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What is a BI tool? Which BI tool is best for your organization? Which criteria should be kept in mind while comparing the different BI tools?
Business intelligence (BI) tools transform the unprocessed data into meaningful and actionable insight. BI tools analyze the data and convert them into a presentable and analytical data set in the form of reports, dashboards, etc.
By merging the extensive number of knowledge sets from the different BI tools (i.e., from your current BI tool to different analytical software), you will be able to choose the best for your organization.
If you are researching suitable BI tools for your organization, keep these points in mind:
- Connectivity of the data: It is very important to have proper connectivity of BI to your system to access the data and to analyze the data.
- Visualization of the data: When it comes to reporting data, visualization is the primary thing for any organization. The data should be clear and inherent to deliver the clear potential out of it.
- Analysis of data: Once all the data is merged and cleaned up in one place, data analysis helps to understand the data relationships, Data Quality, and data accuracy, which is critical to the Data Management phase of BI.
Now, let’s discuss the pros and cons of some different BI tools in detail.
Power BI is a business analytics service by Microsoft, to visualize, analyze, and handle reporting of data. It also helps to create attractive and intellectual data.
Pros of Power BI
- You can easily upload data in Power BI just by maintaining data in an Excel sheet, or you can import data from the web.
- It is not that technical and can be used by anyone.
- With the help of Power BI, you can have a clear vision of the Excel data in the form of a dashboard or reports.
- After making the reports and dashboards in Power BI, you can transfer those reports to another person by inserting a link directly to the website.
- There are a wide range of visuals and graphics readily available in the Power BI tool.
- The Power BI Desktop version is free of cost.
Cons of Power BI
- Power BI is not that technical to use, but at some point, you may need a Power BI expert.
- A Power BI Pro plan costs $9.99/user/month, but the Premium version of it is a bit expensive.
- You must have a Microsoft environment or license to work on it.
Tableau is another business intelligence tool that helps in converting raw data into a simplified and clear format in the form of a dashboard. Tableau Desktop has a rich feature set and allows you to code and customize reports.
The best features of Tableau software are:
- Data blending
- Real-time analysis
- Collaboration of data
Pros of Tableau
- Tableau is a user-friendly BI tool.
- It has good API document support.
- It is used to create interactive dashboards from raw data that is in the form of spreadsheets, databases, and web services.
- Tableau software imports data of all sizes.
Cons of Tableau
- Users cannot import new visuals in Tableau; it can only be recreated.
- Unlike other BI tools, Tableau can only do reporting.
Domo is a mobile, cloud-based business intelligence platform that can help you view all your data sets in one place that can be turned into workflows to get better results. Domo has been popular for its appealing and scalable visualizations. It simplifies the extract, transform, load (ETL) process so users do not need SQL training to explore and manipulate data.
Pros of Domo
- Domo has flexibility in merging data from different sources into one place.
- Domo connects with all cloud storage, such as AWS, Azure, Google Cloud, and Box.
- In this tool you can send the raw data from a third-party platform and do the rest of the ETL in Domo, including transforming data and adding columns.
Cons of Domo
- In Domo, you cannot publish dashboards and as they have 1,000 different connectors, many consumers find it difficult to use.
Business intelligence tools can be a flexible and powerful resource for any organization. The most important factors in choosing the best BI tool for your organization can be the environment, data volume, and scalability you may require in the long run.