SIGMA

My main use case for Sigma  is for enterprise dashboards, which is originally why I brought it in, and self-service analytics.

A quick and specific example of how I used Sigma  for enterprise dashboards is that I built a centralized reporting dashboard for our marketing team.

My main use case for Sigma supports the entire organization, and one of the big reasons that I initially brought it in was I was able to connect it to our Snowflake  environment and let one of our SVPs know that it was connected. Before I got a chance to really train her, she had set up her own dashboard. It was a comprehensive dashboard that had at least five tabs on it, and it was actually really good. I could not believe that she set it up by herself with no training.

The best features Sigma offers include the self-service functionality, which was a really big deal, as well as their very good data apps and integration with Snowflake . Sigma is also moving into the AI space, as a lot of companies are, and they are doing a really great job at it.

The data apps feature stands out for me because it was just more focused data that is easier to get to, not having to do just the regular dashboards.

Sigma has positively impacted my organization because we were able to retire an old enterprise reporting tool that was homegrown, which involved a lot of canned SQL and parameterized SQL, making it a lot easier for us.

After switching from our homegrown reporting tool to Sigma, we noticed that a set of employees were able to create their own dashboards, allowing other organizations within the company to really take off and not depend on BI after that. So that was one of the big things.

I think Sigma can be improved by continuing to do what they are doing in leaning into AI and leaning into the Snowflake integration with AI. All of the conversational features that they have recently rolled out are really great, and I think that is mainly it. It is about being able to hold people within the tight context of the data in the dashboard and being able to interact with it conversationally.

I cannot think of any needed improvements right now, even something minor.

I have been using Sigma for three years.

Sigma's scalability as our data or user base grows is very easy, especially with the organizations.

Sigma's customer support is excellent, and that is actually one of the other reasons why we ended up going with Sigma, as we are able to hit the question mark and ask for support and get real live people that are very knowledgeable. Their support I really think is a 10 out of 10.

Positive

For actual users, I find it very easy to get into and adopt Sigma.

Sigma's performance when handling large data sets or complex queries is wholly dependent on the Snowflake warehouse, so if we do not want to burn too many Snowflake credits, we keep it on a smaller warehouse. Usually, it is okay, which is mainly because what we are trying to do is also be careful with our Snowflake budget.

I think Sigma handles data security and compliance requirements for my organization really strongly since they integrate with Snowflake security as well.

I do not know that we really had any big integrations, but we did have a couple API integrations with some homegrown tools, and that went pretty smoothly. They have been getting much better at that.

I think the level of customization Sigma allows for dashboards and reports is very good and getting better, but the other big thing is really what they are heading towards with more of the data apps.

My advice for others looking into using Sigma is to make sure your data foundation is set. I just do not think it is a smart idea for any tool to go after your transactional data; you should at least have some sort of data model so that way you are not querying 10 years of data when you only need last month or last year.

I think Sigma is a very strong company, and I consider them one of the top vendors in the space. The only question that I would have is that I have not had a chance to look at some of the newer agentic, AI-only tools. I would rate this review as a 9 out of 10 overall.

The project I worked on with Sigma  involved creating a migration assessment tracker. We fetch all the data from the Tableau server and the cloud through the metadata API or the REST API. Then our data engineering team puts that particular data through the Alteryx  workflow, refines all the components, and pushes the data into Snowflake . We then connect Snowflake  with Sigma . With that report, you can compute how much time it will take to migrate a particular site, how many workbooks exist, how many tabs are in Tableau, the duration required, and the complexity of the workbook based on the calculations.

The report also shows if any workbook is associated with upstream workflows or how many published data sources exist. We brought this information onto Sigma and created our report accordingly to estimate the migration time.

It serves the marketing team by ensuring that when receiving a project involving migration from Tableau to Sigma, they can estimate the time required. It estimates all efforts based on these complexities, the size of the Tableau server, and the number of users involved.

Compared to other BI tools, each tool has its own capabilities. Sigma has excellent features, such as lookup tables where you can easily bring data that are not interrelated or at different granularity. Because in Tableau, you can see various LODs. To create those same functionalities in Sigma, we generally use lookup tables and replicate that functionality there. It has multiple good controls such as segmented controls. It also provides tab options with the inbuilt feature in the interface itself. If you need to create a similar thing in Tableau, you need to create separate sheets or buttons. Sigma provides several cool features. You can create multiple visuals, and the maps functionality is very good in Sigma. We explored all the charts that Sigma has provided in its interface. Although Sigma is introducing some AI capabilities, that has yet to be explored from our side. We have explored the interface part, creating dashboards, and managing data sources with joins and relationships.

As we are exploring multiple features in Sigma, I think Sigma can add more functionality. As Power BI gives multiple modeling options in its interface with the query editor, those features can be added in Sigma for intuitiveness or for making the data very clean. From the dashboarding perspective, it performs well. However, from the modeling perspective, it requires more capabilities that can be added in Sigma.

The main improvement needed is in data modeling capabilities. If they add those features in the near future, it would be very helpful for us to implement the same or do the data cleansing part in the Sigma tool itself.

I have almost eight years of experience working with Tableau and Power BI. For Sigma, I have been working for the past two years.

I am not sure if my company purchased Sigma through the AWS Marketplace .

We did not face typical errors during our project with Sigma. In the near future, if we receive support from Sigma, that would be more helpful. There are multiple teams in my organization working on Sigma projects. We have not connected with Sigma support yet. In the future, I can provide more detailed reviews.

If data is substantial, in Sigma's case, the data is always live. It is not a kind of extract, whereas Tableau provides both live and extract functionality.

On the scale of 1 to 10, I rate Sigma an 8.5 because there are multiple tools whose setup needs to be done, and the servers are also on physical machines such as Tableau server for maintaining all those components. As Sigma is a cloud platform, you do not need to do all that maintenance work. Regarding visualization and data modeling, as mentioned earlier, they can improve on those aspects. The functionality and interface have improved significantly with their latest versions. Previously, all options were on the left-hand side, and now there are floating themes at the bottom where you can easily select all options and create a good dashboard.

Positive

In Tableau, you have filter actions where you can select any particular sheet, click on that particular button, and the data is filtered accordingly. You can do a similar thing with the help of actions in Sigma. You can even change the dynamic axis. If you want to change the X-axis and Y-axis, you can do it with the help of controls, the segmented controls, and with the help of actions.

Setting up Sigma is not complex. If you know all the components through their documentation, you can easily implement it as the documentation they created is comprehensive and contains all the necessary information.

As we are a hybrid team, operating from India as well as the US side, we do the development part and our US team connects with the clients and deploys all components in the environment. We are primarily developers, but we can also manage the publishing and other tasks.

Regarding the differences between Sigma and Tableau, for visualization, Tableau is the best tool I have worked with because you can change the visualization accordingly by creating different calculated fields. Sigma could add more visualizations. In Tableau, you can do forecasting with the help of the analytics tab. If Sigma also adds these features, it would be beneficial. In Tableau, there is a smoothing model you can select to do forecasting, create good trend lines, and add effective reference lines while creating trends.

I prefer to remain anonymous. Based on my experience with Sigma, I would rate it 8.5 out of 10.