shared data model to be centralized and reused across the company. You can even push the new metrics down to dbt to make them accessible by other tools and improve performance.
Many of our BI users don’t know how to write SQL. Which tool is a better fit for our situation?
Both Sigma and Omni allow you to explore data and create visualizations without using SQL.
The key difference is that in Sigma you have to choose upfront; if you start building in the UI and want to see the underlying SQL (and tweak the query from there), you have to start over.
Omni doesn’t have these barriers. At any point, you can seamlessly switch between the point/click UI, Excel calculations, SQL, or AI. Omni adjusts to how you work – not the other way around.
We have a small data team with limited bandwidth. Which tool is a better fit for us?
Both Sigma and Omni allow for self-service data exploration, which massively reduces the reliance on the data team.
However, Sigma’s architecture and workflows will become more of a burden on your data team over time as your company scales. For example, any changes to underlying data sources need to be manually reflected in every single workbook to prevent them from breaking, while in Omni you can refresh your data model and analyses with a single click.
In addition, Omni seamlessly integrates with dbt, letting you push metrics from Omni directly to dbt models, making them universally accessible and saving your team time.