Tableau Tutorial for Interview Questions.
This document will help you for quick preparation of important Tableau interview topics. This is a handy guide which gives you sneak peak once you prepare for the Interview.
In what order filter get executed in Tableau ?
There are several different kinds of filters in Tableau and they get executed in the following order from top to bottom.
Different Type of Filter in Tableau ?
- Extract Filter
- Data Source Filter
- Context filter
- Dimension Filter
- Measure Filter
What are the Tableau Annotation types ?
There are 3 different types.
- Mark:- That is associated with the selected mark.
- Point:- Select this option to annotate a specific point in the view.
- Area:- Select this option to annotate an area in the viz, such as a cluster of outliers or a targeted region.
Tableau computes Attribute(ATTR)
It returns a value if it is unique, else it returns *
IF MIN([dimension]) = MAX([dimension]) THEN MIN([dimension]) ELSE “*” END
Discrete vs Continuous fields
Discrete fields contain distinct values. They make headers or labels in the view and the pills are blue.
Continuous fields “form an unbroken whole”. They make an axis in the view and the pills are green.
What is Tableau bridge?
Bridge is a Windows-based program and it is client software that runs on a machine in your network. The client works in conjunction with Tableau Online to keep data sources that connect to on-premises data, which Tableau Online can’t reach directly, up to date.
What is Cube data sources?
Cube data sources are supported only for Tableau Desktop on Windows — not for the Mac. A cube data source is a data source in which hierarchies and aggregations have been created by the cube’s designer in advance.
Cubes are very powerful and can return information very quickly, often much more quickly than a relational data source. However, the reason for a cube’s speed is that all its aggregations and hierarchies are pre-built.
How many types of calculations you can use to create calculated fields in Tableau?
- Basic expressions
- Level of Detail (LOD) expressions
- Table calculations
What is Data Interpreter?
It can give you a head start when cleaning your data. It can detect things like titles, notes, footers, empty cells, and so on and bypass them to identify the actual fields and values in your data set. It can even detect additional tables and sub-tables so that you can work with a subset of your data independently of the other data.
TOTAL( ) Vs WINDOW_SUM( )
TOTAL( ) will always calculate the sum of all values in your window WINDOW_SUM( ) gives you more control over which values to include in your sum.
What is Extensions?
You add unique features to dashboards or directly integrate them with applications outside Tableau.
How clustering works?
Cluster analysis partitions the marks in the view into clusters, where the marks within each cluster are more similar to one another than they are to marks in other clusters. Tableau distinguishes clusters using color.
Tableau uses the k-means algorithm for clustering. For a given number of clusters k, the algorithm partitions the data into k clusters. Each cluster has a center (centroid) that is the mean value of all the points in that cluster. K-means locates centers through an iterative procedure that minimizes distances between individual points in a cluster and the cluster center. In Tableau, you can specify a desired number of clusters, or have Tableau test different values of k and suggest an optimal number of clusters.
What are the types of Trend Line Model ?
The model types which are available for trend lines are :
Linear, Logarithmic, Exponential, Power, & Polynomial.
What is Forecast Model?
You can add a forecast to a view when there is at least one date dimension and one measure in the view. If you’re interested in predictive modeling, also available in Tableau
Forecast >Show Forecast, or choose Analysis >Forecast >Show Forecast.
These models capture the evolving trend or seasonality of your data and extrapolate them into the future. Forecasting is fully automatic, yet configurable. Many forecast results can become fields in your visualizations.
When a forecast is showing, future values for the measure are shown next to the actual values.
Use the drop down to specify whether Tableau selects what it determines to be the best of all models (Automatic), the best of those with no seasonal component (Automatic without seasonality), or the model you specify (Custom).
When you choose the Custom option, two new fields appear in the Forecast Options dialog box, which you use to specify the trend and season characteristics for your model:
The choices are the same for both fields:
None: When you select None for Trend, the model does not assess the data for trend. When you select None for Season, the model does not assess the data for seasonality.
Additive: An additive model is one in which the combined effect of several independent factors is the sum of the isolated effects of each factor. You can assess the data in your view for additive trend, additive seasonality, or both.
Multiplicative : A multiplicative model is one in which the combined effect of several independent factors is the product of the isolated effects of each factor. You can assess the data in your view for multiplicative trend, multiplicative seasonality, or both.
What are Constraints on Multiplicative Models?
- You cannot use a multiplicative model when the measure to be forecast has one or more values that are less than or equal to zero, or even when some of the data points are too close to zero, relative to other data points.
- You cannot specify a model with multiplicative trend and additive season because the result may be numerically unstable
What are the tips to be followed to work with your Data ?
Data can be organized in various ways. To take advantage of Tableau Desktop, Tableau recommends that you connect to data that is formatted for analysis. Specifically, data that is: as granular as possible rather than aggregated (such as daily weather data rather than monthly averages) organized like a database table (rather than a column-oriented table such as a crosstab) stripped of extraneous information (anything that’s not the data and its headers).
COUNTD is one of the slowest functions types, avoid when possible.
MIN and MAX functions perform better than AVG and ATTR.
Strings and dates are slow, numbers and Booleans are fast.
When you create calculated fields, the data type you use has a significant impact on the calculation speed. Integers and Booleans are generally much faster than strings. If your calculation produces a binary result (for example, yes/no, pass/fail, over/under), be sure to return a Boolean result rather than a string.
Tableau Desktop is optimized to connect to row-oriented tables, where math, science, and history values are organized under a column called “Subject” and the scores for each student are organized under a column called “Score.” You can pivot the columns in the rows, by manually editing your Excel data.
Conclusion:
This tutorial includes all the important questions required for the quick preparation for Interview question on Tableau. So here you can find the short description on each topic if you want to get more details on each topic kindly visit https://help.tableau.com/ for the elaboration.
