Wednesday 25 April 2018

Tableau Interview Questions

1. What is Tableau?

Tableau is a business intelligence software that allows anyone to connect to respective data, and then visualize and create interactive, shareable dashboards.

2. What are Measures and Dimensions?

Measures are the numeric metrics or measurable quantities of the data, which can be analyzed by dimension table. Measures are stored in a table that contain foreign keys referring uniquely to the associated dimension tables. The table supports data storage at atomic level and thus, allows more number of records to be inserted at one time. For instance, a Sales table can have product key, customer key, promotion key, items sold, referring to a specific event.
Dimensions are the descriptive attribute values for multiple dimensions of each attribute, defining multiple characteristics. A dimension table ,having reference of a product key form the table, can consist of product name, product type, size, color, description, etc.

3. What is the difference between .twb and .twbx extension?

·         A .twb is an xml document which contains all the selections and layout made you have made in your Tableau workbook. It does not contain any data.

·         A .twbx is a ‘zipped’ archive containing a .twb and any external files such as extracts and background images.

4. What is the difference between Tableau and Traditional BI Tools?

Tableau provides easy to use, best in class, visual analytic capabilities but has nothing to do with the data foundation or plumbing. But with an integration with a SQL server it can be the complete package.

On the other hand traditional BI tools have the before mentioned capabilities but then you have to deal with significant amount of upfront costs. The cost of consulting, software and hardware is comparatively quite high.

5. How many maximum tables can you join in Tableau?

You can join a maximum of 32 tables in Tableau.

6. What are the different connections you can make with your dataset?

We can either connect live to our data set or extract data onto Tableau.

·         Live: Connecting live to a data set leverages its computational processing and storage. New queries will go to the database and will be reflected as new or updated within the data.

·         Extract: An extract will make a static snapshot of the data to be used by Tableau’s data engine. The snapshot of the data can be refreshed on a recurring schedule as a whole or incrementally append data. One way to set up these schedules is via the Tableau server.

The benefit of Tableau extract over live connection is that extract can be used anywhere without any connection and you can build your own visualization without connecting to database.

7. What are sets?

Sets are custom fields that define a subset of data based on some conditions. A set can be based on a computed condition, for example, a set may contain customers with sales over a certain threshold. Computedsets update as your data changes. Alternatively, a set can be based on specific data point in your view.

8. What are groups?

A group is a combination of dimension members that make higher level categories. For example, if you are working with a view that shows average test scores by major, you may want to group certain majors together to create major categories.

9. What is a hierarchical field?

A hierarchical field in tableau is used for drilling down data. It means viewing your data in a more granular level.

10. What is Tableau Data Server?

Tableau server acts a middle man between Tableau users and the data. nTableau Data Server allows you to upload and share data extracts, preserve database connections, as well as reuse calculations and field metadata. This means any changes you make to the data-set, calculated fields, parameters, aliases, or definitions, can be saved and shared with others, allowing for a secure, centrally managed and standardized dataset. Additionally, you can leverage your server’s resources to run queries on extracts without having to first transfer them to your local machine.

11. What is Tableau Data Engine?

Tableau Data Engine is a really cool feature in Tableau. Its an analytical database designed to achieve instant query response, predictive= performance, integrate seamlessly into existing data infrastructure and is not limited to load entire data sets into memory.

If you work with a large amount of data, it does takes some time to import, create indexes and sort data but after that everything speeds up. Tableau Data Engine is not really in-memory technology. The data is stored in disk after it is imported and the RAM is hardly utilized.

12. What are the different filters in Tableau and how are they different from each other?

In Tableau, filters are used to restrict the data from database.

The different filters in Tableau are: Quick , Context and Normal/Traditional filter are:

o    Normal Filter is used to restrict the data from database based on selected dimension or measure. A Traditional Filter can be created by simply dragging a field onto the ‘Filters’ shelf.

o    Quick filter is used to view the filtering options and filter each worksheet on a dashboard while changing the values dynamically (within the range defined) during the run time.

o    Context Filter is used to filter the data that is transferred to each individual worksheet. When a worksheet queries the data source, it creates a temporary, flat table that is uses to compute the chart. This temporary table includes all values that are not filtered out by either the Custom SQL or the Context Filter.

13. What is disaggregation and aggregation of data?

The process of viewing numeric values or measures at higher and more summarized levels of the data is called aggregation. When you place a measure on a shelf, Tableau automatically aggregates the data, usually by summing it. You can easily determine the aggregation applied to a field because the function always appears in front of the field’s name when it is placed on a shelf. For example, Sales becomes SUM(Sales).  You can aggregate measures using Tableau only for relational data sources. Multidimensional data sources contain aggregated data only. In Tableau, multidimensional data sources are supported only in Windows.

According to Tableau, Disaggregating your data allows you to view every row of the datab source which can be useful when you are analyzing measures that you may want to use both independently and dependently in the view. For example, you may be analyzing the results from a product satisfaction survey with the Age of participants along one axis. You can aggregate the Age field to determine the average age of participants or disaggregate the data to determine at what age participants were most satisfied with the product.

14. What is the difference between joining and blending in Tableau?

·        Joining term is used when you are combining data from the same source, for example, worksheet in an Excel file or tables in Oracle database

·        While blending requires two completely defined data sources in your report.

15. What are Extracts and Schedules in Tableau server?

Data extracts are the first copies or subdivisions of the actual data from original data sources. The workbooks using data extracts instead of those using live DB connections are faster since the extracted data is imported in ableau Engine.After this extraction of data, users can publish the workbook, which also publishes the extracts in Tableau Server. However, the workbook and extracts won’t refresh unless users apply a scheduled refresh on the extract. Scheduled Refreshes are the scheduling tasks set for data extract refresh so that they get refreshed automatically while publishing a workbook with data extract. This also removes the burden of republishing the workbook every time the concerned data gets updated.

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