Why Sigma?

One of our jobs at Maverick Data is to stay informed about the latest and greatest technologies available to our clients. One BI platform that has really caught our eye is Sigma Computing.  Based out of San Francisco, Sigma Computing is taking on the challenge that all other BI platforms have failed at – recreating Excel in the Cloud. In this blog we will break down why we like Sigma Computing, where we see it going, and some of its limitations that we want our clients to understand. 

Why We Like Sigma

There are many reasons why Maverick Data would suggest a tool like Sigma to our clients, but there are three main reasons:

1. Alignment with Modern Data Strategy
2. Simplicity
3. Innovation

Next we’ll dive into why these three topics are important for our client’s and their success. 

Alignment with Modern Data Strategy – the data industry is always evolving and changing to meet modern data consumer’s needs. Today’s data consumers are consuming data faster and more frequently than every before making the demand on timely data higher than ever. Sigma only live queries data (no caches/extracts) – so you know the data you are consuming is the most up to date data.

Additionally, not extracting data from the CDW means that there is consistency across reporting that could not be guaranteed when using a cache/extracts for reporting. Sigma is able to do this because of the extremely powerful query engine and cloud-native technology allowing it to integrate seamlessly with the modern data platforms such as Snowflake and Databricks.

Lastly – organizations spend millions of dollars and have entire teams of highly trained data engineering creating and maintaining CDWs. Creating extracts of these data models takes the control, governance, and security out of these team’s hands and gives it to line of business analysts. While some would argue that this gives the business more flexibility and autonomy – the self-service wave showed that often the technical skills of this LOB persona actually created more of a net cost to companies than benefits. Keeping the data modeling and data processes within the IT team helps maximize the investment made in the CDW. Sigma more than other tools allows for this model to flourish.

Simplicity – at Maverick Data we service clients with all different BI platforms, so we’ve been exposed to almost all of the market leaders. Sigma by far is easiest of them to skill up in. In addition to the actual development being straight forward, Sigma’s pricing and governance models are extremely simple compared to competing technologies. 

While Sigma cannot produce some of the crazy cool visualizations that a tool like Tableau can – that’s not its goal. The simplicity of the tool keeps the main thing the main thing – getting data to users in a consumable manner in a timely and efficient manner.

Because Sigma is simple to license and install, it does not require the massive amounts of people to govern and maintain like other tools like Power BI. This decreases additional costs  associated with the Total Cost of Ownership that often come with other BI platforms.

Innovation – when Maverick Data evaluates BI platforms, we are not just assessing the tool as is – we also want to assess where tools are going so that we can make the best long term recommendations to our clients. Sigma is still in rapid growth mode. Their product releases are frequent and include meaningful feature adds that immediately add value to existing clients. 

In order to compete with the other major player in the BI platform market – Microsoft’s Power Platform – Sigma must continue to build on the idea that they are a data platform – not just a data tool. Features such as native write-back functionality signal that they have this goal in mind and are moving in that direction.  

Sigma’s Shortcomings

While there are a lot of great things going on at Sigma Computing, it is our job at Maverick Data to inform our clients about the shortcomings of tools as well. Overall, Sigma is a great tool – but it is still limited compared to other tools.

One of Sigma’s pros is that it’s so simple – but that’s also one of its drawbacks. The development UI is still a work in progress and can be unintuitive at times. Additionally, data modeling within the tool leaves a lot to be desired especially when compared to a tool like Power BI.

The visualization capability of Sigma has come a long way since its initial release, but it still leaves a lot to be desired when compared to a tool like Tableau. Additionally – Sigma currently only connects to a handful of cloud data sources. Given, they are some of the biggest cloud platforms available – Snowflake, Databricks, Google BigQuery – but that means if your organization is not entirely in the cloud, or if you are using a CDW that they cannot connect to yet, Sigma would not be a viable option.

As mentioned earlier, Sigma is in high growth mode, so while some of these issues that we have with Sigma might be true now, we do believe that Sigma will continue to drive forward on these issues moving forward.

Conclusion

At Maverick Data we are bullish on Sigma Computing. Their easy to use product will allow quick adoption and ROI on the platform. Their cloud-native infrastructure and alignment with modern data strategies are also huge pluses. Some of their limitations around visualization and connection capabilities give us pause, but we believe that their technical teams will continue to build Sigma into a world class data platform. 

If you would like to talk to someone at Maverick Data about Sigma Computing, please email us at spencer@maverickdata.io.