The Business Intelligence (BI) tool has become a cornerstone in modern data analysis by transcending the limitations of traditional methods like Excel and databases.

With plenty of options, selecting the right BI tool is crucial for unlocking the full potential of your organization's data. In this blog, we will explore some popular BI tools, their features, and key considerations to help you make an informed decision.

Here are some of the leading tools at the forefront of our discussion.

• Power BI 
• Tableau
• Qlik Sense
• SAP BI
• Apache SuperSet

Key Considerations for Choosing the Ideal BI Tool

1. Business Objectives 

Your selected BI tool must align with your business objectives and user expertise:

• Identify the specific goals and outcomes you want to achieve from the BI tool. It could be improving sales, optimizing operations, or enhancing competitive insights. 
• Be sure to also assess the technical proficiency of your users and choose a BI tool that matches the skill level of your team to achieve optimal utilization and efficiency.

After solidifying the objectives, dive into the additional considerations explained below to craft your ultimate decision.

2. Factors Related to Installation

When choosing the BI tool from an installation and deployment perspective, various factors come into play. A selection of these considerations is outlined in the table below.

Based on these points, we can summarise that:

• Smaller businesses might prefer user-friendly options like PowerBI or Qlik Sense. 
• Larger enterprises with extensive IT support might opt for Tableau or SAP BI for their comprehensive features. 
• Open-source enthusiasts might find Apache Superset appealing, but it requires a solid understanding of software deployment.‍

3. Ease of Use & Learning Curve 

To ensure widespread adoption within your organization, we must choose the BI tool that prioritizes ease of use and has a manageable learning curve. 

• Power BI and Tableau offer user-friendly interfaces, making them accessible to a wide range of users, with moderate learning curves.
• SAP BI is ideal for organizations already familiar with SAP products, leveraging existing expertise for seamless integration.
• Superset and Qlik Sense provide a balanced approach, accommodating users with different levels of technical proficiency while ensuring accessibility and usability.

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4. Integration with Existing Infrastructure

You must also consider how well the BI tool aligns with existing IT infrastructure, applications, and databases:

Power BI: 

Integrates well with Microsoft products, providing seamless connectivity and robust integration. It is well-suited for businesses leveraging Microsoft technologies.

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Tableau:

It’s a leading BI and data visualization tool with robust integration capabilities. Like many other BI platforms, it also supports a wide range of data sources, Cloud Platforms, and big data techs like Spark and Hadoop. This makes it suitable for organizations with a diverse tech stack. Learn More

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SAP BI:

It integrates well with SAP products. For third-party applications, Business Connector is used for integration. It can be challenging and requires additional configuration. Best suited for organizations that are heavily invested in SAP products.

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Apache Superset:

Apache Superset Provides integration options with a wide range of system techs due to open source and active community support. However additional setup and configuration must be done first for specific technologies. Thus, it would be wise to use this for small-scale businesses as using it for a large organization can become a very complex & tedious task.

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Qlik Sense:

Qlik Sense is known for its strong integration capabilities and real-time data analysis. Much like Tableau, it also seamlessly connects with various data sources, big data techs like Hadoop and Spark, and major cloud platforms like GCP, AWS, and Azure. Learn More

5. Cost Estimation 

BI platforms can vary significantly in their pricing models and associated costs. So, you need to evaluate costs against your current and future usage and team size. Here, I’ve mentioned some key points to consider when comparing BI tools with a focus on budget constraints:

• If an organization possesses the expertise to manage its cloud infrastructure and has a dedicated team to oversee resource scaling and monitoring, Apache Superset stands out as an excellent choice. This minimizes your licensing costs.
• However, if building a cloud infrastructure isn't your preference and you need a Software as a Service (SaaS) solution, Power BI Premium could be suitable for small teams focused on analysis.
• SAP BI presents a viable option for large organizations needing customized pricing plans tailored to specific requirements. 
• Alternatively, if you require both cloud and on-premise options, Qlik Sense and Tableau offer versatile solutions, catering well to the needs of small and medium-sized businesses.

Summary

So, in a nutshell, when choosing a BI tool, carefully assess your organization's individual needs, technical infrastructure, budget limitations, and technical proficiency. Each tool has its strengths, so tailor your choice to match your specific requirements, enabling you to maximize your data's potential.

References:

1. Power BI
   https://learn.microsoft.com/en-us/power-bi/connect-data/desktop-quickstart-connect-to-data
   https://community.fabric.microsoft.com/t5/Microsoft-Power-BI-Community/ct-p/powerbi
   https://powerbi.microsoft.com/en-us/pricing/
2. Tableau
   https://help.tableau.com/current/pro/desktop/en-us/basicconnectoverview.htm
   https://www.tableau.com/blog/community
   https://www.tableau.com/pricing/teams-orgs
3. SAP BI
   https://www.sap.com/india/products/technology-platform/cloud-analytics/pricing.html
4. Qlik Sense
   https://www.qlik.com/us/products/data-sources?category=ProductOrServiceQlikSense
   https://www.qlik.com/us/pricing
5. Apache Superset
   https://superset.apache.org/docs/databases/installing-database-drivers/