An Alternative to Microsoft Power BI. How Governments Are Leaving Microsoft for MPP BI

Recently we’ve noticed a trend when meeting with government data teams around the world - many of them start using Microsoft Power BI because that’s already generally accepted, but they get stumped when getting ready to productionize because they need their data on-prem.

Many start their analytics projects with Microsoft Power BI because it's the tool they already know. They don't always stop to ask what other options are available and happily accept their fate of being pushed to the cloud.

One of our government clients was the same. The organization works with sensitive social data and supports the ministry of labor and social affairs of the Republic of Armenia. As their reporting needs grew, they started running into challenges and limitations. That's when the team began looking at other Microsoft Power BI alternatives.

MPP BI is an enterprise business intelligence platform designed for organizations that need secure and scalable analytics with more flexibility in how they manage their data.

In this article, we'll walk through the exact problems teams face with Power BI, and how switching to MPP BI as an alternative can solve them. We'll also share the story of this government organization and why it decided to make the switch.

The Power BI Limitations Governments Run Into

#1. Dependence on the Microsoft ecosystem

Microsoft Power BI works best when it is part of a larger Microsoft environment. For organizations already using tools like Microsoft 365, OneDrive, and Azure, this can be convenient.However, many government organizations work with a mix of different systems and databases. Depending heavily on one ecosystem can create challenges when teams need more flexibility.

Limited storage and collaboration flexibility in Power BI

Power BI is closely connected with Microsoft services, including OneDrive. Organizations that use other platforms may need additional steps to connect their existing workflows.

MPP BI works with any tool you use

MPP BI is tool-agnostic, and it doesn’t require your organization to use a specific set of tools.It connects with many different tools and databases, no matter who built them. Your team can keep using the systems they already have, including Google Drive, or any other storage and collaboration tools, without needing to switch to a specific ecosystem just to make the platform work.

#2. Deployment: on-premise vs on cloud deployments

When choosing a BI platform, governments usually have to think carefully about where their data is stored and how their systems are managed.Some organizations prefer cloud deployments because they are easier to maintain and scale. Others require on-premise deployment because of security policies or the need to keep sensitive data inside their own infrastructure.

Power BI on-premise

Power BI offers an on-premise option through Power BI Report Server. But even running it outside the Microsoft cloud, it still depends on Microsoft's software stack.Some challenges include:

• Windows-based environment requirements: Power BI Report Server only runs on Windows Server, and Power BI Desktop is also Windows-only. This limits organizations that use other operating systems.
• Additional Microsoft components required: Power BI Report Server needs a SQL Server database to store reports, and typically Active Directory to manage user authentication. A full deployment usually involves several Microsoft products working together, not just Power BI Report Server on its own.
• Licensing tied to Microsoft's cloud: Even for on-premise use, activating a license requires a product key obtained through the Power BI service or the Microsoft 365 admin center.

MPP BI keeps data on your own infrastructure

MPP BI supports both cloud and on-premise deployment, so organizations can choose the setup that fits their needs, rather than being limited to one option.For governments that need to keep their sensitive data inside their own infrastructure, MPP BI can run entirely on-premise, using existing servers and databases. This means:

• Data stays within the organization's own systems.
• There is no dependency on external cloud services.
• Teams can use their existing security policies and access controls.
• The platform can fit into the organization's current IT environment.

#3. 2x-12x Faster Analytics

How other BI tools handle performance

Most BI tools, including Power BI, use a separate analytical engine to process data before creating reports and calculations. This means data needs to be moved, prepared, or stored in another layer before users can get insights from it.That extra step takes time and creates another layer that needs to be managed.

MPP BI calculates data where it already lives

MPP BI calculates results directly where your data already lives, without creating unnecessary copies of your data first. There is nothing extra standing between your question and your answer.This difference in approach, called a data-centric architecture, leads to two advantages:

• MPP BI can process more than 2 billion records in under 5 seconds and maintains performance even when reports and calculations become more complex.
• Depending on the workload and data environment, this approach can deliver up to 12x faster performance compared with traditional BI approaches.

#4. Integration challenges

Government organizations rarely have all their data in one place. A typical environment may include databases, legacy systems, external applications, and internal platforms built over many years. The challenge is connecting to these systems, and creating a reliable way to bring all this data together for reporting and analysis.

Power BI needs extra tools for complex environments

Power BI supports many data sources, but complex environments can require additional tools and steps to make everything work together. For example, connecting on-premise data sources with cloud-based Power BI services may require additional components such as data gateways to transfer data between environments.

MPP BI connects without extra layers

• Flexible connections: Works with a wide range of databases, applications, and data formats, without requiring extra layers.
• Support for existing infrastructure: Fits into current systems and data architecture, without forcing major changes to the technology environment already in place.

#5. Pricing

Cost is often one of the first questions government teams ask, especially when budgets need to be planned carefully. Overall, MPP BI comes with a lower total cost of ownership compared to Power BI.

• Viewer seats ($10/user per month). These let people view dashboards and reports, filter and explore data, export reports to Excel, PDF, or PowerPoint, and ask questions in plain language.
• Admin seats ($18/user per month). These include everything a viewer can do, plus the ability to build and edit dashboards, create reports and presentations, prepare data, set up forecasting, connect new data sources, build dashboards and reports with AI, and manage users, groups, and security settings.
• One-time license. For governments planning long-term budgets, having the choice between a subscription and a one-time license can make a real difference in how costs are planned and managed over time. Pricing depends on your organization's size and needs. Contact our team for a quote.
• No separate tool for data prep. MPP BI includes its own data preparation engine, so there's no need to buy and manage a separate tool just to get data ready for analysis.

#6. Calculation language and MDX compatibility

Many government organizations already store their data in "cube" systems. A cube lets you look at the same data from different angles. You can analyze sales by product, region, month, customer, and so on, without having to build a separate data model for every view.This setup is common with Microsoft SQL Server and SSAS. Power BI connects to these cubes to build reports and dashboards.For organizations that have been using this setup for years, it's common to end up with hundreds of cubes.

What is SSAS

SSAS, short for SQL Server Analysis Services, is a Microsoft tool for organizing and analyzing business data. In other words, it is a layer that sits on top of a database and makes the data easier to analyze.

• SQL Server stores the organization's data.
• SSAS organizes that data into analytical models, including cubes.
• Power BI connects to those cubes to build reports and dashboards.

What is MDX

MDX stands for Multidimensional Expressions. It is the language used to pull data out of a cube. It works a bit like SQL, but it is made for cube data, not regular tables.

Where Power BI runs into trouble with SSAS cubes

Cubes are great for deep analysis, but new calculations often can't be added right away and on the fly. When a user needs a simple formula, they can't build it themselves. They have to ask IT to add it to the cube.This is the opposite of self-service BI. The idea behind self-service BI is that people should be able to do this kind of work on their own.

Why not just move the cube data somewhere else

At first people teams might think it is simpler to move the cube data into a faster database. But a cube is not one dataset, it's a complex model that gives you many different views of the same data.Move that data out of the cube and you may need to recreate those views as separate tables. For example, one cube may require up to 20 different tables.And if the cubes are constantly changing, the ETL processes that keep all those tables updated become another problem.

How MPP BI handles it

Instead of moving the cubes to another database, MPP BI connects directly to the existing SSAS cubes. To do this, MPP BI needed to communicate with SSAS using MDX.MPP BI also has its own language for calculations, called OctoLang. It generates the MDX behind the scenes, so your team never has to write MDX by hand. It is also built to feel familiar to people who already know DAX. So it does not feel like learning a new tool.

What this means for the customer

The new approach gives the customer three major benefits.

1. The technical complexity is hidden. MPP BI can work with the SSAS cubes without forcing the user to understand how MDX works. From the user's perspective, the cube behaves almost like any other data source.
2. Existing cubes can be kept. The company doesn't have to throw away the hundreds of cubes it already built. It can continue using them while moving the visualization and BI layer to MPP BI.
3. Less migration work. Most importantly, the company doesn't have to rebuild all its ETL processes and move huge amounts of data. The existing infrastructure remains in place.

MPP BI vs Microsoft Power BI: At a Glance

Here's a quick side-by-side summary for reference, we've already covered what each of these points means in the sections above.

Feature
Read-only user / month	$10	~$14
Creator / admin / month	$18	~$24
Business logic runs in database	Yes	No
Calculation engine	Not required	Required
Internal data storage	Not required	Required
Data extraction required	Never	Always
On-premises (full)	Full	Limited
Performance vs traditional BI	2x–12x faster	Baseline

The case study: a government's switch to MPP BI

Let's go back to the government client we mentioned earlier. This organization manages digital systems for social services, and works closely with a country's Ministry of Labor and Social Affairs. Its job involves handling large amounts of sensitive citizen data that requires strict rules about who can access it.This organization started with Power BI because it was the familiar choice. And for a while, it did the job well enough.But over time the organization grew with more systems, more users, more data to bring together. Power BI wasn't failing exactly, it just wasn't built for the specific requirements this organization had: keeping sensitive data fully under its own control, scaling without added complexity, and connecting to a wide mix of systems already in place. That's when the organization began to explore other options.MPP BI matched what they needed: full control over sensitive data, room to grow, and the flexibility to connect with the systems already in place.

MPP BI's benefits and features

MPP BI comes with a set of features built specifically for organizations that need to grow and stay secure.

Scalability

MPP BI can scale in two directions:

• Horizontal scaling: add more servers to handle more users or more data.
• Vertical scaling: add more power (like memory or processing capacity) to existing servers.

One node with 24 GB of RAM can already handle several computers processing data at once. Need to support more users? Just add one more node and more RAM.

Microservice architecture

MPP BI is built from many small, independent parts, instead of one large connected system. This is called a microservice architecture.The benefit is durability. In a traditional, all-in-one system, if one part breaks, the whole system can stop working. With MPP BI, if one part has a problem, the rest of the platform keeps running normally.

Security

Government organizations need control over who can see what. MPP BI offers two layers of security:

• Granular access control: set permissions for each part of the system, like data sources, dashboards, and individual charts. This lets you decide exactly what each person can open.
• Row-level security: two people can open the same dashboard, and each one only sees the records they're allowed to see.
• Single sign-on (SSO): Staff can sign in with their existing company account, no need to create or manage separate logins. MPP BI also supports multi-factor authentication, so signing in takes more than just a password.
• Data protection: Passwords are stored in encrypted form, not as plain text. Data is also encrypted while it moves in or out of MPP BI.
• A full record of activity: MPP BI logs every action, so organizations can review what happened at any time. These logs work with standard security monitoring tools already in place.

Customization

MPP BI can be adapted to match an organization's look and workflow. So the platform can feel like part of the organization's own systems.This includes:

• Colors, logos, and fonts
• The overall interface
• Dashboards built around the organization's specific needs

Self-service analytics

MPP BI lets people build their own reports, without waiting on a BI team or analyst every time they need one. Users can connect directly to the data they need, explore it, and create reports on their own.

AI Capabilities (Agentic BI)

• Answer your questions in plain language: Type what you want to know, and it finds the data and gives you an answer.
• Build dashboards: Describe the dashboard or report you need, and it creates it. You can review or edit it, then share it with your team.
• Walk you through the platform as a guide: Not sure how to do something in MPP BI? Just ask, and it shows you.

Reliability and support

MPP BI includes ongoing technical support, including:

• Ongoing support: Our team is available to help with setup, updates, and any technical issues, for as long as you use the platform.
• Regular updates: MPP BI is continually improved with new features and updates over time.

Not sure where to start?

Many teams know their current solution is becoming difficult to maintain or no longer meets their requirements, but they are not always sure what the next step should be. They may also worry that moving to a new platform will require major changes and create more complexity.That hesitation makes sense. Moving away from a system your team already knows can feel like a bigger risk than staying with something that's "good enough." But as we've seen throughout this article, staying with a tool that doesn't fit your needs comes with its own cost, in security, in scalability, and in how much control you have over your own data.

Sahar Fallah

Marketing Specialist

Sahar Fallah is a Marketing Specialist at MPP Insights. She has four years of experience in marketing and technology-focused work. She is part of the team that builds and supports BI solutions, dashboards, and data pipelines. She creates content that helps businesses understand and use their data. Sahar works closely with the team and clients to understand their challenges and goals. She turns those into clear, practical content.