Are You Using Snowflake & Power BI? 3 Reasons Sigma Is So Much Better

While popular across businesses of all sizes, Snowflake and Power BI have been particularly embraced by large enterprises as key tools in their data & analytics (D&A) stacks. However, this combination is often more about necessity than efficiency. It's time to consider a better alternative: Sigma. In this blog, we'll show you how pairing Sigma with Snowflake can elevate your D&A infrastructure and free you from the constraints of legacy BI systems.

Data governance & Single Source of Truth (SSOT)

If you use Power BI, you may have noticed that it performs best in Import mode and often relies on it for optimal functionality. This means Power BI duplicates your data from your Cloud Data Warehouse (CDW) and stores it in Power BI Service. This method brings several issues to the table:

1. Data governance - Copying data from your CDW for reporting introduces unnecessary risks to your organization. The lack of comprehensive security and governance measures outside of IT departments can lead to the adoption of unapproved IT resources (shadow IT), increasing risks and complicating operations.
2. Single source of truth - Power BI’s Power Query provides strong data transformation features, but it often results in a scattered mix of data models trying to report on the same domain. The inconsistencies in reporting and analysis can be avoided by maintaining a Single Source of Truth (SSOT) in your CDW.
3. Paying twice - When you copy your data out of your CDW, you’re hit with double charges: consumption fees from your CDW and storage costs in Microsoft’s ecosystem. This payment model is complicated and costly. With the Sigma + Snowflake approach, all your data costs are straightforward and consolidated into your Snowflake bill.

Power BI’s Direct Query modeWhile Import mode is the preferred method for using Power BI, Direct Query mode is also available, but it comes with several significant drawbacks:

• Limited functionality: Direct Query mode in Power BI restricts developers from accessing the full suite of features available in Import mode. Power Query, Power BI’s ETL interface, is off-limits; more critically, many DAX features are unavailable. This limitation means that the level of analysis achievable in Direct Query mode falls short compared to Import mode.
• Query speed: Despite having a dedicated Snowflake connector, Power BI's Direct Query mode is notoriously slow and cumbersome. How it processes and sends queries to the CDW reflects an outdated approach built for a different generation of BI users and data workflows. In contrast, Sigma is purpose-built for CDWs, offering the fastest direct query times of any BI platform.
• Row limitation: Direct Query mode in Power BI limits query results to 1 million rows, a restriction that feels like a relic from Excel’s early days. Is this the kind of limitation you want in a modern analytics tool? Sigma offers a refreshing alternative, providing unlimited row results and allowing you to analyze data without artificial constraints.

Speed to insight & scalabilityWhile Microsoft markets Power BI as user-friendly for Excel users and everyday analysts, this is misleading. Power BI is a complex tool that takes years to master, hindering an organization’s ROI from its BI investments.

• Multiple languages - Power BI users need to learn two complex languages, M and DAX, which are challenging to pick up quickly. The complexity is such that third-party tools are often necessary to help users understand and manage the code. In contrast, Sigma’s syntax is easy to learn and apply. Most users get comfortable with Sigma’s calculations within a week or two.
• Administration & gateways - Power BI's complexity and non-cloud-native nature place a heavy administrative burden on platform teams. Administrators must manage access, maintenance, data refreshes, and data sets stored in Power BI Service. Sigma's cloud-native approach and direct querying of CDWs make it far less complex and burdensome to administer, freeing up your IT team for more strategic tasks.
• Unintuitive UI - Despite Microsoft’s efforts to improve Power BI’s user interface, it remains clunky and hard to navigate. Sigma’s intuitive and streamlined UI makes our tool far more accessible and user-friendly.

Additional thoughtsIf you're still on the fence about moving from Power BI to Sigma + Snowflake, let's dig into why this switch could be substantial for your organization.

• Hidden costs of Power BI - Microsoft's pricing for Power BI might seem attractive at first glance, but beware of the hidden costs lurking beneath.
  
  • Azure VMs and Gateway Software: Many Power BI users need Gateway software for on-premises to cloud connections or cloud security. While Gateways themselves aren't an extra cost, best practices dictate running them on Azure VMs. The data processed through these VMs adds to your expenses, sometimes inflating your total cost of ownership for Power BI by 33%.
  • Auto-scaling capacity: For those on Power BI Premium Capacity, Microsoft recommends the Auto-scaling feature to meet user demand. While it ensures performance, it can also lead to unexpected spikes in your monthly bill, especially given the high cost of top-tier P SKUs.
  • Training for new users: Training users in Power BI can be challenging, directly impacting your bottom line. The longer it takes to get users up to speed, the longer it takes to realize the value of your BI tool, costing your organization time and money.
• Maximizing ROI with Snowflake - Investing in Snowflake or other CDWs is significant. Leadership expects meaningful returns from these investments. If you're using your CDW merely as a data extraction point, you're missing out on all its benefits. Sigma leverages your CDW investment to its fullest, ensuring maximum return.
• Simplifying embedded use cases - As data sharing and embedding become industry standards, BI tools must keep pace. While Power BI offers embedding capabilities, it can involve complex configuration and coordination between Power BI and Azure admin portals. Sigma, being cloud-native, makes embedding data faster and easier, cutting down on administrative hassle and speeding up implementation.

Embrace the future of data analytics with SigmaPower BI is undeniably popular, and many organizations use it alongside Snowflake. However, this blog highlights why moving away from Power BI and legacy BI tools is pivotal for a cloud-first future. Sigma offers clear advantages: strategic alignment, rigorous governance, rapid insights, reduced administrative burden, and flexible pricing.Sigma + Snowflake can revolutionize your data and analytics capabilities. Contact us at sales@sigmacomputing.com to connect with an expert in Power BI and Sigma. We're here to answer your questions and help you transition seamlessly.