Which is better PowerBi & Tableau for Business Analysis

Tableau and Power BI are two of the most popular and powerful data visualization and business intelligence tools in the market. They enable users to connect to various data sources, analyse and explore data, and create interactive dashboards and reports. However, they also have some differences and similarities in terms of features, performance, pricing, and compatibility.

Choosing between Tableau and Power BI for business development can be a challenging decision, as both tools have their own strengths and weaknesses. There is no definitive answer to which one to use between Tableau and Power BI for a business developer as it depends on various factors, such as the data source, the complexity of the analysis, the performance, the preference, and the skill level of the developer.

In this article, I will compare and contrast Tableau and Power BI based on these aspects and help you decide which one is more suitable for your business development needs.

• Tableau provides faster and better performance, including when handling bulk data. On the other hand, Power BI provides fast and good performance but only when working with low volumes of data but, it performs slower when handling bulk data.
• Tableau has a wider range of chart types and visualization options than Power BI, such as line charts, bar charts, maps, scatter plots, and many more. Power BI has fewer chart types and visualization options, but it allows users to create custom visuals using R or Python.
• Tableau has a simpler and more intuitive interface than Power BI, as it uses plain English words and a clear syntax. Power BI has a more complex and less intuitive interface, as it uses various functions and operators that require a deeper understanding of the data model and the evaluation context.
• Tableau is more expensive than Power BI, as it charges per user per month for its products. Power BI is cheaper than Tableau, as it offers a free version for individual users and a low-cost version for small businesses.
• Tableau is more compatible with various data sources than Power BI, as it can connect to databases, spreadsheets, big data platforms, and cloud services. Power BI is less compatible with various data sources than Tableau, as it has some limitations and restrictions when connecting to certain data sources.
• Tableau is expensive when compared to Power BI. The Tableau Creator costs $70/month/user. The yearly subscription to Tableau Pro comes to over $1000. Power BI is affordable compared to Tableau. The yearly subscription to the Power BI Pro version will be around USD 100.

There are many common functions that can be used in Tableau and Power BI for business intelligence analysis, depending on the data source, the complexity of the calculation, the performance, and the preference of the developer. Some of the most common and useful functions are Aggregation functions (SUM, COUNT, AVERAGE, MIN, MAX, etc.), Logical functions (TRUE or FALSE value, IF, AND, OR, NOT, etc.), Date and time functions (DATEADD, DATEDIFF, DATEPART, DATETRUNC, NOW, TODAY, etc.), String functions (LEFT, RIGHT, MID, LEN, FIND, REPLACE, TRIM, etc.), Statistical functions (MEDIAN, MODE, STDEV, VAR, CORR, COVAR, etc.)

Expression Language:

Here, I would like to talk about Expression languages used in both the tools which are Level of Detail (LOD) Expression and Data Analysis Expressions (DAX) Query respectively used for Tableau and PowerBI. DAX queries are statements that return a table of data using DAX syntax and functions. Tableau has LOD, which is simpler and more intuitive than DAX, but also less powerful and flexible. Both the tool has similar functions, such as CALCULATE, FILTER, and SUMMARIZE.

• The EVALUATE function can run a DAX query and return a table of data as a result. You can use this function in tools such as DAX Studio or SQL Server Management Studio to test and debug your DAX formulas, or to extract data from your model for further analysis.

DAX: To calculate the average sales per product category and region, you can use the following DAX statement:

Average Sales by Category and Region = AVERAGEX (SUMMARIZE (Sales,Products[Category],Regions[Region],"Total Sales", SUM ( Sales[SalesAmount] )),[Total Sales])        

• The CALCULATETABLE function can apply filters to a table and return another table as a result. You can use this function in measures or calculated columns to create dynamic tables based on user selections or other criteria.
• The FILTER function can return a subset of rows from a table that meets a certain condition. You can use this function as an argument for other functions, such as CALCULATE, SUMX, AVERAGEX, etc., to perform calculations or aggregations on the filtered table.

LOD expressions are specific to Tableau, while DAX is a standard language that can be used in other Microsoft products, such as Power BI, Excel, SQL Server Analysis Services, etc.

Therefore, depending on the situation and the goal of the developer, LOD or DAX may be more suitable or preferable. For example, if the developer wants to create a simple calculation that aggregates a measure at a different level of detail than the visualization, then LOD may be easier and faster to use. However, if the developer wants to create a complex calculation that involves multiple tables, filters, variables, or logic, then DAX may be more capable and flexible to use.

I hope this helps you understand the differences and similarities between LOD and DAX for the BI developer. Kindly ping me to increase my knowledge on this topic.

Thank You,

Jyoti bisht