Optimizing the performance of your Power BI dataset or Tabular model is crucial for achieving efficiency and delivering a seamless user experience. With DAX Optimizer, we aim to assist developers in enhancing their models by detecting bottlenecks, suggesting code improvements, and prioritizing them based on their impact on overall performance.

The value of performance optimization

Performance is a key factor for several reasons:

  1. Cost Efficiency: Poorly performing models consume more computing power, resulting in increased costs. By optimizing your models with DAX Optimizer, you can save valuable resources and allocate them more efficiently.
  2. User Experience: Consider a scenario where your model is used by 1,000 end-users. Even a small optimization, such as saving 4 seconds per report, can accumulate substantial time savings: by multiplying this by the number of users and working days in a year, you can see the significant impact on time savings. With DAX Optimizer, you can enhance the experience for your users, saving them time and improving productivity across the board.
  3. Ease of Collaboration: Clean and optimized DAX measures make it easier for colleagues and new team members to understand and work with your model. DAX Optimizer ensures your code follows best practices and standards, facilitating seamless collaboration among developers.

The cost-effective solution

Now, envision hiring a DAX expert to evaluate and optimize your model—a process that can be time-consuming and expensive. DAX Optimizer offers you similar value but at a fraction of the cost and in a faster timeframe. By utilizing DAX Optimizer, your entire team can benefit from optimized models, resulting in fewer errors and consistent practices.

Moreover, DAX Optimizer can also be employed to validate the work of external consultants, providing peace of mind for both parties. This win-win situation ensures the model adheres to best practices and is optimized with minimal errors.

Pricing options

When determining the pricing structure for DAX Optimizer, we carefully evaluated various approaches. Ultimately, we arrived at two compelling options tailored to meet your specific needs:

  1. Consumption Model: Under this model, you can purchase “per model evaluations,” known as “runs.” These runs can be bought individually or in bundles. Prices for the consumption model range from USD 45 to USD 24 per “run,” depending on the bundle size. This option suits users who prefer flexibility and wish to optimize models on demand.
  2. Subscription Model: With the subscription model, you can sign up for a monthly or yearly subscription that allows you to evaluate your model daily. Subscription prices range from USD 69 to USD 99 per month. If you need regular evaluations or want to demonstrate adherence to best practices to your customers, the subscription model is an excellent choice. Opting for a monthly subscription is convenient if you require more than two evaluations in a month, as you can perform multiple evaluations in a single day.

You can read more about the two options in the Comparing Plans and Licensing section of the DAX Optimizer documentation.

Options for large enterprises

In the future, we plan to introduce enterprise-level packages tailored for larger organizations. These packages will incorporate additional features in DAX Optimizer to enhance collaboration within large teams and meet advanced enterprise compliance requirements. If you cannot wait and wish to discuss an early adoption of DAX Optimizer at the enterprise level, please contact us directly.

Early adopter discount

To show our appreciation to early adopters who trust us right from the start, we offer a 30% discount on all packages and subscriptions until DAX Optimizer exits the beta phase. This discount is our way of rewarding our customers and acknowledging their support.

You are welcome!

We are excited about welcoming early adopters and are looking forward to receiving your feedback while you are optimizing your models. At the time of writing, access to the beta is still limited and requires an invitation: join the waitlist if you are interested. As soon as we increase capacity and confidence, we will remove the invitation requirement and open the beta to the public!