Best BI tools for startups: How to choose a BI tool

Find the right data analytics and business intelligence tool for your organization with this guide to some of the best BI tools for startups.

Published on Jan 17, 2024 by AirOps Team

Business Intelligence (BI) tools are software applications that take unstructured data from many sources, prepare the data for analysis, analyze it, and provide insights in an easy-to-understand format, like dashboards, visuals, and other reports. 

BI tools make it easy to query your organization’s data so that your teams can discover valuable business insights. These insights can increase operational efficiency, enable quicker and better business decisions, help remove operational bottlenecks, and ultimately drive revenue. 

There are tons of BI tools available, 

Since there’s no one-size fits all BI tool for every company, we’re going to share 12 of our favorites, grouped by the tools that are:

  • Business user-friendly
  • Technical user-friendly
  • OEM (original equipment manufacturer) BI tools
  • Low entry cost

Once we review 12 of the best BI tools for startups, we’ll share the six most important things that you need to keep in mind when choosing a tool. 

Finally, we’ll close things out with our point of view that explains why a BI tool is unlikely to solve all of your startup’s data-related problems. BI tools are powerful and have a place in many modern data stacks, but they aren't a cure-all – going in with eyes wide open will help you make the right decisions and manage expectations.

Business user-friendly BI tools for startups

If you want to solve the data adoption problem, your data stack needs to be built with user-friendly tools that anyone in your organization can learn how to use. This is especially important if your BI tool will be primarily used by people in departments like sales, marketing, and operations. These business end-users are generally more accustomed to working in spreadsheets or other operating documents and may avoid using BI tools. They may also not have advanced technical data skills.

If this describes the users in your organization, you’ll want to pick a user-friendly BI tool that’s easier to learn. User-friendly tools are easy to install, their user interface is intuitive, you can master them quickly, and they don’t require programming chops to use. 

1. Tableau

Tableau is a popular BI tool with a loyal fan base. It has a slick drag-and-drop interface that’s powerful and easy to learn. Tableau does not require scripting or programming knowledge to use, which is a big plus for teams with limited technical resources. If your users frequently work from their smartphones, the mobile apps offer almost as much functionality as the desktop version.

Tableau can be expensive, though. The pricing depends on the number of users (licenses), whether you use Tableau Cloud for hosting or opt to self-host with Tableau Server, and whether you use add-ons like Embedded Analytics. 

At a minimum, you can expect to spend $70 per user per month with Tableau. If you want more features, like report sharing, you'll need Tableau Server (which is even more expensive) or Tableau Online (which has more limited functionality). To unlock the more advanced features, you’ll need someone who knows SQL to create rich and complex data sets.

Tableau offers a free trial.

2. Microsoft Power BI

Microsoft Power BI has led Gartner’s Magic Quadrant rankings for BI tools for the past dozen years. The Power BI solution consists of the Power BI Desktop (a free Windows standalone tool), the cloud-based Power BI Service, and the Power BI Report Server.

Power BI comes bundled with Office 365 Enterprise Edition, which is a huge plus for organizations that are already heavily invested in the Microsoft/Azure/Office365 ecosystem. Its low pricing and rich feature set make it an attractive option for startups that already use Microsoft tools. It has comprehensive analytics and ML capabilities. Its AI services are powered by Azure.

The simple UI is intuitive and the dashboards that Power BI generates are easy to use with rich visualizations.

Power BI is priced from $10 to $20 per user/month. There is a $5,000/month option for unlimited users.

Power BI offers a free trial.

3. Qlik

Qlik is a flexible and scalable BI tool that can carry out data analysis and visualization for a wide range of users but is targeted at enterprises. It has a strong product vision for machine learning.

Qlik runs entirely in the cloud and setup is fast and easy. Its AI capabilities enable non-technical users to perform data analysis with ease. However, some users may not find its UI as visually intuitive as other BI tools on this list.

Qlik’s pricing is complex, so you’ll want to review their pricing page yourself if you’re serious about this tool. A Qlik Sense license includes analytical and BI capabilities. Add-ons like Qlik Catalog, Insight Advisor Chat, and Qlik NPrinting cost more. The Qlik-hosted Qlik Sense Business Data Analytics solution costs $30/user/month.

You can try the product for free.

Technical user-friendly BI tools

This group of tools contains a similar set of BI tool features but is geared toward a more technical user group. Non-technical users can still use these tools, but you can get more out of them if you have advanced programming capabilities.

Looker, for instance, extends SQL to make it collaborative and extensible. You can make changes, such as defining new terms, then share your changes via Git. Mode, another technically oriented tool, is integrated with more than 60 data science libraries. Power users can pipe data directly to these libraries to perform complex analyses.

4. Looker

Google acquired Looker in 2020.

Looker is a cloud-first BI tool: it's completely web-based, is optimized for cloud data warehouses, and sits directly on top of your data, which makes for a user-friendly workflow.

Looker provides strong developer support. It offers extensive APIs, SDKs (for Python, R, JavaScript, and other languages), and developer tools. Developers can use them to create custom analytics and embed them in workflows or applications.

The Looker platform is based on the LookML language.

Looker does not publish pricing data on its website – you must request a quote.

There’s no free trial for Looker.

5. Mode Analytics

Mode BI is a cloud-based analytics platform that combines a SQL editor, Python and R notebooks, and a drag-and-drop visualization editor. This makes Mode a great choice for data analysts, data scientists, and analytics engineers who want a code-first workflow.

Mode makes it easy to collect data and analyze it seamlessly without switching applications. You can write HTML, CSS, and JavaScript code to embed dashboards into websites. You can also share reports via a web URL, email, or Slack. 

The shared SQL editor supports collaboration, while the visualization editor allows you to drill down to the level you need.

Mode’s Studio plan is free for up to 5 users. Contact Mode for a demo or quote for the more powerful Business (you can request a free trial) and Enterprise plans.

OEM BI tools

OEM BI tools are meant to be integrated or embedded into other products, applications, or workflows. They are designed to integrate seamlessly with the application, reducing development costs and time. They are customized for different business domains.

Providers offer the OEM BI tools (also known as embedded BI) to their customers bundled with a SaaS application. This helps users get critical insights into their data, thereby increasing the value of their product. OEM BI tools also help SaaS companies increase customer acquisition, reduce churn, and boost revenue.

6. Sisense 

Sisense is an end-to-end analytics platform that supports complex data projects and the development of analytics apps. Most Sisense customers use the product in OEM form.

The Sisense platform comprises three components: 

  1. Sisense Fusion Embed, which helps integrate customized analytics into your products and is built on an API-first architecture that can be easily embedded through the Sisense.JS javascript library.
  2. Sisense Infusion Apps, which enable users to query data with NLQ and analyze and share information. 
  3. Sisense Fusion Analytics, which uses ML to provide advanced analytical insights.

The product offers a free trial. Reach out to the company for pricing information.

7. ThoughtSpot

ThoughtSpot is an innovative, AI-powered analytics platform. It uses search and NLP (natural language query) as the primary means of querying data. 

Queries can be made by typing or speech, making it easy for non-technical users. The inbuilt AI fires queries that users may not have thought of, then pushes these auto-generated insights back to the users. ThoughtSpot can easily support complex queries on big data.

ThoughtSpot has a Team version starting at $95 per month and a Pro version at $2,500 per month. Both support unlimited users. Contact ThoughtSpot to get a quote on two other versions, Enterprise and Everywhere.

A free trial is available. 

8. Domo

Domo is known for ease of use and fast time to deployment. Its cloud-based platform offers several data connectors, user-friendly visualizations, and a low-code environment for application development.

The platform is designed for cloud and mobile – it comes with iOS and Android apps. The Domo Sandbox enables customers to use a DevOps approach to data analytics. Domo simplifies ETL (extract, transform, load) processing.

The cloud-based processing has its advantages (lower load on client machines, easy to share dashboards and information) and disadvantages (slower in some situations).

Domo has a reputation for being pricey. Call them for a quote. They offer a free trial.

Low entry cost BI tools

Data is one of the most valuable assets that a business can have. Using the right BI tool to analyze the data and glean insights may mean the difference between success and failure. Hence, BI tools are critical to most businesses.

The tools we have looked at are all excellent choices, but they are also expensive. This may be a deal-breaker for many startups.

The BI tools that we will look at now are much more affordable. Some of them are open-source and totally free, if self-hosted. Yet, they are packed with impressive features and will more than suffice as entry-level tools.  

9. AWS QuickSight 

AWS QuickSight makes it easy for end-users to query data using natural language and receive answers with appropriate visuals. It uses ML to understand the query intent and to analyze the data.

QuickSight is integrated with the AWS stack. The AWS ecosystem enables users to create serverless dashboards very fast. You can set up a query on large amounts of data (think petabytes) in Amazon S3 using Athena (a serverless SQL query service). You can do all this in minutes using cloud-based infrastructure without installing additional software.

QuickSight’s strengths are AWS integration, scalability, performance, and pricing.

QuickSight pricing varies according to whether the user is an Author (dashboard creator) or Reader (dashboard consumer) and whether you pay monthly or yearly. It also depends on whether you subscribe to the Standard version (this starts at $12/user/month) or the Enterprise version.

A free trial is supported.

10. Metabase

Metabase is an open-source BI tool that’s not super common yet but is becoming increasingly popular amongst startups looking for a free BI tool. It lets you query data and provides answers using appropriate visuals, like charts or tables. You can save the queries or group them and use them in dashboards.

You can use SQL if you have complex queries, or you can get answers with a few clicks.

Setup is fast and uncomplicated. Metabase claims that you can get up and running in about 5 minutes.

Critics complain that Metabase is too limited unless your needs are very straightforward. You will need support from your technical team for anything advanced.

The self-hosted, open-source version is free. Hosted services are available in 3 tiers – Starter ($85/month for 5 users), Pro ($500/month for 10 users), and Enterprise (contact for a quote).

11. Preset

Preset is a BI tool built using Apache Superset (which is an open-source data exploration and visualization tool).

Preset sits directly on top of your data, making for speedy access. It is simple to use – you can build dashboards with a few clicks. Data analysis is possible either with the no-code viz builder or the SQL editor.

You can self-host Preset on your AWS servers or use the Preset Cloud.

The self-hosted option is free. The hosted option comes in 3 versions – Starter (free for 5 users), Professional ($20/user/month), and Enterprise (contact the company for a quote).

Free trials are available for some versions.

12. Google Data Studio

Data Studio is a free and easy-to-use BI tool. The built-in and partner connectors enable you to fetch data from several sources. You can create interactive reports and dashboards with the included web-based reporting tools. It is easy to share data and collaborate in real-time.

Users have reported that the product is easy to use after you have got the hang of it. It integrates easily with data sources from the Google ecosystem, like Google Analytics, Google Ads, and YouTube Analytics.

Users have reported usability issues (report generation takes time) and slow speeds with large data sets.

Custom-built libraries & enterprise-level BI tools

Visualization libraries that enable you to custom build are common amongst startups with engineering-forward cultures and startups with technical resources. They allow you to create custom data apps and rich data visualizations.

Some of our favorites in this category are:

And while these enterprise-level BI tools aren’t likely to be on the radar (or in the budgets) of most startups, if you’re curious about the types of tools that a larger, more all-encompassing tech stack might include, it’s worth becoming familiar with them:

A quick comparison of the best BI tools for startups

If you want the TLDR version, here’s a quick comparison of some of the best BI tools for startups:

Deployment Technical Ability Cost
Tableau Vendor-agnostic Drag and drop, SQL Starting at $70/user/month
Microsoft Power BI Vendor lock-in with Microsoft Drag and drop, SQL, better for users familiar with Microsoft data stack $10 - $20 per user/month; $5,000/month option for unlimited users
Qlik Vendor-agnostic Drag and drop, SQL Pricing starting at $30/user/month
Looker Vendor lock-in with Google Cloud LookML, SQL, point and click Contact for a quote
Mode Analytics Vendor-agnostic SQL, R, Python; Better for data scientists and data analysts Studio Plan free for up to 5 users, custom quotes available on request for other tiers
Sisense Vendor-agnostic SQL, Python, point and click; Better for product teams Contact for a quote
Thoughtspot Vendor-agnostic SQL, point and click, natural language query Starting at $95 per month (unlimited users)
Domo Vendor-agnostic Drag and drop, "beast mode" syntax More expensive than others, contact for a quote
AWS Quicksight Vendor lock-in with Amazon’s AWS Drag and drop, SQL Starts at $12/user/month
Metabase Easy-to-use for non-technical end-users Point and click Free self-hosted, open-source version
Preset Vendor-agnostic SQL, drag and drop (generated SQL) Free self-hosted, open-source version
Google Data Studio Vendor lock-in with Google Cloud SQL Free

How to choose the best BI tool for your startup

The information above will help you do a first pass – use it to quickly determine which BI tools could potentially be a good fit for your startup.

Once you have an initial list of candidates, assess each one in more detail based on the following criteria:

1. Workflow

This is the most important (and often most overlooked) piece of criteria – do your users actually like using the BI tool? Many organizations try to find a tool that checks every box in terms of features and functionality. While that’s important, it’s even more important to find a tool that fits into the workflows of your users. It’s especially crucial if you want to solve the data adoption problem and get people to use data.

While we’ve categorized Looker and Mode as the most business-user-friendly BI tools in this list, note that many tools fit into multiple categories. Google Data Studio, Metabase, Domo, and others have no-code and low-code interfaces that are very easy to use.

2. Integration

Any BI tool you consider needs to play nice with the tools and technologies your team already uses.

When vetting BI tools for your startup, make sure your final pick integrates with everything in your modern data stack, including your cloud data warehouse and SaaS apps. Keep in mind that even if a BI tool supports integration with your favorite technologies, some do a better job than others. For example, Salesforce works great with Tableau because it owns Tableau. The same goes for QuickSight – it’s a good option if you already use AWS cloud services.

3. Deployment

Some BI tools are cloud-vendor specific and others are vendor agnostic. Vendor lock-in is fairly common and there are pros and cons to choosing a tool that’s locked into Amazon (QuickSight), Google (Looker, Data Studio), Microsoft (Power BI), or another vendor.

If your organization already has a significant investment within one cloud vendor, platform provider, or application ecosystem, efficiencies can be gained by using a BI tool within that network. If your startup primarily uses Google tools and services, for example, Looker or Data Studio could be a good fit.

On the other hand, vendor lock-in typically means less flexibility to migrate to other tools in the future. If you don’t want to be locked into a single vendor, look for BI tools with vendor-agnostic deployment options, like Sisense. 

When assessing deployment, you’ll also need to make a decision about using an on-premise tool or a cloud-native tool. While cloud-native BI tools have lots of benefits, some privacy-minded and heavily regulated industries (like healthcare and government) still lead toward on-prem solutions

If you need an on-premise BI tool, pay careful attention to Tableau Server, Power BI Report Server, Metabase, and Sisense.

4. Version control integration (Git)

Version control in BI tools is a notoriously tricky (and frustrating) experience. 

If you’ll have developers and analysts working on new versions of dashboards while they’re simultaneously in use by business end-users, version control integration will be an important feature. It’s also vital if you’ll have multiple developers and analysts working on the same dashboard at the same time.

Looker stands out here – it has a version control system that’s fully integrated with Git, a version control system that’s widely used around the world. Git functionalities can be accessed from inside Looker, so it’s relatively easy to use.

5. Permissioning structure

Most organizations would prefer to restrict certain data to specific users, so review each BI tool’s permission structure to ensure it will meet the level of granularity that you need. 

There are various components that go into permissions structures, including row-level security (aka RLS or data security), object-level security, and role-based access controls (RBAC).

RLS is a permissioning standard that you’ll see referenced frequently when comparing the best BI tools for startups; you’ll want to make sure that all associated dashboards, reports, and analyses will appropriately enforce the RLS rules that you set.

6. Customization

Every startup (and every team within a startup) has unique workflows, needs, and preferences. You want a BI tool that can be configured in a way that will lead to wider adoption – data is a powerful tool, but only when employees have access to tools that allow them to use it within their existing workflows.

Some of the customizations you might want to implement with your BI tool include (but aren’t limited to) adjusting permissions and access controls, modifying query behavior, creating custom data connections, and modifying/white-labeling the user interface.

Sisense and Qlik are both highly customizable. Sisense in particular has a vast plugin/extension marketplace and can easily be extended through its open API architecture.

Dashboards are dead… or are they? 💀

You’ve probably heard a pundit or two proclaim that “Dashboards are dead!”

And while modern data analytics and BI programs have evolved past dashboards in many (many) ways, saying that they’re completely obsolete feels a tad hyperbolic. They still have a time and a place, for now. 

The whole “dashboards are dead” concept highlights some interesting changes in the modern business landscape, though:

  • Dashboards aren’t the only way to communicate (and use) data. 
  • Organizations want to go beyond insights; they want to use data to drive action.
  • New tools and technologies make it possible to do a ton of cool stuff with data. These new additions to the modern data stack do a better job of meeting the needs of regular business users, too.

And while the BI tools that we’ve reviewed have their differences, each one still produces the same end product: a dashboard, report, or other visualization. 

Unfortunately, dashboards don’t meet most people where they are (or where they want to be). 

The majority of operations-focused users would prefer to interact with data in an environment that they understand, like within a spreadsheet or inside of their favorite SaaS tools. This hasn’t always been easy to achieve, but a new class of reverse ETL tools are changing the game. These tools give businesses the benefits of BI (e.g., accessible and searchable data, standardized data definitions, user access controls, and more) inside the tools they already know and love.

So, maybe dashboards aren’t dead quite yet, but their role in data analytics and BI is certainly changing… and we’re here for it 🙌. 

That’s why AirOps is building something exciting that will help analytics teams support and empower business end-users to operationalize their data and dream beyond dashboards. What does that mean exactly? Find out more and get started ⬇️

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