Power BI and Azure Analysis Services are dynamic visualization and modeling tools that can help you generate key insights for your business. But are they the best systems for the job? In this guide, we’ll discuss the pros and cons of using these two systems in tandem, and offer essential tips on choosing the best data analysis tools for your business.

Power BI and Azure Analysis Services

What is Azure Analysis Services? 

Azure Analysis Services is a platform as a service (PaaS) offered by Microsoft. You can use it to generate and manage data models in the cloud. At its core, the service provides a semantic layer for your organization: It takes complex sets of data from a server or other storage source and breaks it down into models that are easy for a layperson to understand.

The service works by connecting to a data source, usually the SQL Server, a Microsoft-operated data management system. From here, it creates custom models based on what you would like to test or predict. Microsoft offers three different tiers of Azure Analysis Services that each connect with a different SQL Server and have a different uses for your business:

  • Developer tier: This connects with the SQL Server Developer edition. You can use it to develop basic test models. However, you’re limited by low processing power and reduced Query Processing Units (QPUs)—a metric for measuring current compute load capacity. You’re also only alloted three gigabytes of memory.
  • Basic tier: This connects with the SQL Server Standard edition. Use it to create robust tabular models, ideal for production-focused data analysis. Within this tier, you can choose between a B1 or B2 service. The first offers 10 Gb of memory and the second offers 20 Gb of memory. Besides the memory limits, it also doesn’t support multiple partitions or perspectives.
  • Standard tier: This is used for advanced data modeling, and connects with the SQL Server Enterprise edition. It can handle flexible data models, real time updates, and multiple users. This tier includes six subtiers that vary in cost and complexity. The higher the sub-tier is, the faster the processing power and larger the memory limit. The highest sub-tier, S9, supports 400 Gb of memory.

All of these tiers can also connect with Microsoft’s Power BI, a powerful data visualization tool. To generate the most detailed and user-friendly reports, you should use Power BI and Azure Analysis Services together.

Connecting Power BI to Azure Analysis Services 

When you connect Power BI with Azure Analysis Services, you’ll generate engaging visuals from Azure’s complex data models. There are four basic steps to this process:

  1. Create a new model in the Azure Analysis Services platform;
  2. Sign into your Power BI desktop account;
  3. Add the name of your Azure server in the Power BI desktop settings; and
  4. Start generating new visuals based on the connected Azure Analysis Services model directly from the Power BI desktop app.

The combined services let you generate powerful visuals and share them with others quickly, without showing them the internal structure of the original data model.

Data models generated from Azure Analysis Services are both detailed and easy to understand. However, they’re not as visually-appealing or elegant as Power BI’s custom visuals. Your IT team or managers can use Azure Analysis Services to organize the data and generate accurate models. When you’re ready to share your results with your team or support important business decisions in a meeting with shareholders, you’ll use Power BI to break the model down into visual pieces that are even easier to digest.

Although Power BI and Azure Analysis Services help you find out precisely what your data means, the systems also have a few limitations.

The Cost of Power BI and Azure Analysis Services  

The main problem with using both Power BI and Azure Analysis Services is cost. While Power BI can be free, the Pro and Premium versions cost an additional $9.99 per user per month and $4,995 per resource per month, respectively.

As for Azure Analysis Services, pricing is assessed by the hour. Generally, you’ll pay an estimated: 

  • $96 per month for the Developer tier;
  • Between $313 and $627 per month for the Basic tier; and
  • Between $591 to $5,920 per month for the Standard tier.

Your precise costs depend on which sub-tier you purchase, how often you use the system, and where you are located. 

If you also sign up for a SQL Server license, your monthly costs may increase even more. Developer and Express SQL Servers are both free. However, you can only use them for testing and development. If you want full data intelligence capabilities, including data governance and greater cloud storage security, then you have to buy an Enterprise or Standard SQL Server license. 

To do so, you must license the server and buy a separate Client Access License (CAL) for every individual user. The Standard server license costs $931 and each CAL costs $209. Or, you can license processor cores, with a minimum of four cores per server. Just one Enterprise processor core costs $7,128. One Standard core costs $1,859. 

It all adds up quickly, particularly if you’re planning on buying Power BI Pro or Premium along with Standard Azure Analysis Services and an Enterprise SQL Server license. While this would give you full control over your data and let you generate powerful insights, it’s not the most cost-effective choice for many businesses.

Should You Use Power BI and Azure Analysis Services?

Using Power BI and Azure Analysis Services is the right choice for businesses that can afford the upper-tier licenses or only need to use the low-cost versions of each tool (e.g. the Developer tier of Azure Analysis Services or Power BI Pro) for just a handful of users. It may be out of the price range for smaller businesses or those that require advanced data analysis and increased data security. 

You can get all of the same advanced data analytics by hiring a third-party data analysis provider instead. These data analytics firms provide:

  • Data modeling, including support for tabular models and real time updates;
  • Detailed and beautiful visualizations that connect to these data models; 
  • A user-friendly portal from which you can generate models, visuals, and reports; 
  • Cloud storage and computing from an off-premise server; and
  • Reliable data security, including encryption and user authorizations.

All of this comes at a comparably lower cost, depending on the vendor you choose and your organization’s specific needs. You also won’t have to buy core processors or manage any servers yourself.

Another benefit of hiring a third-party firm is that the process is less complicated and time-consuming compared with using Power BI and Azure Analysis Services in tandem. A third-party firm saves you from having to find the right system for your needs. Sifting through the various versions and tiers of Power BI, Azure Analysis Services, and the SQL Server is a challenge for many business owners, especially those without in-depth data science knowledge. Letting specialists do the job means no one needs to learn all of these separate systems or connect them manually.

When you hire a data analytics firm, you simply tell them what you want to learn from your data and their team of data scientists will create the right models, visuals, and dashboards for your needs. They’ll also help you migrate your data storage system to the cloud safely and seamlessly. With their help, you’ll create insightful data models and compelling visuals at the touch of a button.

To create the most accurate data models and visuals, contact Tek Leaders. We provide our clients with all of the tools they need to gain valuable insights from their data, including advanced data analytics tools, predictive modeling, visualizations, reports, data governance, secure storage, and more. If you have more questions about how our services compare with Power BI and Azure Analysis Services, you can reach us by email directly.

Author: Shashank Reddy Tummala.

Shashank is the COO of Tek Leaders inc.He helps SMB’s to achieve their goals in their journey of Digital Transformation.