Business Intelligence SaaS - 5 tools we tried you should know about

By

Aleks Tiupikov

Apr 30, 2024

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There's so many different SaaS Business Intelligence tools.

And if you're thinking which one will suit your SaaS well, you might be really confused.

We were in the same boat. So I've spent a week testing different SaaS BI tools, so you don't have to.

Here are the best 5 tools I found that helped me to learn a ton about our business.

Best SaaS BI Tools in 2024

1 . PowerBI

Pros

  • Powerful Excel so looks and feels familiar

  • Works well with R & Python

  • Price is nothing crazy

Cons

  • Not very user friendly

  • Requires a lot of upfront setup work

  • Need to learn custom language to make it work really well

  • Doesn't work on MacOS

Think of it as a more advanced Excel. If your company is already on Microsoft, then you might benefit from it a lot. It's a super capable software that in the right hands can deliver you an insane amount of insights.

Speaking of the right hands...

Set Up

This tool will not work if you're non-technical. Even technical people might find it confusing to use.

So to set this up, companies typically go with 2 options:

  1. Do it internally and load engineers to set it up. (If you have data analysts you probably already use some BI tool)

  2. Hire a contractor to do it for you. There's I think a consultant profession called "PowerBI Consultant" and all they do for living is configure PowerBI for companies. So you definitely can get a lot of value from hiring one - but it will cost you good money.

Overall it's a great tool for teams that operating in Microsoft Ecosystem.


2. Tableau

Pros

  • Super nice visuals

  • Data connectivity options

  • Built for analysts in first place

  • Great support community

Cons

  • A lot of things require hacky workaround

  • Expensive

  • Not really for business reporting

Tableau is great for data teams. It's got very powerful visualization capabilities and data manipulation features t

But the main problem of it is it wasn't originally designed with business people in mind. In 90% of case need to have a dedicated BI person that is going to work on creating meaningful reports for managers to work with.

That's not to say business managers and executives can't use Tableau. They can, but it often requires a dedicated BI person to create meaningful reports that non-technical folks can understand and work with.

Without that support, the learning curve can be pretty intimidating, and you might end up with a powerful tool that no one knows how to use effectively.

If you're considering Tableau for your organization, make sure you have the resources in place to support it.

That could mean hiring a BI specialist, providing extensive training for your team, or even bringing in a consultant to help get you set up.


3. Popsql

Pros

  • Great SQL writing experience

  • Very affordable

  • SQL collaboration

  • Great app look and feel

Cons

  • Basic charts & reports

  • No data cleaning options

  • No python integrations

PopSQL may not be a traditional BI tool, but it deserves a spot in this list since we're discussing BI solutions for SaaS businesses.

Realistically, writing SQL queries can handle most of the analytical needs that BI tools are used for in SaaS companies. For more advanced modeling, Python and R libraries are often the go-to tools.

So, why not focus on having a great SQL experience at a reasonable cost without overspending on BI tools?

This approach may not suit every team, but it has its merits. A typical analytics stack for this setup could include:

  1. A product analytics tool like Posthog or Mixpanel for tracking user behavior and gathering user analytics insights.

  2. PopSQL for writing, editing, and sharing SQL queries and reports with your team.

  3. Python with Jupyter notebooks or other libraries for advanced data analysis and modeling.

This combination of tools can be highly effective for many SaaS products.

PopSQL has nice features such as syntax highlighting, auto-completion, and version control, making it really easy to work together on SQL queries.

While this approach may not be suitable for every organization, it's worth considering as an alternative to expensive BI tools, especially for SaaS businesses that heavily rely on SQL (since you probably have a well maintained database) and have a strong focus on product analytics.


4. Amplitude

Pros

  • Very user friendly interface

  • Great data export functionality

  • A/B testing functionality

  • Product events tracking

Cons

  • Not a comprehensive BI tool. But great for SaaSes

  • Pricey

  • Plenty of interface limitations that require custom coding

This is another great "SaaS BI tool" if you wish. I've seen product and finance teams being able to answer 90% of their requests only from Amplitude, which is... impressive, given that it was built to be a product analytics tool.

The reason I decided to include it here is primarily because of how highly customizable this product is. You can push revenue data inside of it and do arithmetic operations around it. Something Mixpanel, Heap, or Posthog (main alternatives) handle pretty poorly.

And considering the fact that it will have a lot of product analytics inside of it, which is based on events tracking, you are getting an overarching view of your SaaS performance.

Another neat feature is A/B testing. If you run SaaS, you've got to be A/B testing things a lot. And trust me, analyzing experiments using traditional BI software is... painful.

However, keep in mind - this all is not going to happen out of the box. You can't simply add their JS library to your product and start getting all of the things above.

You will need to spend a good amount of time setting it up. Your engineers will have to add this to their roadmap, and you'll need to learn how the tool works.

Not to say this is something only related to Amplitude, but the setup process can be a bit more involved compared to some other tools on this list.

But with all that, I think the level of customization and control you get with Amplitude for your SaaS business makes it worth the effort.


5. Looker

Pros

  • Great for non-technical people

  • Data modeling layer with "sql injection"

  • Can do basic pivots with no code

Cons

  • Super slow on some reports

  • Need to learn lookml

  • Has a nice 1 year free plan if you use BigQuery

  • A bit dated design

Last but not least... Looker. I wasn't very confident about putting it in the list since I know how tricky this software is. It's not the most intuitive one to set up, for sure, but once you do it - the experience for business people reading the reports is great.

Mainly because it's very straightforward how to slice and dice the data and even create pivot tables.

The complex part is creating the reports. I used to very much dislike Google Data Studio due to its limitations and unintuitive UX, and here the situation is very similar. If in PowerBI or Tableau you can pretty much figure it out as you're playing with the tool - this is definitely not the case with Looker.

You'll have to learn what LookML is, how to create different models, views, objects, and so on. Is it powerful? Yes. Will you enjoy going through all of this? Definitely not.

The other big benefit, however, is Looker works great with BigQuery. And BigQuery is a very popular data warehouse choice for a few reasons. So it might be a great addition to it.

Plus, as far as I know, Google offers a great 1-year free offer to try Looker if you actively use BigQuery. So it might make sense to give it a shot.


SaaS BI Top Use Cases

Generally speaking, your BI tool should cover all the use cases that your product analytics tool doesn't cover. Those are things that require revenue calculation in 9/10 cases. Especially when your product has different payment plans and options.

It supposes to give you actionable insights to make data-driven decisions. BI tools have seamless integration with your data sources, so you can get a complete picture of your business performance in one place.

With interactive dashboards and real-time data, you can spot trends and opportunities quickly.

  • Visual representations make it easy to understand complex data even for not very sophisticated users.

  • Predictive analytics help you anticipate future outcomes and plan accordingly.

  • Customizable reports let you focus on the metrics that matter most to your business.

  • Integration capabilities allow you to connect data from multiple sources for a comprehensive view. Whereas user-friendly interfaces make it easy for anyone to explore data and find valuable insights.

Cloud-based SaaS BI tools eliminate the need for upfront investments in hardware and infrastructure. You can access your data and insights from anywhere, at any time.

With advanced analytics functionality, you can perform deeper analysis and uncover hidden patterns in your data. Machine learning algorithms can automate complex tasks and provide more accurate predictions.

SaaS BI tools also offer self-service capabilities, so business users can create their own reports and dashboards without relying on IT consultants/teams. This empowers teams to make informed decisions based on real-time data.

Whether you're looking to improve customer satisfaction, optimize operations, or drive revenue growth, SaaS BI tools give you the insights you need to succeed. They provide a competitive edge by enabling data-driven decision-making across your organization.


To Sum Up - What SaaS BI Does Your Company Need?

The answer is, as always - it depends. If you're more into SQL and a lot of people in your team feel comfortable writing it - I'd go with PostgreSQL as your go-to business intelligence tool. It's enough to get the majority of valuable insights in the right hands. Combined with product analytics tools like Amplitude, it will cover 95% of your data needs.

If you're looking for the more old and proven way of creating interactive dashboards and then providing your management and investors level with visual powerful business analytics, then traditional reporting tools like Tableau or PowerBI will do the job really well.

They have great community support, a lot of documentation, and industry experts, so you will most certainly get what you need, even though it might be an overkill for your SaaS and might cost you some good money.

And finally, speaking of customizable dashboards, if you're looking for a really powerful visualization tool that will live on top of BigQuery and your business users can easily interact with, and this will help with informed decision-making - Looker would be your go-to SaaS Business Intelligence platform.

At the end of the day - give them all a shot. Create a list of 5 questions and try to answer them using each of these tools. This way, you will see what fits you and your business the most.

There's no silver bullet BI tool. You need to find what works best for you. And I hope this article did help with that a bit.

There's so many different SaaS Business Intelligence tools.

And if you're thinking which one will suit your SaaS well, you might be really confused.

We were in the same boat. So I've spent a week testing different SaaS BI tools, so you don't have to.

Here are the best 5 tools I found that helped me to learn a ton about our business.

Best SaaS BI Tools in 2024

1 . PowerBI

Pros

  • Powerful Excel so looks and feels familiar

  • Works well with R & Python

  • Price is nothing crazy

Cons

  • Not very user friendly

  • Requires a lot of upfront setup work

  • Need to learn custom language to make it work really well

  • Doesn't work on MacOS

Think of it as a more advanced Excel. If your company is already on Microsoft, then you might benefit from it a lot. It's a super capable software that in the right hands can deliver you an insane amount of insights.

Speaking of the right hands...

Set Up

This tool will not work if you're non-technical. Even technical people might find it confusing to use.

So to set this up, companies typically go with 2 options:

  1. Do it internally and load engineers to set it up. (If you have data analysts you probably already use some BI tool)

  2. Hire a contractor to do it for you. There's I think a consultant profession called "PowerBI Consultant" and all they do for living is configure PowerBI for companies. So you definitely can get a lot of value from hiring one - but it will cost you good money.

Overall it's a great tool for teams that operating in Microsoft Ecosystem.


2. Tableau

Pros

  • Super nice visuals

  • Data connectivity options

  • Built for analysts in first place

  • Great support community

Cons

  • A lot of things require hacky workaround

  • Expensive

  • Not really for business reporting

Tableau is great for data teams. It's got very powerful visualization capabilities and data manipulation features t

But the main problem of it is it wasn't originally designed with business people in mind. In 90% of case need to have a dedicated BI person that is going to work on creating meaningful reports for managers to work with.

That's not to say business managers and executives can't use Tableau. They can, but it often requires a dedicated BI person to create meaningful reports that non-technical folks can understand and work with.

Without that support, the learning curve can be pretty intimidating, and you might end up with a powerful tool that no one knows how to use effectively.

If you're considering Tableau for your organization, make sure you have the resources in place to support it.

That could mean hiring a BI specialist, providing extensive training for your team, or even bringing in a consultant to help get you set up.


3. Popsql

Pros

  • Great SQL writing experience

  • Very affordable

  • SQL collaboration

  • Great app look and feel

Cons

  • Basic charts & reports

  • No data cleaning options

  • No python integrations

PopSQL may not be a traditional BI tool, but it deserves a spot in this list since we're discussing BI solutions for SaaS businesses.

Realistically, writing SQL queries can handle most of the analytical needs that BI tools are used for in SaaS companies. For more advanced modeling, Python and R libraries are often the go-to tools.

So, why not focus on having a great SQL experience at a reasonable cost without overspending on BI tools?

This approach may not suit every team, but it has its merits. A typical analytics stack for this setup could include:

  1. A product analytics tool like Posthog or Mixpanel for tracking user behavior and gathering user analytics insights.

  2. PopSQL for writing, editing, and sharing SQL queries and reports with your team.

  3. Python with Jupyter notebooks or other libraries for advanced data analysis and modeling.

This combination of tools can be highly effective for many SaaS products.

PopSQL has nice features such as syntax highlighting, auto-completion, and version control, making it really easy to work together on SQL queries.

While this approach may not be suitable for every organization, it's worth considering as an alternative to expensive BI tools, especially for SaaS businesses that heavily rely on SQL (since you probably have a well maintained database) and have a strong focus on product analytics.


4. Amplitude

Pros

  • Very user friendly interface

  • Great data export functionality

  • A/B testing functionality

  • Product events tracking

Cons

  • Not a comprehensive BI tool. But great for SaaSes

  • Pricey

  • Plenty of interface limitations that require custom coding

This is another great "SaaS BI tool" if you wish. I've seen product and finance teams being able to answer 90% of their requests only from Amplitude, which is... impressive, given that it was built to be a product analytics tool.

The reason I decided to include it here is primarily because of how highly customizable this product is. You can push revenue data inside of it and do arithmetic operations around it. Something Mixpanel, Heap, or Posthog (main alternatives) handle pretty poorly.

And considering the fact that it will have a lot of product analytics inside of it, which is based on events tracking, you are getting an overarching view of your SaaS performance.

Another neat feature is A/B testing. If you run SaaS, you've got to be A/B testing things a lot. And trust me, analyzing experiments using traditional BI software is... painful.

However, keep in mind - this all is not going to happen out of the box. You can't simply add their JS library to your product and start getting all of the things above.

You will need to spend a good amount of time setting it up. Your engineers will have to add this to their roadmap, and you'll need to learn how the tool works.

Not to say this is something only related to Amplitude, but the setup process can be a bit more involved compared to some other tools on this list.

But with all that, I think the level of customization and control you get with Amplitude for your SaaS business makes it worth the effort.


5. Looker

Pros

  • Great for non-technical people

  • Data modeling layer with "sql injection"

  • Can do basic pivots with no code

Cons

  • Super slow on some reports

  • Need to learn lookml

  • Has a nice 1 year free plan if you use BigQuery

  • A bit dated design

Last but not least... Looker. I wasn't very confident about putting it in the list since I know how tricky this software is. It's not the most intuitive one to set up, for sure, but once you do it - the experience for business people reading the reports is great.

Mainly because it's very straightforward how to slice and dice the data and even create pivot tables.

The complex part is creating the reports. I used to very much dislike Google Data Studio due to its limitations and unintuitive UX, and here the situation is very similar. If in PowerBI or Tableau you can pretty much figure it out as you're playing with the tool - this is definitely not the case with Looker.

You'll have to learn what LookML is, how to create different models, views, objects, and so on. Is it powerful? Yes. Will you enjoy going through all of this? Definitely not.

The other big benefit, however, is Looker works great with BigQuery. And BigQuery is a very popular data warehouse choice for a few reasons. So it might be a great addition to it.

Plus, as far as I know, Google offers a great 1-year free offer to try Looker if you actively use BigQuery. So it might make sense to give it a shot.


SaaS BI Top Use Cases

Generally speaking, your BI tool should cover all the use cases that your product analytics tool doesn't cover. Those are things that require revenue calculation in 9/10 cases. Especially when your product has different payment plans and options.

It supposes to give you actionable insights to make data-driven decisions. BI tools have seamless integration with your data sources, so you can get a complete picture of your business performance in one place.

With interactive dashboards and real-time data, you can spot trends and opportunities quickly.

  • Visual representations make it easy to understand complex data even for not very sophisticated users.

  • Predictive analytics help you anticipate future outcomes and plan accordingly.

  • Customizable reports let you focus on the metrics that matter most to your business.

  • Integration capabilities allow you to connect data from multiple sources for a comprehensive view. Whereas user-friendly interfaces make it easy for anyone to explore data and find valuable insights.

Cloud-based SaaS BI tools eliminate the need for upfront investments in hardware and infrastructure. You can access your data and insights from anywhere, at any time.

With advanced analytics functionality, you can perform deeper analysis and uncover hidden patterns in your data. Machine learning algorithms can automate complex tasks and provide more accurate predictions.

SaaS BI tools also offer self-service capabilities, so business users can create their own reports and dashboards without relying on IT consultants/teams. This empowers teams to make informed decisions based on real-time data.

Whether you're looking to improve customer satisfaction, optimize operations, or drive revenue growth, SaaS BI tools give you the insights you need to succeed. They provide a competitive edge by enabling data-driven decision-making across your organization.


To Sum Up - What SaaS BI Does Your Company Need?

The answer is, as always - it depends. If you're more into SQL and a lot of people in your team feel comfortable writing it - I'd go with PostgreSQL as your go-to business intelligence tool. It's enough to get the majority of valuable insights in the right hands. Combined with product analytics tools like Amplitude, it will cover 95% of your data needs.

If you're looking for the more old and proven way of creating interactive dashboards and then providing your management and investors level with visual powerful business analytics, then traditional reporting tools like Tableau or PowerBI will do the job really well.

They have great community support, a lot of documentation, and industry experts, so you will most certainly get what you need, even though it might be an overkill for your SaaS and might cost you some good money.

And finally, speaking of customizable dashboards, if you're looking for a really powerful visualization tool that will live on top of BigQuery and your business users can easily interact with, and this will help with informed decision-making - Looker would be your go-to SaaS Business Intelligence platform.

At the end of the day - give them all a shot. Create a list of 5 questions and try to answer them using each of these tools. This way, you will see what fits you and your business the most.

There's no silver bullet BI tool. You need to find what works best for you. And I hope this article did help with that a bit.

There's so many different SaaS Business Intelligence tools.

And if you're thinking which one will suit your SaaS well, you might be really confused.

We were in the same boat. So I've spent a week testing different SaaS BI tools, so you don't have to.

Here are the best 5 tools I found that helped me to learn a ton about our business.

Best SaaS BI Tools in 2024

1 . PowerBI

Pros

  • Powerful Excel so looks and feels familiar

  • Works well with R & Python

  • Price is nothing crazy

Cons

  • Not very user friendly

  • Requires a lot of upfront setup work

  • Need to learn custom language to make it work really well

  • Doesn't work on MacOS

Think of it as a more advanced Excel. If your company is already on Microsoft, then you might benefit from it a lot. It's a super capable software that in the right hands can deliver you an insane amount of insights.

Speaking of the right hands...

Set Up

This tool will not work if you're non-technical. Even technical people might find it confusing to use.

So to set this up, companies typically go with 2 options:

  1. Do it internally and load engineers to set it up. (If you have data analysts you probably already use some BI tool)

  2. Hire a contractor to do it for you. There's I think a consultant profession called "PowerBI Consultant" and all they do for living is configure PowerBI for companies. So you definitely can get a lot of value from hiring one - but it will cost you good money.

Overall it's a great tool for teams that operating in Microsoft Ecosystem.


2. Tableau

Pros

  • Super nice visuals

  • Data connectivity options

  • Built for analysts in first place

  • Great support community

Cons

  • A lot of things require hacky workaround

  • Expensive

  • Not really for business reporting

Tableau is great for data teams. It's got very powerful visualization capabilities and data manipulation features t

But the main problem of it is it wasn't originally designed with business people in mind. In 90% of case need to have a dedicated BI person that is going to work on creating meaningful reports for managers to work with.

That's not to say business managers and executives can't use Tableau. They can, but it often requires a dedicated BI person to create meaningful reports that non-technical folks can understand and work with.

Without that support, the learning curve can be pretty intimidating, and you might end up with a powerful tool that no one knows how to use effectively.

If you're considering Tableau for your organization, make sure you have the resources in place to support it.

That could mean hiring a BI specialist, providing extensive training for your team, or even bringing in a consultant to help get you set up.


3. Popsql

Pros

  • Great SQL writing experience

  • Very affordable

  • SQL collaboration

  • Great app look and feel

Cons

  • Basic charts & reports

  • No data cleaning options

  • No python integrations

PopSQL may not be a traditional BI tool, but it deserves a spot in this list since we're discussing BI solutions for SaaS businesses.

Realistically, writing SQL queries can handle most of the analytical needs that BI tools are used for in SaaS companies. For more advanced modeling, Python and R libraries are often the go-to tools.

So, why not focus on having a great SQL experience at a reasonable cost without overspending on BI tools?

This approach may not suit every team, but it has its merits. A typical analytics stack for this setup could include:

  1. A product analytics tool like Posthog or Mixpanel for tracking user behavior and gathering user analytics insights.

  2. PopSQL for writing, editing, and sharing SQL queries and reports with your team.

  3. Python with Jupyter notebooks or other libraries for advanced data analysis and modeling.

This combination of tools can be highly effective for many SaaS products.

PopSQL has nice features such as syntax highlighting, auto-completion, and version control, making it really easy to work together on SQL queries.

While this approach may not be suitable for every organization, it's worth considering as an alternative to expensive BI tools, especially for SaaS businesses that heavily rely on SQL (since you probably have a well maintained database) and have a strong focus on product analytics.


4. Amplitude

Pros

  • Very user friendly interface

  • Great data export functionality

  • A/B testing functionality

  • Product events tracking

Cons

  • Not a comprehensive BI tool. But great for SaaSes

  • Pricey

  • Plenty of interface limitations that require custom coding

This is another great "SaaS BI tool" if you wish. I've seen product and finance teams being able to answer 90% of their requests only from Amplitude, which is... impressive, given that it was built to be a product analytics tool.

The reason I decided to include it here is primarily because of how highly customizable this product is. You can push revenue data inside of it and do arithmetic operations around it. Something Mixpanel, Heap, or Posthog (main alternatives) handle pretty poorly.

And considering the fact that it will have a lot of product analytics inside of it, which is based on events tracking, you are getting an overarching view of your SaaS performance.

Another neat feature is A/B testing. If you run SaaS, you've got to be A/B testing things a lot. And trust me, analyzing experiments using traditional BI software is... painful.

However, keep in mind - this all is not going to happen out of the box. You can't simply add their JS library to your product and start getting all of the things above.

You will need to spend a good amount of time setting it up. Your engineers will have to add this to their roadmap, and you'll need to learn how the tool works.

Not to say this is something only related to Amplitude, but the setup process can be a bit more involved compared to some other tools on this list.

But with all that, I think the level of customization and control you get with Amplitude for your SaaS business makes it worth the effort.


5. Looker

Pros

  • Great for non-technical people

  • Data modeling layer with "sql injection"

  • Can do basic pivots with no code

Cons

  • Super slow on some reports

  • Need to learn lookml

  • Has a nice 1 year free plan if you use BigQuery

  • A bit dated design

Last but not least... Looker. I wasn't very confident about putting it in the list since I know how tricky this software is. It's not the most intuitive one to set up, for sure, but once you do it - the experience for business people reading the reports is great.

Mainly because it's very straightforward how to slice and dice the data and even create pivot tables.

The complex part is creating the reports. I used to very much dislike Google Data Studio due to its limitations and unintuitive UX, and here the situation is very similar. If in PowerBI or Tableau you can pretty much figure it out as you're playing with the tool - this is definitely not the case with Looker.

You'll have to learn what LookML is, how to create different models, views, objects, and so on. Is it powerful? Yes. Will you enjoy going through all of this? Definitely not.

The other big benefit, however, is Looker works great with BigQuery. And BigQuery is a very popular data warehouse choice for a few reasons. So it might be a great addition to it.

Plus, as far as I know, Google offers a great 1-year free offer to try Looker if you actively use BigQuery. So it might make sense to give it a shot.


SaaS BI Top Use Cases

Generally speaking, your BI tool should cover all the use cases that your product analytics tool doesn't cover. Those are things that require revenue calculation in 9/10 cases. Especially when your product has different payment plans and options.

It supposes to give you actionable insights to make data-driven decisions. BI tools have seamless integration with your data sources, so you can get a complete picture of your business performance in one place.

With interactive dashboards and real-time data, you can spot trends and opportunities quickly.

  • Visual representations make it easy to understand complex data even for not very sophisticated users.

  • Predictive analytics help you anticipate future outcomes and plan accordingly.

  • Customizable reports let you focus on the metrics that matter most to your business.

  • Integration capabilities allow you to connect data from multiple sources for a comprehensive view. Whereas user-friendly interfaces make it easy for anyone to explore data and find valuable insights.

Cloud-based SaaS BI tools eliminate the need for upfront investments in hardware and infrastructure. You can access your data and insights from anywhere, at any time.

With advanced analytics functionality, you can perform deeper analysis and uncover hidden patterns in your data. Machine learning algorithms can automate complex tasks and provide more accurate predictions.

SaaS BI tools also offer self-service capabilities, so business users can create their own reports and dashboards without relying on IT consultants/teams. This empowers teams to make informed decisions based on real-time data.

Whether you're looking to improve customer satisfaction, optimize operations, or drive revenue growth, SaaS BI tools give you the insights you need to succeed. They provide a competitive edge by enabling data-driven decision-making across your organization.


To Sum Up - What SaaS BI Does Your Company Need?

The answer is, as always - it depends. If you're more into SQL and a lot of people in your team feel comfortable writing it - I'd go with PostgreSQL as your go-to business intelligence tool. It's enough to get the majority of valuable insights in the right hands. Combined with product analytics tools like Amplitude, it will cover 95% of your data needs.

If you're looking for the more old and proven way of creating interactive dashboards and then providing your management and investors level with visual powerful business analytics, then traditional reporting tools like Tableau or PowerBI will do the job really well.

They have great community support, a lot of documentation, and industry experts, so you will most certainly get what you need, even though it might be an overkill for your SaaS and might cost you some good money.

And finally, speaking of customizable dashboards, if you're looking for a really powerful visualization tool that will live on top of BigQuery and your business users can easily interact with, and this will help with informed decision-making - Looker would be your go-to SaaS Business Intelligence platform.

At the end of the day - give them all a shot. Create a list of 5 questions and try to answer them using each of these tools. This way, you will see what fits you and your business the most.

There's no silver bullet BI tool. You need to find what works best for you. And I hope this article did help with that a bit.

Start retrieving the insights in your own language

Think about the last time you had a question about your data. How long did it take to answer it?

Start retrieving the insights in your own language

Think about the last time you had a question about your data. How long did it take to answer it?

Start retrieving the insights in your own language

Think about the last time you had a question about your data. How long did it take to answer it?

Copyright © 2024 Docugenie, Inc.

Copyright © 2024 Docugenie, Inc.

Copyright © 2024 Docugenie, Inc.