Data analytics might be the closest thing we have to fortune telling in modern business, and a quality embedded analytics tool can give your company a powerful edge. Organizations look to statistical trends to anticipate future outcomes and prepare for them.
Business intelligence (BI) tools are the answer. We look to these software-as-a-service (SaaS) tools to help us turn the noisy data into something from which we can learn and benefit. The good news is, many of these tools give us a glimpse into the future via embedded analytics.
ALSO READ: What is Embedded Analytics?
Top embedded analytics tools
Microsoft Power BI: Best for security/compliance
Pros
Cons
White labeling: Power BI Embedded allows businesses to white-label its analytics so they can provide customer-facing dashboards and analytics in their applications without revealing the underlying technology.
Integration with Microsoft Azure
Row-level security: Data can be filtered and restricted at the row level based on user roles or other criteria.
Monitoring and automation with REST APIs
Investment in cybersecurity: Microsoft’s significant annual investment in cybersecurity research and development ensures Power BI Embedded benefits from the latest security advancements and best practices.
Dedicated security experts: Microsoft employs over 3,500 security experts who are dedicated to data security and privacy.
Power BI Pro: $9.99/user/month
Power BI Premium: $20/user/month OR $4,995/capacity/month
Microsoft Power BI is a good bet if you’re looking at embedded analytics through the lens of security and compliance.
It checks all the right boxes for keeping data secure, meeting a whole host of compliance standards like ISO 27001 and GDPR, which are crucial for any business serious about data protection. But the real kicker is how Power BI integrates with Azure Active Directory, giving you a straightforward way to manage who gets to see what data. Plus, with its data encryption, you know your data is protected both when it’s stored and when it’s on the move. It’s these thoughtful, user-centric security features that make Power BI a go-to for businesses that need their analytics to be as secure as they are insightful.
We’ll start with Microsoft’s proprietary solution: Power BI. Because it’s built by Microsoft, it offers all of the same business-focused cybersecurity features as other Microsoft products. Organizations that choose to use Office 365 for improved file security, for example, will likely find a lot to love about Power BI, especially internal use.
Power BI also features an “analytics playground,” where functionality and features can be test driven, and where updates can be previewed ahead of full deployment.
Qlik Sense: Best for customizable integrations
Pros
Cons
Associative engine: Associative engine technology allows users to explore data and uncover relationships without needing pre-defined metrics.
Custom and embedded analytics: Qlik Sense supports tailored analytics that can be directly embedded into applications or platforms.
Integration with many data sources
High performance SaaS and hybrid cloud platform: Qlik Sense on Qlik Cloud offers flexibility with hybrid deployment options across public cloud, private cloud, and on-premises.
AI-powered analytics: AI-generated insights include automated data preparation, and predictive analytics.
Free trial available
Qlik Sense Business: $30/user/month
Qlik Sense Enterprise SaaS: Contact Qlik Sense for a customized quote
Qlik Sense stands out as a top-tier choice when customization and integration are the name of the game. It’s designed with the flexibility to fit snugly into a variety of applications and processes, which is a big win for any business looking to tailor its analytics tools to its unique needs.
Qlik Sense’s open APIs are a game-changer, allowing for seamless integration with existing systems and enabling a level of customization that’s hard to find elsewhere. This means you can mold and shape Qlik Sense to work just how you need it to, whether that’s integrating with complex IT infrastructures or plugging into bespoke software solutions. It’s this adaptability that sets Qlik Sense apart, making it a smart pick for businesses that want their analytics to be as nimble and responsive as they are.
Qlik Sense is heavily focused on providing flexibility and customizability to dev teams who wish to implement it. First and foremost, it supports an open-source library to facilitate easier integrations across a multitude of environments.
It also provides numerous automation options, so product teams can integrate analytics tools directly into their data life cycles. DevOps teams can leverage this to improve their ability to provide seamless user experiences.
Powered by Looker: Best for data modeling
Pros
Cons
LookML: Looker’s proprietary LookML is a SQL-based modeling language that centralizes business rule definitions for consistent and governed data.
Integration with Looker Studio: Users can connect to Looker’s semantic model and utilize Looker Studio unified data analysis.
Looker (Google Cloud Core): Built on Google Cloud infrastructure, Looker integrates with the Google Cloud service portfolio.
Enterprise-Class Business Intelligence: Looker streamlines report and dashboard creation.
Real-time data views
Starting at $20,000
Contact Google for exact pricing.
Powered by Looker is a powerhouse when it comes to turning complex data into actionable insights, thanks to its modeling layer, LookML.
With LookML, businesses can define and manage their data logic directly, creating a single source of truth that everyone in the organization can tap into. This means that your data models are consistent, reusable, and extendable, which is a big plus for efficiency.
Looker’s approach to data modeling focuses on making sure the data serves the business logic, not the other way around.
Powered by Looker is a Google Cloud product that does for BI data lineage what Google Docs did for document editing. It provides a way to track changes and review the history of the database.
The app itself is web-native, and features a web-native interface, regardless of where it’s embedded. This makes it more user friendly to lay professionals. Where it really shines is what it offers data science teams.
Tableau: Best for data visualization
Pros
Cons
Informative dashboards: Tableau Dashboards combine various visual objects, images, and text to offer a comprehensive view of data.
Supports numerous data sources: Tableau can connect to a vast array of data sources, from local files to cloud data, and supports various data connections like Google Analytics, Salesforce, and SQL Server.
Connectivity with live and in-memory data
Provides great security: The platform emphasizes data and user security with authentication and authorization mechanisms, integration with other security protocols, and features like row-level filtering.
Easy collaboration, sharing, and real-time feedback
Excellent mobile Version
Tableau Viewer: $15/user/month
Tableau Explorer: $40/user/month
Tableau Creator: $70/user/month
Tableau’s strength lies in its intuitive design capabilities that allow users to create complex charts and graphs with ease, making data analysis an art form.
The tool’s drag-and-drop interface is a standout feature, inviting users of all skill levels to explore data and uncover insights without the steep learning curve often associated with advanced analytics. This user-friendly approach, combined with the ability to handle vast amounts of data, makes Tableau a top pick for organizations that emphasize the ability to visualize and understand data quickly and effectively.
True to its brand name, Tableau offers some of the smoothest, most aesthetically pleasing analytics options from the perspective of end users. Built with external embedded implementations in mind, Tableau can power a web page, web portal, or external-facing app with equal ease and simplicity.
The tool can be white labeled, further indicating its intended use as the analytics engine for apps built by different brands.
As for external users, they get a variety of customization options, all with minimal complexity. Most visualizations can be created and edited with drag-and-drop tools, so users can focus on the key performance indicators (KPIs) they benefit from most.
Domo Everywhere: Best for simplicity
Pros
Cons
Domo data experience platform: A cloud-native platform emphasizing speed, visibility, and action, Domo offers intuitive experiences underpinned by AI, data science, and a secure data foundation.
App creation tools: Domo provides both low-code and pro-code tools for creating business applications.
Data integration: Domo can connect to over 1,000+ data sources.
Self-serve analytics: Users can create their own reports and set up data alerts for real-time insights.
Data science and machine learning: Users can build automated models that highlight relevant data and surface insights.
Governance and security: Features include user permissions, monitoring, built-in certification workflows, and row-level data security.
Standard: $83 user/month
Professional: $160 user/month
Enterprise: $190 user/month
Domo excels at delivering insights without complexity, making it a favorite for businesses that want to democratize data across their teams. It’s simple to use and straightforward to deploy.
The platform is designed with a clean, user-friendly interface that strips away the intimidation factor often associated with data analytics. The ease with which users can create dashboards and share insights makes Domo Everywhere a smart choice for organizations that value getting to the heart of their data with minimal barriers. It’s this simplicity and clarity that make Domo Everywhere stand out for companies looking to embed analytics directly into their workflows without the need for deep technical expertise.
Domo as a stand-alone business intelligence solution has been available for a while, but its embedded version, Domo Everywhere, is a bit more recent. Don’t expect a heavily pared-down version though, as it still brings a full suite of features to the table.
Like Tableau, Domo Everywhere offers a visually appealing user interface (UI) experience and white label presentation. It also provides external users with a high level of flexibility to build the dashboards and visualizations they want. Almost all of its functionality is self-service, meaning users can adjust and customize as needed, without having to get technical support.
Dundas BI: Best for multiple businesses
Pros
Cons
Unified Business Intelligence Platform: Dundas BI offers a single, unified platform for data visualization, reporting, and analytics.
Drag-and-Drop Interface: Users can easily design dashboards, reports, and scorecards using a drag-and-drop interface.
Customizable Visualizations: Dundas BI provides a wide range of customizable data visualizations.
Data Integration: The platform supports integration with a variety of data sources, including databases, web services, Excel, and more.
Self-Service Analytics: Dundas BI empowers users to explore and analyze data on their own, without relying on IT.
Starting from $2,500.
Contact Dundas BI for a customized quote.
Dundas BI is a great option for organizations that operate across multiple business units or need to cater to a variety of clients. Its multi-tenancy support allows different groups or clients to access personalized dashboards and reports while maintaining a centralized management system. This means you can offer a tailored analytics experience to different users without compromising on control or security.
Moreover, Dundas BI’s flexibility in design and open APIs means it can be deeply integrated and customized to match the branding and unique analytical needs of each business unit or client. Whether it’s for internal departments with their own data priorities or external clients with distinct branding requirements, Dundas BI delivers a cohesive, yet distinct, analytics experience.
Where the previous BI tools focused on singular deployments (to an internal organization or into a host app that faces external users), Dundas BI is aimed at “multi-tenant” use cases. Whether the host needs it housed on-premises or is deploying to the cloud, Dundas BI offers an analytics engine for those who need to power a variety of apps, platforms, and websites.
The multi-tenant architecture makes it easy for instances and deployments to be isolated via a virtual private cloud. The separation improves security, restricts access, and provides improved control to the team managing the host environment.
Embedding BI analytics tools
We actually benefit from embedded analytics tools all the time — whenever we see the engagement metrics of a social post or use a finance app to see where all of our hard-earned cash is going.
The issue with these examples is that the analytics are all native to the app you’re using, meaning the data and the insights are trapped therein.
Standard BI tools suffer from similar drawbacks. Sure, you can dump massive data piles into the hopper, and some fun graphs will come out the other end. But, it can make it difficult to provide access or disseminate the important information at scale, without everyone getting a license to the expensive BI app, that is.
It’s quite the bottleneck for organizations internally. It becomes even more of an obstacle when you want to offer those data insights to external users, though.
Wise BI brands have realized this and have taken steps to enable users to integrate the analytics into other platforms, apps, and dashboards.
Turning analytics inside-out
Whatever the industry, intended use, or other circumstance, embedded business intelligence has two primary uses: internal and external. Using embedded analytics internally provides internal staff with access to the data and related insights. External implementation offers BI functionality to customers, clients, and others using your software.
The advantage in both cases is providing a “native” analytics tool to users, without having to cook one up yourself.
The internal use case, often referred to as “user owns data,” allows teams to integrate the analytics into the software they are already using.
External use cases, known as “app owns data,” are primarily a “white label” situation, where brands embed the analytics in their applications or platforms. This allows outside users and clientele to leverage data insights while using the product by placing the burden for building, maintaining, and powering those automations on the BI vendor.
We mention this because, for one, it helps to illustrate who can benefit from embedded analytics. It also helps us break up the available options into those best for internal or external use.
Methodology
At TechnologyAdvice, we assess a wide range of factors before selecting our top choices for a given category. To make our selections, we rely on our extensive research, product information, vendor websites, competitor research and first-hand experience. We then consider what makes a solution best for customer-specific needs.
For our best embedded analytics tools list, we looked at 25 options before whittling them down to the six that cover all the bases for a quality embedded analytics solutions. We looked at features including security, compliance, ease of use, reporting capabilities, integrations, pricing, ease of setup, and more.
Choosing the best BI integration solution
Large ticket software solutions like this can be difficult to shop for due to technical knowledge gaps. The ones who can evaluate the viability of a vendor aren’t usually the ones who sign the contract, and vice versa. Ensure you have every team represented in any software purchase to help minimize surprises.
Like any online shopping experience, don’t be afraid to compare different options, ask questions, and dig deep into the research. Most importantly, be sure to question any claim of “one size fits all,” as no tool can cover every use case.
Hopefully, the above picks give you a starting point for your selection process. If you’re still in need of guidance and insight, check out our Business Intelligence Software Buyer’s Guide.
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FAQ: Embedded analytics
Embedded analytics allow businesses to create custom analytical profiles of any aspect of their business. That data can then be used internally or externally to aid in a myriad of opportunities.
Embedded analytics tools can help a company gain competitive advantage, enable data-driven decision-making, identify upsell opportunities, and create a pleasing analytical experience for its clients.
