📅 最后修改于: 2021-01-11 09:44:19 🧑 作者: Mango
最近，Tableau和Power BI都是出色的可视化工具。 Tableau已确立自己的地位，成为数据分析和BI工具的市场领导者。
Power BI是Tableau的最接近竞争对手。两种可视化工具都有其长处和特色，并且每种工具都将根据需求用于业务中。
Tableau提供了可视化工具，使公司中任何级别的所有用户都可以轻松理解数据。
Power BI为小型企业提供服务，并提供了一种易于使用的界面以及创建强大的仪表板的功能。
Tableau和Power BI两种工具均提供高级报告和可视化功能。
Tableau提供了一个强大的BI工具，可以增强所有类型的企业和组织用户的数据可视化和发现能力。 Tableau具有简单的拖放功能，用户可以快速分析关键数据。用户可以在整个企业内共享重要的见解，并在Tableau中创建创新的可视化效果和报告。
Tableau允许将仪表板嵌入到现有业务应用程序(如SharePoint)中以进行快速分析。
Power BI是基于云的分析和商业智能平台。 Power BI提供了关键组织数据的完整概述。
通过连接到用户的所有数据源，它简化了用户的数据共享和评估。它提供了可扩展的仪表板，使用户可以轻松地将各种可视化选择为蓝图，然后将数据从导航拖放到可视化中。
我们比较了Tableau和Power BI，以查看主要差异和因素，这些因素可以帮助您确定最适合自己的需求。
| Parameters | Tableau | Power BI |
|---|---|---|
| Meaning | Tableau is the data analytics and business intelligence tool for generating reports and data visualization tool with high flexibility. | Power BI is the business analytics tool to analyze the business and derive insight from it. |
| Year | Tableau was established in 2003. | Power BI was established in 2013. |
| Cost | Tableau is more expensive when it comes to large enterprise, and it paid more when connected to third party application. | Power BI is less expensive when compared to the Tableau. |
| Data visualization | Tableau is a more preferred tool when it comes to data visualization. | Power BI focused on predictive modeling and reporting. |
| Data source | Tableau has access to many database sources and servers. Ex: Text file, Excel, JSON file, Access, PDF file, Statistical file, Spatial file, etc. |
Power BI has limited access to other database and servers. Ex: Access database, SQL server database, SQL server analysis services database, IBM DB2 database, Oracle database, etc. |
| Deployment | Tableau have more flexible deployment. It available on-premises and cloud both model options. | Power BI is available as SaaS model options only. |
| User interface | Tableau has a slick user interface that enables the user to create a customized dashboard. | Power BI has a more understandable interface and much simpler to learn. Due to its simplicity and easy to use, that’s why business users prefer power BI. |
| Data capacity | Tableau works on the columnar based structure that stores unique values for each column, making it possible to fetch millions of rows. | Power BI can Handel up to 10 GB of data. For more than 10 GB, data should be in the cloud (Azure). If it is in the local database, then Power BI selects the data from the database but does not import. |
| Machine learning | Python machine learning capacities is in build with a Tableau that makes it efficient for performing machine learning operation over the datasets. | Power BI is integrated with Microsoft Azure that helps in analyzing the data and understanding the pattern of the business. |
| Performance | Tableau can handle huge data with better performance. | Power BI can handle limited data only. |
| Users | Tableau required analysts users for their analytics purpose. | Power BI required both technical and non-technical users. |
| Infrastructure | Tableau provides flexible infrastructure. | Power BI provides software as a service infrastructure. |
| Overall functionality | Tableau has excellent functionality. | Power BI has good functionality. |
| Support level | Tableau has a high support level in comparison to power BI. | Power BI has a low support level. |
| Programming tools support | Tableau integrates much better with R language as compared to power BI. | Power BI is also connected to the R language using Microsoft revaluation analytics. But it is only available for enterprises level users. |