Self-service BI tools 2024: comparison for companies

What are self-service BI tools?

What are the benefits of self-service BI tools for your company?

Self-service BI tools offer companies and their employees concrete benefits such as speed, accuracy, cost efficiency, productivity, increased autonomy, optimized workflows and more effective teamwork.

Benefits for companies:

• Speed and agility: Companies can respond more quickly to market changes because users are able to analyze data in real time and gain immediately actionable insights for their individual needs.
• Cost efficiency: Reducing dependence on the IT department (data analysts) for data queries leads to more efficient use of resources and lower operating costs.
• Improved competitiveness: With quick access to relevant data, companies can identify environmental changes and trends more quickly and make strategic decisions.

Benefits for employees/users:

• Increased autonomy: Employees can perform data analyses independently, which increases their job satisfaction and engagement. They are no longer dependent on the IT department to create reports or prepare data.
• Current and secure data: Users can access current and secure data, which reduces uncertainty and increases trust in the data. This leads to better business results and minimizes the risk of errors.
• Collaboration and transparency: Teams can access common data sources and share their analyses, which improves collaboration and greatly improves the internal flow of information.

What functions should you look for in self-service BI tools?

Self-service BI tools should be user-friendly, offer comprehensive data connectivity and integration, enable customizable dashboards and reports, support AI and machine learning integration, meet high security and compliance standards, and be scalable and support the .

• Ease of use
• Data connectivity and integration
• Customizable dashboards and reports
• AI and machine learning integration
• Security and compliance
• Scalability

What makes a BI tool user-friendly?

A user-friendly BI tool offers an intuitive and easy-to-use interface. The balance between functionality and simplicity is crucial here.

• Intuitive user interface: Clear and structured so that users can find their way around quickly.
• Drag-and-drop functionality: Easily drag data fields into analyses or reports.
• Clear menu navigation: Logical and easy navigation to the functions required.
• Customizable user interface: Ability to customize the interface.
• Automation of routine tasks: Functions for automating regular tasks.
• Availability on different devices and as a cloud solution: Ensuring use on desktops, tablets, smartphones and, if required, via the cloud.

Why are customizable and interactive dashboards essential in BI tools?

Customizable and interactive dashboards allow users to design analyses and visualizations according to their specific needs, increasing the relevance and efficiency of data analysis.

• Personalized insights: Users can configure dashboards according to their individual requirements to highlight the data that is most important to them.
• Flexibility: Customizable dashboards allow you to combine different visualization types and data sources to gain comprehensive insights.
• Data freshness: Connecting to the data sources allows users to always have access to up-to-date data, increasing the accuracy and relevance of the dashboards.
• Easy updates: Users can easily update dashboards to adapt to new business requirements and data changes.

How important is the integration of artificial intelligence (AI) and machine learning (ML) in BI tools?

AI and ML are currently the biggest technological revolution since the Internet. Although these technologies are still in their infancy, they are already changing the way companies use data and make decisions. Companies that miss this development run the risk of quickly being left behind.

A BI tool with AI and ML functions offers the following advantages:

• Predictive models: By analyzing historical data, future trends and events can be predicted. The analysis parameters can be determined with the utmost precision in order to obtain the most relevant results.
• Anomaly detection: Unusual patterns and outliers in the data are automatically detected, saving a lot of time and reducing the risk of incorrect data.
• Increased efficiency: Routine tasks can be automated, saving time and increasing the accuracy of analyses. This allows employees to focus on more strategically important tasks.
• Individualized data work: AI and ML are extremely adaptable and customizable, so they can be tailored precisely to the specific needs of a company.
• Continuous development: New integrations for services and programs are added every day. Those who are at the forefront here can develop sustainable competitive advantages and use the flexibility to respond quickly to new requirements.

How do security and compliance influence the selection of BI tools?

Security and compliance are crucial factors when selecting BI tools as they ensure the protection of sensitive data and regulatory compliance.

A BI tool must offer robust security features such as data encryption, user authentication and access control to ensure that only authorized users can access sensitive data and GDPR is adhered to.

Why is scalability important for BI tools?

Scalability is crucial for BI tools as it ensures that the tool can keep pace with the growth of the company and quickly capture new business processes.

Scalability is especially important when entering new business areas, products and markets. Companies can integrate these new elements quickly and efficiently into their data processes, providing flexibility and long-term investment security.

What are the leading self-service BI tools in 2024?

We have analyzed the 9 leading BI software tools for you, including:
Qlik, Microsoft Fabric, Power BI, Tableau, Looker, Domo, Sisense, SAP Analytical Cloud and IBM Cognos Analytics.

What is Qlik?

Qlik is a leading data integration and analytics platform developed by QlikTech International AB. With millions of users worldwide, Qlik provides advanced analytics tools and enables companies to gain deeper insights into their data. Qlik is particularly known for its associative engine, which allows users to connect data from different sources and analyze it intuitively. This engine enables flexible data linking, allowing users to freely navigate between different data sets and discover relationships without being limited to predefined analysis paths.

Target group and application area: Companies of all sizes and users at all levels, from beginners to advanced users, who want to integrate extensive data from different sources and gain deeper insights.

Data integration with Qlik

Functions: Qlik offers powerful functions for integrating various data sources, including cloud data sources (e.g. AWS, Google Cloud), on-premise databases (e.g. Oracle, SQL Server) and SaaS applications (e.g. Salesforce, SAP). The platform supports a wide range of data formats and offers native connectors to many data sources.

Benefits: This comprehensive data integration enables companies to seamlessly combine and centrally manage data from different systems and formats. This enables companies to get a complete picture of their data landscape and make informed decisions.

Data analysis with Qlik

Features: Qlik supports both ad hoc analysis and pre-built analysis models. Users can create interactive visualizations, perform complex data queries and access data in real time. The associative engine allows users to freely navigate through the data and intuitively discover connections between different data sets.

Benefits: These powerful analytical tools enable companies to gain deeper insights into their data, discover hidden patterns and correlations, and make quick, data-driven decisions.

Dashboard functionality (reporting) in Qlik

Features: Qlik enables the creation of highly customizable and interactive dashboards. Users can use various visualization types such as charts, maps, and tables to present their data clearly.

Benefits: Qlik's interactive dashboards are easily customizable and allow users to design their reports according to their specific needs. This facilitates the rapid detection of trends and anomalies and supports the effective communication of findings within the company.

AI and ML with Qlik

Qlik integrates basic AI and ML functions, including pattern recognition, anomaly detection and predictive analytics. Enables highly individualized insights into your own data.

What is Microsoft Fabric?

Microsoft Fabric is an all-in-one SaaS data platform developed by Microsoft that enables seamless integration and analysis of data. MS Fabric combines Microsoft 365 and Azure in a unified and user-friendly environment for users. Power BI is also integrated into Microsoft Fabric, but is covered separately in this article.

Target group and application area: Companies of all sizes that have already invested in the Microsoft ecosystem and need seamless integration with Microsoft 365 and Azure. Ideal for teams that want to collaborate and analyze data in real time.

Data integration with Microsoft Fabric

Features: Microsoft Fabric offers comprehensive features for integrating data sources such as Azure SQL Database, Azure Data Lake, Microsoft Dynamics 365 and external cloud services such as AWS and Google Cloud. The platform supports a wide range of data formats and offers native connectors for numerous applications.

Benefits: This deep integration enables companies to efficiently connect data from different systems and manage it centrally, creating a holistic view of the company's data.

Data analysis with Microsoft Fabric

Features: Microsoft Fabric supports ad hoc analysis, pre-built analysis models and real-time data processing. The platform offers powerful tools such as Power Query and DAX for detailed data query and analysis.

Benefits: Users can gain deep insights into their data, perform complex data queries and access up-to-date data in real time.

Dashboard functionality (reporting) in Microsoft Fabric

Features: Microsoft Fabric enables the creation of customizable and interactive dashboards with various visualization types such as charts, maps and tables. The platform is tightly integrated with Power BI and offers comprehensive dashboard and reporting capabilities.

Benefits: Users can customize dashboards to their needs and create reports efficiently and quickly. Report distribution works seamlessly across the Microsoft world.

AI and ML with Microsoft Fabric

Microsoft Fabric integrates advanced AI and ML capabilities, including Azure Machine Learning, Cognitive Services, and automation tools to support data analysis and prediction.

What is Power BI?

Power BI is a powerful business intelligence platform from Microsoft that helps companies visualize and analyze data. Power BI is known for its user-friendly interface and seamless integration with other Microsoft products such as Excel and Azure.

Target group and application area: Companies of all sizes looking for a cost-effective, user-friendly BI solution. Ideal for users who already use Microsoft products and need seamless integration.

Data integration with Power BI

Features: Power BI supports integration with a variety of data sources such as SQL Server, Excel, Azure, Google Analytics and many more. It offers native connectors to many popular cloud services and databases.

Benefits: This extensive data integration allows users to combine data from different sources and present it in a single view.

Data analysis with Power BI

Features: Power BI provides powerful tools for performing ad hoc analysis and creating ready-made analysis models. Users can create interactive visualizations and analyze data in real time. DAX (Data Analysis Expressions) and Power Query are central functions for detailed data queries.

Benefits: The powerful analysis functions enable users to gain deep insights into their data and make data-based decisions quickly and efficiently.

Dashboard functionality (reporting) in Power BI

Features: Power BI enables the creation of interactive and customizable dashboards with various visualization types such as charts, maps and tables. Users can update and share their dashboards in real time.

Benefits: Power BI's easy-to-use dashboards make it easy to visualize complex data and support effective communication of insights across the organization.

AI and ML with Power BI

Power BI integrates advanced AI and ML capabilities, including natural language query analysis, anomaly detection, and predictive modeling.

What is Tableau?

Tableau is a leading business intelligence platform developed by Tableau Software, a Salesforce company. With millions of users worldwide, Tableau provides intuitive and powerful tools for data visualization and analysis. Tableau is known for its user-friendly interface and its ability to present complex data in a clear way.

Target group and application area: Companies of all sizes and users at all levels who need a user-friendly and powerful BI solution to visualize and analyze data.

Data integration with Tableau

Features: Tableau supports integration with a variety of data sources, including SQL Server, Google BigQuery, Salesforce, Excel, Amazon Redshift, and many more. It offers native connectors for numerous cloud services and databases, enabling seamless connection of data sources.

Benefits: This extensive data integration enables companies to connect data from different sources and manage it centrally. Users can combine and analyze data from different systems in a single view.

Data analysis with Tableau

Features: Tableau offers powerful tools for performing ad hoc analysis and creating pre-built analytical models. Users can create interactive visualizations, analyze data in real time, and gain deep insights. Tableau Desktop and Tableau Prep can be used to perform detailed data queries and preparation. Tableau also supports statistical analyses such as regression analysis, confidence intervals, forecasting, clustering and distribution curves.

Advantages: The associative engine allows users to freely navigate through the data and discover hidden patterns.

Dashboard functionality (reporting) in Tableau

Features: Tableau enables the creation of highly customizable and interactive dashboards with various visualization types such as charts, maps and tables. Users can update and share their dashboards in real time, which promotes collaboration. Tableau also offers automated, intuitive and meaningful visualization suggestions to match the selected data.

Advantages: Tableau's user-friendly dashboards make it easier to visualize complex data and support the effective communication of insights within the company. This promotes rapid detection of trends and anomalies. Tableau's drag-and-drop functionality allows users to easily create and customize visualizations without requiring any programming knowledge.

AI and ML with Tableau

Tableau integrates advanced AI and ML capabilities, including natural language query analysis, anomaly detection, and predictive model building by connecting with Einstein Discovery. Tableau also offers alternative hierarchies, classifications, and dynamic table calculations.

What is Looker?

Looker is a modern business intelligence platform developed by Looker Data Sciences, a Google Cloud company. With Looker, companies can easily model, visualize and analyze data. Looker is known for its strong data modeling and seamless integration with Google Cloud.

Target audience and application area: Companies of all sizes that want to perform flexible and powerful analytics in the Google Cloud environment. Ideal for companies that need strong data modeling and integration with Google Cloud.

Data integration with Looker

Features: Looker offers comprehensive data integration capabilities, including support for SQL databases, Google BigQuery, Redshift, Snowflake, and many more. Looker uses the LookML language to define and manage data models.

Benefits: Deep integration with Google Cloud and other data sources enables companies to seamlessly connect and analyze data. This makes it easier to manage large amounts of data and promotes collaboration across different teams.

Data analysis with Looker

Features: Looker offers powerful tools for performing ad hoc analysis and creating pre-built analysis models. Users can create interactive visualizations, perform complex data queries, and access data in real-time. Looker also supports advanced analytics through LookML and custom dashboards.

Benefits: Using LookML enables users to create consistent and reusable data models that improve collaboration and efficiency.

Dashboard functionality (reporting) in Looker

Features: Looker allows you to create customizable and interactive dashboards with various visualization types such as charts, maps, and tables. Users can update and share their dashboards in real-time, which promotes collaboration. Looker also offers drag-and-drop functionality to easily create and customize reports.

Benefits: Looker's easy-to-use dashboards make it easy to visualize complex data and support effective communication of insights across the organization.

AI and ML with Looker

Looker integrates advanced AI and ML capabilities, including predictive analytics and anomaly detection through integration with Google Cloud AI services. Looker also allows users to create and implement custom machine learning models.

What is Domo?

Domo is a comprehensive business intelligence platform that enables companies to integrate, analyze and visualize data from various sources. Developed by Domo, Inc., the platform offers an all-in-one data management and analytics solution that is particularly suitable for large companies and teams. Domo supports collaboration and data communication within companies through its user-friendly and interactive tools.

Target group and application area: Large companies and teams looking for a comprehensive platform for data analysis, visualization and collaboration.

Data integration with Domo

Features: Domo offers extensive integration of data sources, including cloud services such as AWS, Google Cloud and Azure, on-premise databases such as Oracle and SQL Server, and SaaS applications such as Salesforce, Adobe Analytics and Zendesk. It supports over 1000 native connectors and also offers the ability to create your own data connections.

Benefits: This comprehensive data integration enables companies to seamlessly connect and centralize all relevant data sources, resulting in a holistic view of business data.

Data analysis with Domo

Features: Domo offers powerful analysis tools for performing ad hoc analysis, creating ready-made analysis models and using data visualizations. It supports real-time data processing and allows users to perform in-depth analysis and create interactive dashboards.

Benefits: Real-time data processing ensures that decisions are based on up-to-date information, which is particularly beneficial in fast-moving industries.

Dashboard functionality (reporting) in Domo

Features: Domo allows you to create customizable and interactive dashboards with various visualization types such as charts, maps, and tables. The drag-and-drop functionality makes it easy to create and customize dashboards. Users can update and share dashboards in real time, encouraging collaboration.

Benefits: Domo's easy-to-use dashboards make it easy to visualize complex data and support effective communication of insights across the organization.

AI and ML with Domo

Domo integrates advanced AI and ML capabilities, including predictive analytics, anomaly detection, and automated data preparation. Users can build and deploy machine learning models directly in the platform.

What is Sisense?

Sisense is a comprehensive business intelligence platform that helps companies efficiently process and analyze large amounts of data. Developed by Sisense Inc., the platform offers a user-friendly interface and powerful data integration, analysis and visualization capabilities. Sisense is particularly known for its ability to process complex data quickly and efficiently, making it an ideal solution for data-intensive companies.

Target audience and application area: Companies of all sizes that require powerful data processing and analytics capabilities, especially in data-intensive industries.

Data integration with Sisense

Features: Sisense supports integration with a wide variety of data sources, including SQL databases, NoSQL databases, cloud services such as AWS, Google Cloud and Azure, and SaaS applications such as Salesforce and Zendesk. The platform offers native connectors and API integration to seamlessly connect data.

Benefits: This comprehensive data integration enables companies to combine data from different sources and manage it centrally, creating a unified data basis for analytics.

Data analysis with Sisense

Features: Sisense offers powerful tools for performing ad hoc analyses, creating pre-built analysis models and using data visualizations. The platform uses in-chip technology to efficiently process large amounts of data and enables users to perform in-depth analysis.

Benefits: In-chip technology ensures fast query speeds and efficient data processing, which is particularly beneficial for large data sets.

Dashboard functionality (reporting) in Sisense

Features: Sisense enables the creation of highly customizable and interactive dashboards with various visualization types such as charts, maps and tables. The drag-and-drop functionality makes it easy to create and customize dashboards. Users can update and share dashboards in real time.

Benefits: Sisense's easy-to-use dashboards make it easy to visualize complex data and support effective communication of insights across the organization.

AI and ML with Sisense

Sisense integrates advanced AI and ML capabilities, including predictive analytics, anomaly detection, and automated data preparation. Users can build and deploy machine learning models directly in the platform.

What is SAP Analytics Cloud?

SAP Analytics Cloud (SAC) is a comprehensive business intelligence platform developed by SAP. It provides integrated planning, business intelligence, and predictive analytics capabilities in a single cloud environment. SAP Analytics Cloud is particularly suitable for companies that already use SAP products and require seamless integration and advanced analytics capabilities.

Target group and application area: Large companies and organizations, especially those that already use SAP products, and are looking for integrated planning and analytics as well as comprehensive data integration.

Data integration with SAP Analytics Cloud

Features: SAP Analytics Cloud supports integration with a wide range of data sources, including SAP HANA, SAP S/4HANA, SAP BW/4HANA, SQL databases, Google BigQuery, and many more. The platform offers native connectors and APIs to seamlessly connect data.

Benefits: This deep integration enables companies to centrally manage and analyze data from various SAP and non-SAP systems. This enables companies to gain consistent and comprehensive insights into their business data with a single platform.

Data analysis with SAP Analytics Cloud

Features: SAP Analytics Cloud offers powerful tools for performing ad hoc analyses, creating pre-built analytical models and using data visualizations. Users can create interactive dashboards and analyze real-time data. The platform also supports statistical evaluations and advanced analytics using machine learning.

Benefits: Companies can gain deeper insights into their data by performing comprehensive and detailed analyses. Real-time data analysis and advanced analytics capabilities support data-driven decision-making and improve operational efficiency.

Dashboard functionality (reporting) in SAP Analytics Cloud

Features: SAP Analytics Cloud enables the creation of customizable and interactive dashboards with various visualization types such as charts, maps, and tables. The platform offers drag-and-drop functionality and enables real-time updating and sharing of dashboards.

Benefits: SAP Analytics Cloud's user-friendly dashboards make it easier to visualize complex data and support the effective communication of insights within the organization. This promotes a data-driven company culture and enables teams to quickly access important information.

AI and ML with SAP Analytics Cloud

SAP Analytics Cloud integrates advanced AI and ML capabilities, including predictive analytics, anomaly detection, and automated data preparation. Users can build and deploy machine learning models directly in the platform. The platform leverages the SAP AI Foundation to develop and integrate advanced AI models.

What is IBM Cognos Analytics?

IBM Cognos Analytics is a comprehensive business intelligence platform developed by IBM. The platform provides powerful data analysis, visualization, and reporting capabilities. Cognos Analytics is known for its robust reporting and analysis capabilities as well as its ability to manage and analyze complex data structures.

Target group and application area: Large companies that require comprehensive reporting and analysis capabilities as well as robust security features.

Data integration with IBM Cognos Analytics

Features: IBM Cognos Analytics supports integration with a variety of data sources, including relational databases (e.g. SQL Server, Oracle), data warehouses (e.g. IBM Db2, Teradata) and cloud services (e.g. AWS, Microsoft Azure). The platform offers native connectors and APIs for data integration..

Benefits: This extensive data integration enables companies to connect data from different sources and manage it centrally. This facilitates uniform and consistent data analysis, which is particularly beneficial for large companies with complex data requirements.

Data analysis with IBM Cognos Analytics

Features: IBM Cognos Analytics provides powerful tools for performing ad hoc analysis and creating pre-built analysis models. Users can create interactive visualizations and access data in real time. The platform also supports advanced analytics such as predictive modeling and data exploration.

Benefits: Real-time data analysis and advanced analytics capabilities support data-driven decision-making and improve operational efficiency.

Dashboard functionality (reporting) in IBM Cognos Analytics

Features: IBM Cognos Analytics enables the creation of customizable and interactive dashboards with various visualization types such as charts, maps, and tables. Users can update and share dashboards in real time. Drag-and-drop functionality makes it easy to create and customize reports.

Benefits: IBM Cognos Analytics' easy-to-use dashboards make it easy to visualize complex data and support effective communication of insights across the organization.

AI and ML with IBM Cognos Analytics

IBM Cognos Analytics integrates advanced AI and ML capabilities, including predictive analytics, anomaly detection, and automated data preparation. Users can build and deploy machine learning models directly in the platform. The platform leverages IBM Watson to develop and integrate advanced AI models.

How do you choose the right self-service BI tool for your company?

Choosing the right self-service BI tool depends on various factors that can be derived from the specific needs and goals of your company. Here are some important criteria and questions that can help you make your decision:

What are your company's requirements for the BI tool?

To choose the right BI tool, you should first determine your specific business requirements. This includes the type and number of data sources to be integrated, ease of use for different user groups, and the ability of the tool to keep pace with the growth of your business.

• Data sources: Which data sources need to be integrated? Do you have specific requirements for cloud or on-premise data sources?
• Users: Who will use the tool? Are they technically savvy data analysts or more business users without in-depth technical knowledge?
• Scalability: How big is your business and how fast is it growing? Do you need a tool that can scale with your business?

What tool features are important to you?

Your BI tool choice should be based on the specific features you need. Consider what type of data integration, analytics capabilities, dashboard options, and AI or ML capabilities are most relevant to your business.

• Data integration: Do you need seamless integration with existing systems and applications?
• Data analytics: What type of analytics do you want to perform? Do you need ad hoc analytics, pre-built analytics models, or advanced statistical analytics?
• Dashboard functionality: How important are customizable and interactive dashboards to your users? What types of visualizations do you need?
• AI and ML: Do you want to use AI and ML capabilities to perform predictive analytics and pattern recognition?

What is your budget?

Set your budget and compare the costs of different BI tools. Consider not only the license costs, but also the ongoing costs for maintenance and support to find the best value for money.

• Cost: What is your budget for BI tools? Consider both the license costs and the ongoing costs for maintenance and support.
• Value for money: What features do you get for the price you pay? Is the tool cost-effective for your company?

How important is the usability of the BI tool?

Choose a tool that is user-friendly and minimizes the need for training. Features such as drag-and-drop can make it easier to use and increase adoption within the company.

• Usability: Is the tool intuitive and easy to use? Does it support drag-and-drop functionality and other user-friendly features?
• Training needs: How much training do your users need to use the tool effectively?

What security and compliance requirements must the BI tool meet?

Make sure the BI tool has robust security features and meets the compliance requirements of your industry. This is especially important for companies in highly regulated industries.

• Security: What security features does the tool offer? Is your data managed and stored securely?
• Compliance: Does the tool meet the regulatory requirements of your company and industry?

Conclusion: Choosing the right self-service BI tool

Choosing the right self-service BI tool is critical to the success of your data management strategy and has a significant impact on your company's efficiency and decision-making.

The BI tools presented offer a variety of features tailored to different needs and budgets. While Qlik, Power BI and Tableau are known for their ease of use and cost-effective pricing, platforms such as SAP Analytics Cloud and IBM Cognos Analytics offer comprehensive security and compliance features for large companies.

The future of BI tools lies in AI and machine learning

An important aspect when choosing a BI tool is the integration of AI and machine learning. The current boom is real and justified. Chip manufacturers are increasingly focusing on the production of AI-enabled microchips. Microsoft with Open AI, Google, Amazon, Apple and the entire BI industry are at the forefront when it comes to the development of AI and ML. Those who can take advantage of this trend will be able to increase their productivity, costs and efficiency exponentially in the long term.

Those who have not yet invested in this area should pay attention to the AI and ML capabilities and in particular to the future development of the tools when selecting their BI tool.