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Post By Admin Last Updated At 2020-06-11
Explain about Tableau Desktop?

Tableau Desktop depends on the breakthrough technology that lets you drag and drop to analyze data. You can associate with information in couple of clicks, then visualize and create attractive dashboards. You'll utilize Tableau Desktop to build  a simple product data, map product sales and profitability  by region, fabricate a dashboard of your discoveries, and afterwards make a story to exhibit. At that point, you will share your discoveries on the web so that remote colleagues can look at Explain about Tableau Desktop.

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Dimensions and Measures:

When you associate with an information source. Tableau allocates each field in the information source as playing one of two possible roles : dimension  or measure.

When you initially associate with an information source, Tableau assigns any fields that contain discrete all out data (for instance, fields where the qualities strings or Boolean values) to the Dimensions area in the Data pane.

If you snap and drag a field from the Dimensions area to Rows or Columns. Tableau creates row or column headers.

Tableau desktop

Any field you drag from the Dimension range will be at first be discrete. When you add it to a view, with a blue back ground. Thus, it may be anything but difficult to accept foundation shading demonstrates whether it is a measurement or a measure. In any case, Date dimensions and numeric dimensions can either discrete or constant, and all measures can be discrete or nonstop. A field's background color indicates demonstrates whether it is discrete (blue) or ceaseless (green).

On the off chance , If  you need to make a dimensions persistent (without first changing over it into a measure). your alternatives are restricted.  Date measurements can discrete or persistent yet are always dimensions, and with numeric dimensions. You can't change over dimensions containing strings or Boolean values.

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Tableau does not aggregate dimensions.  On the off chance,if  you need a field's values  to be aggregated, that field must be a measure. When you change  a dimensions  into a measure, Tableau will constantly provoke you to assign it a aggregation (Count, Average, and so on.).Aggregation means gathering various values (singular numbers) into a single value by, for instance, checking the quantity of individual values, averaging them, or showing the littlest individual value for any row in the data source.

Measures:

When you initially connect to a  information source, Tableau assigns any fields that contain quantitative, numerical data (that is, fields where the qualities are numbers) to the Measures area in the Data pane.

When you drag a field from the Measures area to Rows or Columns, Tableau makes a continuous axis.

Data Analytics

Tableau keeps on aggregate values for the field, because of the fact that the field is currently discrete. It is  yet a measure, and Tableau will constantly total measures. You can make the procedure one step further and change over the measure to a dimension on the off chance that you like. At exactly that point will Tableau stop aggregating its values.

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 Advantages :

Speed: This is the major advantage of tableau. It can analyses hundreds of millions of rows and gives the required answers in seconds. It is very useful when business decisions need to be taken.

Ease of use: Another most advantage of Tableau is its Ease of use. All the work in tableau is done by drag and drop. No programming skills were required. Only Microsoft Excel required for learning tableau.

 Beautiful and interactive dashboard: The dashboard of tableau very interactive. Rich visualizations created easily. Images ,web pages documents added easily which is useful for Presentation.

Recommended Audience :
Generally Tableau is not programming software require expensive programming language. Programming ideas and skill immense interest to manage the data in right way.DevelopersProject MangerData AnalystsNon-BI professionals
Prerequisites:

Its better to have a basic knowledge on analyzing and maintaining the data for implementation purpose. In practical  no Programming skills required to learn this course.  It’s good to have knowledge on use of Excel or the worksheets  to understand the entire design of Tableau. Trainers will train you if don’t have a knowledge on Excel.

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