# Tableau Interview Questions BI and Visualization

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• 51 Question(s)

## Beginner

Data visualization is merely the method by which data is described via visual representation. For millions of years, people have used visuals to describe the world around them. Data visualization gives a universal and instant understanding through the use of the strong visual treatment scheme of our minds.

Technological developments have increased the significance of business intelligence by making data visualization more common and effective than ever before. Tableau leads the world in providing company people with all backgrounds and sectors with the data visualization process. Global businesses understand that the capability to efficiently visualize information leads to improvement. Data visualization facilitates the understanding of large and small data by the human mind and also facilitates the detection of patterns, trends, and outliers in groups. Good visualization of information should position meaning in complex datasets so your message is clear and concise. Some benefits are as follows:

1. Building methods for data absorption.
2. Data visualization allows users to obtain vast quantities of operational and company conditions data.
3. Visualize corporate relations and patterns.
4. Action on new trends more quickly.

Tableau is an innovative Tableau Software data visualization software. Tableau can readily connect to almost any information source, such as corporate information storage, Microsoft Excel or Web-based information. Tableau enables instantaneous understanding by transforming information into interactive dashboards called visually attractive visualizations. It takes only seconds or minutes rather than months or years, and it can be achieved with a drag and drop interface that is simple to use. Tableau is a business intelligence software that enables someone in just a couple of clicks to connect to data and then visualize and create shareable interactive dashboards with some other information. Every Excel user can learn it easily, but powerful enough to solve even the most complicated analytical problems. It only requires seconds to securely share your results with others. The result is BI software, which you can trust to give the people who need it answers. The figure below shows the Family offerings tableau:

Software for quick analysis and quick-fire business intelligence is provided by Tableau Software. Tableau Desktop is an application for data visualization that allows you to analyze practically any structured information and generate lovely interactive charts, dashboards, and accounts in minutes. You can connect nearly any data source from Tableau to data stores after a fast setup and show information in several graphic views. You will work more quickly than ever before, designed to be simple to use. Tableau Server provides browser-based visual analysis that can be used at a fraction of the cost of traditional software. With only a few clicks, you are automatically able to post or incorporate live, interactive charts, dashboards and reports with present information to the requirements of all of your company. It deploys in a few minutes and customers can generate thousands of accounts in your IT facilities, without IT services. Tableau Reader is a free viewing application that allows anyone to read and communicate with Tableau Desktop's packaged workbooks.

Although Tableau can analyze databases, you don't need to know anything about databases to use Tableau. You don't need Tableau. Indeed, Tableau is intended to enable entrepreneurs with no technical training to effectively analyze their information.

Tableau has three easy concepts:

• Connect the Tableau- Connect it to any database you want to evaluate. Note that the data is not imported by Tableau. Rather, it straight queries the database.
• Analyze- Analyzing information is viewed, filtered, sorted, calculated, reorganized, summarized and so forth. It implies analyzing information. By placing areas of the information source on the Tableau worksheets you can do all these things using Tableau. Tableau displays information in conventional controllers and query languages (such as SQL and MDX) and displays a visual assessment of the information when you drop a field on a worksheet.
• Share- By exchanging workbooks with other Tableaux users, adding outcomes into apps, such as Microsoft Office, printing in PDF or using Tableau Server to publish or integrate your opinions across your organisation you can share your outcomes with others.
• Connect live- Makes your information directly connected. You determine your efficiency at the velocity of your information source. You can connect straight to the live database by using this function. The efficiency is decreased when you select this function.  Import all information-You can import all the information to your local computer by using this function. This is called the EXTRACT, which has been saved with the.tde extension.
• Import all the data– Import the complete information source into the quick information motor of Tableau as an extract. The workbook is used to save the sample.  Import certain information–import your information into the rapid information motor of Tableau as an extract. You need to indicate which information you want to obtain with filters. It's also like extracting data, but while you import information to your local scheme, you can apply filters.

There are 13 types of charts in Tableau:

• Bar chart: A bar chart shows information with the bar length proportionate to the variable's value in rectangular bars. When you pull a dimension into the Row shelf and evaluate it to the Column shelf, Tableau generates automatically a bar chart.

• Line chart: A line chart brings together different information points in view. It offers easy ways to visualize a series of values and it is helpful for seeing trends in time or predicting future values. Tableau adds sales as SUM and shows a straightforward line chart.

• Pie chart: A pie chart view that shows how different product categories contribute to total sales.

• Map: Maps are one of Tableau's most successful kinds of charts and are also among the easiest to produce charts.

• Scatter plot: Scatter plots provide an excellent way to perform ad hoc analysis. In Tableau, by putting a measure in a row shelf and another measure in a row shelf, you build a scatter plot. We can ask Tableau to compare two numerical values by doing this. As a default view for this, Tableau selects a scatter plot by default.
• Gantt chart: A Gantt graph shows the advancement over a time period in the value of a job or resource. It is widely used during a period of time in project management and other variation studies. Thus, time is an important area in the Gantt chart.
• Bubble chart: To display data in a cluster of circles use packed bubble charts. Dimensions define the different bubbles and measurements set the size and color of each circle.
• Histogram chart: A histogram represents accurately how numerical data are distributed. It estimates a continuous variable's likelihood distribution.
• Bullet Chart: A bullet chart is a bar chart that replaces dashboards and meters. The graph is a variation. The results of the main measure are compared with one or more other measures using a bullet chart.
• Heat maps: A heat map is a graphical depiction of the information with colors for each value in a matrix. "Heat map" is a new word, but there are long-term shading matrices.
• Highlight table: You generate a highlight table in Tableau by putting one or more sizes in the stand of the columns and one or more on the shelf of the rows. Then you choose Square as the sort of mark and position a measure of concern on the Color shelf.
• Treemaps: To show information in nested rectangles, use treemaps. The structure of the map and the measurements are used to identify the size or color of each rectangle.
• Box-and-whisker plot: The box plots are also known as box-and-whisker plots. They display the value distribution in an axis. Boxes are the mean 50% for the information, the upper two quartiles for the distribution of the information.

Tableau Public is accessible for Windows and Mac, after public version, version 8.2! Tableau Public is the free version of revolutionary software, which makes accessible on the Mac, supports high-resolution Retina displays, and incorporates Mac-Specific controls to anyone wishing to say engaging stories with Public Data. Tableau Public can be downloaded from Download Tableau Public.

Tableau Server is a solution for company intelligence providing browser-based visual analysis that can be used for only a fraction of the typical BI software costs. With a few clicks, you will be able to automatically post or embed interactive charts, dashboards, and reports with present information tailored for everybody's requirements. It deploys in minutes and customers can report thousands without IT facilities— all in their IT facilities. The data extracts, metadata fields and the calculations can be shared and uploaded, database connections can be preserved with the tableau data server and the tableau users can mediate it. Save and share with others any modifications to the parameters, data set, definitions, aliases and calculated fields to establish a safe, standardized and centrally managed data set. The server funds can be leveraged and not first transmitted to the local machine and extract queries can be executed.

If you don't plan to use a set of rows, you should filter them out of the set data as quickly as necessary. When you have an all sales table and just want to check US sales, create a custom SQL application to filter out. When the filter depends on the worksheet, try using a context filter. We can always explore other filter types in Tableau to improve performance. It increases the efficiency but it should always improve the performance if you want to hide any field that you don't use in any of your worksheets, apart from "Dimensions" then  "Hide all unused fields."

First of all, let’s understand the Tableau public. Tableau Public is Tableau software's free alternative.  There are two flavors of Tableau Public.

1. Tableau Public (Server): is the free version of Tableau Server that is hosted by Tableau Software in the cloud. This product is mostly two: As free, it needs everyone's access to all workbooks and information. As far as an information source is concerned, all excerpts should be made and there is 1 million rows limit.
2. Tableau Public(desktop): is a free variant of the tableau desktop or a limited course like workbooks, which can only be saved to the public Tableau (server) and connects only to local information.

You need to build a Tableau Public account here and download the Desktop (Tableau Public) to work with Tableau Public. With a Tableau Desktop user license, you can create data visualization and publish it on Tableau Public, but it is always required to be an excerpt with restrictions on the number of rows and data sources.

Now, we have understood Tableau Public so we can move on to the Permission part. The response is no. Everyone on the internet can access all of the material saved to Tableau Public. The only person who can remove your own material, you are the author, but everyone can view it on the internet. In addition to watching it, everyone can upload and create on your initial copy of your workbook (including the underlying information). Your Tableau Public data is now available throughout the world and can be downloaded by anybody. We highly propose that you only publish information that you are prepared to share. Tableau Public can connect to Microsoft Excel, Microsoft Access, and multiple text file formats. It has a limit of 1,000,000 rows of data that is allowed in one file.

We can easily find out if a color-based field is used as discrete or continuous. Blue shows a discrete field, whereas green shows a continuous field. We are not alone if our mind is blown because we always supposed those colors represented a dimension or a measure of the field. The idea that blue is measured and green is the most popular legend in Tableau. It is simple to comprehend why dimensions are classified by default as separate factors and have in the shelf sizes a tiny blue icon facing them. Measures are divided by continuous variables so that in the measuring panel they are prefaced with a green icon.

Color coding identifies discrete rather than ongoing areas rather than measures. In fact, measures can be used as discrete areas or as ongoing, and the same applies to certain aspects like dates.

There are two laws of thumb. Discrete fields draw headers; continuous fields draw axes.

See the following visualizations, which examine each month's revenues. I use the date as a separate field on the first graph.

Note that for each month there is a discreet header. I am using the same precise information in the second graph, but the dates aspect has been altered from discrete to continuous:

We have a permanent axis of time, as we can see. Since the axis is continuous, we can not alter the order of the dates; from the earliest date on the left to the latest date on the right they follow the chronological order. On the other hand, we can vary the order of the dates if the dimension of the date is used as discreet as shown in the first image. We could, for instance, sort the bars down, first with the largest sales of the month and the last with the smallest sale of the month. Whether or not we should use an area as discrete or ongoing brings me to my second rule: discrete fields can be sorted, continuous fields can not be sorted.

A shelf is an area of the visualization display where parts of information can be dropped to enable Tableau to act on them. If you place a dimension on the shelves of the rows or columns, headers are created for the Members.

Tableau shows information with marks that match each mark in the information source to a line (or a set of rows). A shelf is a display area. There are four kinds of shelves:

• Columns
• Rows
• Pages
• Filters

The columns shelf creates the columns of a table, while the Rows shelf creates the rows of a table. You can place an unlimited number of fields on these shelves.

When you place a dimension on the rows or columns shelf, headers for the members of that dimension are created. When you place a measure on the Rows or Columns shelf, quantitative axes for that measure are created. As you build up your data view with more fields, additional headers and axes are included in the table and you get an increasingly detailed picture of your data.

In the view shown below, the members of the Customer Segment dimension are displayed as column headers, while the profit measure is displayed as a vertical quantitative axis.

Tableau displays data using marks, where every mark corresponds to a row (or a group of rows) in your source.

Each Tableau worksheet includes cards and shelves like Columns, Rows and Marks, Filters, Pages, Legends, etc. Build the framework of your visualization by putting the areas on the shelves or cards.

Increase the amount of detail and control by including or excluding information the number of marks in the perspective. Add context by color, size, shape, text, and detail to the visualization. Experiment with placing areas on various shelves and cards to discover the ideal way of viewing your information.

The ordinary Tableau filters are mutually autonomous. Each filter reads all lines and generates its own outcome from the source information. There may, however, be situations where only the results returned by the first filter can be processed by the second filter. In such a case, the second filter is referred to as dependent filters because the data passing through the context filter is processed only. Background Filters are used for two primary reasons.

• Improves efficiency–The queries can be slow if you set many filters or have a big information source. To enhance efficiency, you can set one or more context filters.
• Create a number or top N filter − A context filter can only include interest data and then set a numerical filter or a top N filter.

Any other filters you set are described as dependent filters because only the information passed through the context filter is processed. Filters used to enhance efficiency are often used in context. If the context filter does not decrease record numbers by 10% or more, the dashboard can effectively be slowed.

The user does not change the context filter many times–when the filter is changed the database has to be re-published and the temporary table re-written, slowing its efficiency.

When you set a context dimension, Tableau creates a temporary table to be reloaded when the view has been launched. The temporary table generated is available in the  Access Table format for Excel, Access, and text information sources. You must have approval to build a Temporary Table on your server for SQL Server, My SQL and Oracle information sources. Temporary tables or context filters are not created in multidimensional information sources or cubes, and only which filters are separate and dependent.

## Intermediate

Tableau product families include the following: Tableau Desktop, Tableau Prep, Tableau Online, Tableau Server, Tableau Mobile, and Tableau Public.

There are different offerings from product family point of view for individuals, for organizations etc.

For individuals: Typically Tableau Desktop, Tableau Prep, Tableau Server, Tableau Online are being leveraged based on pricing options.

For organizations: Tableau offers deployment options such as on-premise or public cloud and fully hosted by tableau. In each of these segments, options vary such as Tableau Creator (Tableau Desktop, Tableau Prep, Tableau Online), Tableau Explorer (Tableau Online) and Tableau Viewer (Tableau Online) etc.

Tableau Desktop – primarily used for visual analytics is a self-service analytics and visualization product. We can connect to multiple data sources directly and perform live data analysis. Data can also be integrated from multiple data sources and dashboard can be created from those.

Tableau Prep – it is used for data preparation, data analysis by helping people quickly, confidently combine data, transform them, and clean them.

Tableau Online – this is fully hosted in the cloud. We can publish dashboards and share our discoveries with anyone. All easily accessible from a web browser or on the go with mobile applications.

Tableau Server – this is primarily required at a large Enterprise level in an organization. We can create and publish dashboards using Desktop and share them across the organization using this Server. Web-based server is available for easy and quick access.

Tableau Mobile – this is a very unique way of getting quick access to data on mobile devices. Based on access privilege, relevant details can be seen. Selecting, filtering, drill down features of data are available on this. It can be downloaded from Google playstore or Apple Appstore.

Tableau Public – One can create and share interactive charts, graphs, maps, mobile-friendly dashboards using this and can publish anywhere on the web.

We can save and share data using a variety of different Tableau File Types. The difference between each file type relate to the amount and type of information stored in the file. Following are different file types:

• Tableau Workbook (twb) – tableau’s default way to save data. Information to visualize data. No source data involved. Typically this is an xml document format.
• Key objective is to capture entire workbook which may contain one or multiple worksheets
• This may also additionally contain dashboards
• This may also contain the stories
• All sheets, connection information stored. But data not stored

• Tableau data source (tds) – typically accesses frequently used data sources. It includes server address, password, other metadata related details to the data source.
• Key objective is to store all information for connecting to a data source
• However, it does not contain the actual data

• Tableau bookmark (tbm) – this is typically sharing worksheets from one workbook to another. It includes information to visualize and the data source provided the source workbook is a packaged workbook.
• As the name reflects, key is to use it as a bookmark
• Contains information for one worksheet
• Simple and easy way to share work quickly through the bookmark if objective is to share a particular worksheet only

• Tableau data extract (tde) – it improves performance and enables more functions. It includes source data as filtered and aggregated during extract.
• Key for storing data source related information and hence users can use it to work in offline mode

• Tableau packaged workbook(twbx) – this is typically shared with all who do not have access to source data and can view entire dashboard with the help of a tableau reader.
• Key objective is to store all information, data, local files, images all in a zip file format in this and share to other users who may not have access to Tableau so that they can view
• All sheets, connection information stored. Data is also stored
• This format takes more space since it captures data, but very useful as it stores all necessary information. Can be used best for backing up your work

• Packaged data source (tdsx) – this is typically a zip file format which contains the data source file of .tds extension and local file data sources such as .tde files, text files, excel files, MS access files etc.

Out of the above, tde and twbx files generally handle potentially large data.

Tableau supports below data types:

• Text values
• Date values
• Date and time values
• Numerical values
• Geographical values (latitude and longitude used for maps)
• Boolean values (true/false, 0/1 type of conditions)

Data type can be changed for a data type either on the “Data source” page or in the “Data” pane in Tableau. For example, if current data type is defined as “text value” and this needs to be changed, then data type in “Data source” page will provide dropdown list options of other data types such as “Number (decimal)”, “Number (whole)”, “Data & Time”, “Date”, “String”, “Boolean”. By default, the data type would be defined as a “Text value”.

It is important to change the data type so that it reflects correctly while we generate an extract.

When Tableau reads from data sources such as files in Microsoft excel or csv (comma separated value) formats, then it assigns data type automatically for respective values such as text/strings, date field, date and time field, Boolean field and so on. Additionally, if we source data from a csv with some mixed-value column is mapped to a single data type field in Tableau, then Tableau may assign one of the data type. For example a mixed value could be a mixture of numbers and dates, and they can be mapped to a number data type or date data type.

Suggested approach is to handle mixed value columns in a way one can format empty cells within the data source so that data type of that field can be matched and also to create additional new field that does not contain mixed values so that it is of a particular data type.

Tableau support below aggregation types: sum, average, median, count, count distinct, standard deviation, variation, minimum, maximum, standard deviation of a population, variance of a population, attribute (ATTR), dimension.

Aggregation in Tableau can be performed on measures and dimensions both. It is more common in measures. When we create a measure in the view, aggregation is already applied to its values by Tableau. So “Revenue” will become “Sum(Revenue)”. Typically “Sum” is the default. Else other aggregations such as Average, Median, Count, Count(Distinct), Minimum, Maximum, Percentile, Std. Dev, Std. Dev(Pop.), Variance, Variance(Pop.) can also be selected from the list. These options are primarily for measures. For dimensions, we can have aggregation types as minimum, maximum, count, count distinct etc.

When we have multiple data sources and we want to integrate those to visualize in our Tableau dashboard, we use blending.

• It creates a connection between primary and secondary data source by a left join kind of a link.
• By default, Tableau does a left join considering all data elements from primary data source.
• Shuffling of various options can be performed between data sources. There are two ways of blending – automatically defined relationship and manually defining the blend.

Each data source contains its set of dimensions and measures. We can not have specific set of dimensions and measures which will limit us to create groups, formulas etc across the data. Data sources can be of multiple RDBMS such as Oracle, SQL Server, DB2 etc. and other data sources such as spreadsheets etc.

Blending also avoids joining of duplicate data as it will be linked via a common dimension.

One can change the linking field (dimension or measure) or add more linking fields to include additional rows of data from the secondary data source in the blend, changing the aggregated values.

Yes Time series is possible in Tableau and can be visualized using Line and Area charts. Both the charts can be represented in continuous and discrete format.

We can use line charts to display time series data in Tableau. We can add the dimensions, create measures and display it based on a time value (e.g. let’s say by year, month, week, day etc.). We can turn on the forecasting feature to see if we can get a feel of the seasonal trend as part of forecasted model. In Analytics pane, there is an option called “Forecast” to be able to see the Forecast. There will be some default period for which it will show the forecasted values.

Using these charts different level of granularity (e.g. monthly, weekly, daily etc.) can be shown. Different forms of aggregation can be performed.

Bullet graphs are bar charts that include a reference line and reference distribution for each cell in the plot. These are used to pack a lot of information into a small space.

Bubble charts offer another way to present one-to-many comparisons by using size and colour. They can be interesting to look at but do not allow for very precise comparisons between the different bubbles.

Hence bullet graph and bubble chart are completely different and used for very different purposes.

Tableau workbooks can be shared securely via Tableau Server. When we want to share dashboard with data and someone who is supposed to view does not have access to Tableau Server and can only view via Tableau reader, then file has to be saved with data as .twbx file format.

Tableau Public can also be used where users can create dashboards and share / publish to other users. Of course these will include – user level filter criteria, database level security, application or environment level security etc. to be able to show relevant data.

There are options to restrict sensitive data at the time of extracting file using extract data dialog box.

There are multiple ways to sort data in Tableau.

1. Manual sorting via icons which appear in toolbar menu.
2. Calculated sorts using the sort menu.
3. Sorting using legends in a visualization chart.
4. Sorting on multiple dimension views.

There are a few different ways to add filters to data visualization.

1. Normal filter - Dragging any dimension or measure on to the filter shelf provides filtering that is accessible to the designer. That is a normal filter.
2. Quick filter - When normal filter is used as a generic filter by making it accessible to more people by turning it into a quick filter. This can be reused by all.
3. Context filter - Context filters do not only filter the data, they cause Tableau to create a temporary table that contains only the filtered data. Typically, if we plan to alter our filter frequently, then it is advisable not to use context filters.
4. Data source filter – this can be applied at data source level to visualize / restrict which dimension, measures etc. to show from a data source or multiple data sources.

Normal filter is used to restrict data from database based on specific dimension / measure etc. that is selected / specified by the user.
Quick filter can be used in an adhoc format. Here user has the option to dynamically change data members at run time. Restricted data members can not be seen here.

Auto scrolling filters are not supported in Tableau Server, but they can be consumed in Tableau Desktop or Tableau Reader.

Step by step process of adding auto filters can be described below:

• Go to “worksheet”
• Select “action” (this could be select, hover, menu etc.)
• Select “filter” (basically there are 3 options under add actions – filter, highlight and URL)

Selecting filter here adds filtering action to the set of data used.

• Give the name of the “filter”
• Select “source sheet”

Essentially auto filters are useful when some action is triggered in the source sheet, then that reflects in the target sheet where there is a correlation of data shown or linked.

When using “action”, by hovering filters automatically gets applied to target sheet if we have defined as “hover” option, and so on.

Any field placed on the filter shelf enables a filter for that dimension or field. The style of filter control is dependent on whether the field is continuous or discrete. If we want to expose a filter in the worksheet, we can right-click on any pill used anywhere in the workspace and then select the menu option Show Quick Filter.

Granular details can be displayed with the help of symbol maps. Proportional values can also be represented using these maps which will help show quantitative values for individual ids. So if we want to show sales data for last 5 years across the country, the same can be shown in the geo-view with proportionate size / magnitude related to each and every location accordingly.

Filled up at the other hand is more suitable for showing “ratio” data. Pie charts typically have that information to a relative whole. For example, we want to display percentage of sales for a product by geographic location. In that case, filled maps can be used to show percentage of sales for different categories individually and relative to total sales by country.

From Symbol Maps standpoint:

• Both data and map should be appealing enough and clear for user to interpret answers out of it
• Proportion of varying magnitude in data can be shown
• For example: we can plot earthquakes around the world and size them by magnitude.

From Fill Maps standpoint:

• Here also both data and map should be appealing and clear enough
• Relevant for showing “ratio” data
• For example: when we want to show “cancer rate” around states, counties across a country for a particular time frame or within a time window, then fill maps or filled maps can be useful.

All of the options above – a, b, c, d are correct. Tableau uses Heat maps, Highlight Tables and Tree maps to compare granular combinations of dimensions and measures.

Both of them are different and not similar.Reference lines in Tableau are used to show visual comparisons to benchmark certain figure, constant or values. These can be added at a constant or computed value on the axis. For example, we are showing sales of Firm1, Firm2 and Firm3; the reference line can be set as an “average sales figure” which could act as a benchmark.

Trend lines on the other hand can be used to represent pattern of the trends in the data. For the same above example of Sales of a Firm1, we can use different trend lines to represent if it is following a particular trend. These can be linear trend, logarithmic trend, exponential trend, polynomial trend, power trend etc.

False. It is critical and important to build cascaded dashboard design.

Typically if input source data is huge, it will always be challenging to display the same in a dashboard. Hence it is advisable to have cascaded dashboard design where multiple views can be defined and cascaded in a dashboard to be able to provide summary view on top, other aspects on bottom left, bottom right etc with actions / filters to display required data appropriately.

tabcmd” and “tabadmin” are command line tools that Tableau uses.

“tabcmd” provides functions for performing workflow tasks like publishing workbooks, adding users, exporting workbooks, exporting data files etc.

“tabadmin” is used for server administration where tasks could be configuration of server options / server parameters, activating users, resetting passwords, managing deployments etc.

Answer should be b and d. As a and c are CORRECT answers.
As a best practice, we should remove all non-data ink. Hence d is INCORRECT.
As a best practice, we should use actions to filter data instead of quick filters. Hence b is INCORRECT.

A dashboard is an information collection that is shown in one location and that supports information so that a range of data can be compared and monitored concurrently. You may have a number of opinions, for instance, which you review each day. You can generate a dashboard that displayed all opinions at once, instead of flipping through each worksheet. In the same way, you create a new worksheet, you can create a dashboard.

Select Dashboard > New Dashboard

Alternatively, on the bottom of the workbook, press the New Dashboard tab. The bottom of the workbook contains a fresh dashboard tab. To add opinions and items, move to the fresh dashboard. The dashboard window on the left-hand side of the workbook replaces the Data Window. The dashboard window lists the sheets in the workbook. When you build fresh worksheets, you can always update the Dashboard window to include all worksheets on a dashboard. The worksheet is labeled with a control mark in the Dashboard window when a picture is added to the dashboard. Any legends or rapid filters on the board are automatically added to the dashboard. By default, dashboards use a Tiled design that allows for a single-layered grid for each perspective and item. To overlap opinions and items, you can alter the design to Floating.

Programs for publishing workbooks connecting to extracts can program the extracts automatically to be retrofitted. This way, every time the underlying data is being updated you do not have to republish the workbook and still obtain the performance of a data extract. Just say you have a workbook connecting to a big database updated on a weekly basis, for instance. You can generate an extract with only the required information instead of releasing a workbook that queries live information. This improves efficiency and prevents live database queries. This workbook can then be added to a schedule so that a server manager will refresh the extract at regular intervals with updated data from the data warehouse. However, when you publish in Tableau Desktop, an administrator can add a workbook to the timetable.

1. As you publish a workbook, press on Scheduling & Authentication in the Publish Workbook to Tableau Server dialog box.
2. Select a working book timetable in the Schedule & Authentication dialog box. In order to re-freshen the extract, you must have an integrated password on all information sources that require authentication. This involves non-extract information sources.

You can plan the excerpts to be refreshed automatically when publishing workbooks that relate to excerpts. In this way, every time your underlying data are updated, you do not have to republish the workbook and still have the performance of a data extract. Let's say you have for instance a workbook that is updated on a weekly basis with a big data warehouse. You can create an extract including only the necessary data instead of publishing a workbook which queries the live data. This improves performance and prevents live database queries. This workbook can then be added to a timetable to refresh the extract at periodic intervals with updated information from the data store. Timetables are established and managed by an administrator on the server. However, when you post from Tableau Desktop, an administrator can add a workbook to a timetable.

1. When you publish a workbook, press on Scheduling and Authentication in the Publish Workbook to Tableau Server dialog box.
2. You can also publish Tableau Server information sources in relation to publishing workbooks in the Scheduling & Authentication dialog box to choose which timetable for the Publishing Data Sources workbook. A reusable link to the information is a data source. You can centrally handle and store information sources by publishing information sources. Published information can be found in the information engine (extracts) of Tableau, or in a live and related database. The published source of information also includes field-level adaptations, such as calculations, groups, sets, and default. This subject explains how to publish a Tableau Server information source. Publishing a Tableau Server information source:

(i) Choose the data source in the menu Data and then choose to Publish to Server:

(ii) You will see the Tableau Server login dialog if you have not already signed up to Tableau Server. Type the server name or URL (sales server, for instance) and click Connect. Simply click Connect.

(iii) Next, type and press Sign In, your user name & password. Type your Windows user name (not needed–except for multi-domain environments where the user does not default) if the Tableau Server is configured for using the Active Directory; else enter your Tableau Server user name. The above dialog will not be displayed if Tableau Server is set up to use SAML for user authentication. You will instead see an immediate sign in from an external supplier of identity.

(iv) Now, you see the Tableau Server dialog box- Publish the Data Source.

Please specify: A project is like a folder containing workbooks and information sources. Project. One project named Default is provided on the Tableau Server. It is necessary to publish all workbooks in a project.

Name: Enter the workbook name in the text box Name. Name: To pick a workbook from the server, use the drop-down list. The workbook on the server is overwritten with your workbook when you publish it with the name of a current workbook. As a license to overwrite workbooks on a server, you must be permitted to Write/Web Save.

Authentication: If you need a username and password from your source, you can specify how to manage authentication when it is posted on the server. The accessible alternatives rely on your sort of information source

Add Tags: One or more keywords can be typed in the Tags text box describing a workbook. Tags assist you and others when browsing the server discover associated workbooks. It should be divided into a comma or a room for each tag. If space is on the tag, type a quote tag in the tag (e.g. "Sales Quotes")

(v) Allowance for or denying access to the workbook on the server can be specified. Standardly, everyone can communicate with the workbook and all functions are permitted as a publisher. See Setting Permit for more details and see Permit for data on user and group capacities.

(vi) Select Include External Files if you publish an external file information source and/or information source on a mapped cart. A copy of the information source is released when you include external documents. Excel Access, Text, Data Extract, and Image File external information sources include. Others may not be able to see the worksheets online if you do not include these documents. Change the link data to ensure that the workbook refers to the entire UNC path if you do not want to release the external server documents. You would connect to \\filesrv\datasource.xls instead of linking to D:\datasource.xls, for instance.

(vii) Click Publish. To publish.

One reason is that filters can not be properly defined at report stage because the whole set (which may not be essential) is taken out of the request. There are a few causes:

1) Create a request that returns many documents from the table(s), if lower aggregated records are sufficient. This can be verified by selecting the amount of marks at the underside of the Tableau Desktop. If this number is very big, you could draw a great deal of information from the database

2) Use indigenous drivers: Tableau will suggest or require you to produce an extract of information so that you can proceed to work with a specific driver. The use of indigenous drivers instead offers better efficiency with ODBC links.

3) Testing using a new tool: A useful way to find out whether the slow query causes a slow workbook is to test the same request in a different instrument, for example, Microsoft Access or Microsoft Excel.

See userName\My TableauRepository\Logs for the request to be executed and see the log.txt file. Open this document and scroll up from below until you discover the following section: A query passed to the database is the section between the start-and-end query tags. This text can be copied and then used by an instrument such as Access or Excel. If it takes the same time to return as in Tableau, the issue is probably the query, not the instruments.

4) Use excerpts: If you have problems with performance, create a table extract. These files can contain performance-oriented characteristics such as pre-aggregated hierarchical data and pre-calculated fields (reducing the quantity of visualization job).

(i)Tune your indexes: Ensure you have indexes on all columns that are component of the table joins Make sure you have indexes on any column that is used in a filter. Explicitly describe keyboards Foreign main relations For big datasets use table partitioning Use NOT NULL columns where possible. The Query Optimizer selects these statistics to find or update the effective plan.

(ii) Optimize the mode of information: useful to generate summary tables if most of your requests need only aggregated information-not base level documents.

Quick Filter

The Quick Filter always seems to the correct side of your window and shows which elements that you select, whichever u filter is used, if you wish to offer the user an opportunity to dynamically change data members at the moment this would be helpful. Quick Filter shows you what components you select. Only unrestricted data members can be seen in this case.

Normal Filter

Normal filer is something that, under certain circumstances, you can confine list alternatives, or restrict field or value information. The database data is restricted by the use of both measurements or sizes selected. Normal filter hides always. U can filter information when you drag a dimension into the filter rack by choosing a set of values. When dragging by measurement, you can select a range of values.

For processing a remote database, Tableau consolidates the components in a SQL or MDX request on your visual canvas. Because the database is used with stronger hardware than the laptop/working stations of the analyst, you should expect to handle queries much faster than most end users hardware-limited memory BI apps. For larger datasets that can be on a quick cluster and too big to add memory, Tableau is progressively able to shift compute (quests) close to information. Another performance factor concerns information transfer or transfer in the case of Tableau. As tableau viewing is intended for human consumption, it is designed to adapt it to the human perception system's capabilities and limitations. This implies usually, that the quantity of information in the query results set is low in relation to the size of the information underlying the aggregation and filtering focused on the visualization of trends and outlines. The tiny result sets require little bandwidth in the network, so Tableau can rapidly get the results. And Tableau is caching query outcomes for quick reuse, as Ross has stated. The final factor as stated in Eriglen includes the capacity of Tableau to speed up memory if required (e.g. when operating with very slow databases, text files). Tableau's Data Engine uses memory-mapped I / O, so it can easily work with large data sets that don't fit into your memory when used in memory acceleration. Only in a subset of disk data that are needed for a given query will the Data Engine work, and as required the data subsets are mapped into memory

We have a very simple formula to calculate Tableau Report Rendering Time.

Report rendering time=Network time(request from URL to Report server) +Query execution time + Network time(response from SQL Server)+calculations(table column)+time taken to display the report in desired format(HTML/ pdf/ excel)

Table Calculations: These are inbuilt calculations in tableau which we normally use to calculate Percentage from or for YTD and other calculations like the measure across the table, below table and etc.

Layout Containers in force spatial links between components of a dashboard. Conceptually, they allow the designer of the dashboard to format common elements and simultaneously move several dashboard objects.

One of two choices includes layout containers: horizontal or vertical.

• The developer can group working sheets and dashboards from right through the pages with horizontal design containers and edit all elements at once.
• Up to the bottom of your page, vertical containers enable the user to group workshop sheets as well as dashboards and modify the width of all elements.

Horizontal and vertical components: We can use these to transfer all sheets or filters in one shot. However, without this, we can still generate the dashboard. It enables us to simplify our job

Three kinds of filters are found in Tableau. More explicitly, the information presented in your chart can be limited in three distinct ways. Each has its own weaknesses and strengths, and we look at them one by one.

These kinds are traditional filters Custom SQL "Filters and Context filters.

Custom SQL Filters:

The "Filter" is a WHERE provision which is put in a SQL to search the workbook information. Custom SQL Filters: "Filter" is a table word that technically only relates to context and classical filters, but which is emulated by the conduct of the worldwide context filter with the Custom SQL Filter, so we're going to refer to it as such. Custom SQL "filters" are always worldwide by building. A personalized SQL filter is usually used because it limits the size of an information sample. The lower your information extract, the faster your charts are loaded. In other words, without sacrificing effectiveness, you can create more complicated graphs. During the server connection phase, one way to generate a custom SQL "Filter."

Context Filters:

Context Filters is a table filter which impacts the information transmitted to each table. Context Filters are good for limiting the worksheet information. If the worksheet queries the information source, a temporary flat table is created that is used to calculate the diagram. This provisional table involves all values not filtered out either with the Custom SQL or the Context Filter. Just like the Custom SQL "Filters," your objective is to reduce this temporary table. Context Filters have some benefits compared to Traditional Filters. First of all, they run faster than conventional filters. They are also performed before traditional filters and can be performed at once, thereby increasing effectiveness. They have a disadvantage, however. It requires time to put the filter in context. One principle is that the filter should be placed in context only if it minimizes the information by at least 10 percent from the knowledge base of Tableau. By dragging a field to the filter shelf and editing the filter, a context filter is developed. If you have various context filters, CTRL-Select all of them and add them to the framework in one lot. You can also pick the context by right-clicking the field at your shelf. This increases your filter's effectiveness.

A traditional filter is precisely what most individuals believe about filters. When Tableau creates the visualization, it checks whether a traditional filter filters out a value. This is the slowest of all filter kinds since it is not done on the table level. However, after the context filters, it has the benefit to be done. If you have complex filters "Top N," this is a must. You can create a traditional filter by dragging a field on the "Filters" shelf.

1. Use extract. Use extract.

There is nothing near the effectiveness of an extract. There is nothing else. Extracting the best bet is if you don't necessarily need live information.

1. Limit your dashboard to respond to only one situation completely.

The easiest thing is for a dashboard to explore a single situation in its entirety. You might not be looking at only one scenario if your dashboard has six sheets, five actions, and 3 fast filters. Remember, whether your solution is elegant and comprehensive, if it doesn't work as fast as the user wants it, he or she won't use it. I would not advise your dashboard to be butchered so heavily that it can not manage a whole situation. Why did you use your dashboard if the user has to go somewhere else to look for the response?

1. Limit the information entered on each worksheet.

If you don't plan to use a set of rows, you should filter them as soon as possible out of the information set. If you have a custom SQL request that filters out your table and wants to view sales in the US only. Try to use a context filter if the filter is worksheet dependent. See my other Types of Filters post in Tableau for more data on filtering. You can also press on a Down arrow in order to conceal all fields you are not using from any of your worksheets. You can select "Hide All unused fields." I am not sure if effectiveness improves, but I just think that less information is always expected to enhance effectiveness.

While esthetic is essential to create a usable dashboard, it is not worth losing effectiveness to unimportant objects. In reality, by adding a purely esthetic item, it would be better to add more features.

1. Remove from visualization any non-essential elements.

This relates to the values on the pages, filters, and detail levels. If the user only sees if he scrolls over one point, he does not add importance to the original look. But, I leave that as the final step because it ought to be a last resort. In most cases, if you create dashboards, you can save a little bit of anticipation. Decide what tale you want to say, and just say it. A tiny dashboard is much simpler to add than to knock a big one

Incorporating public content into a blog needs blogging for integrated HTML content including script tags. Some of Tableau's popular embedded websites include:

Instead of Rich Text, edit your messages in the HTML  mode, otherwise, the Tableau does not preserve public embedded code.

Pressing Word-www.wordpress.org. On this website, a software script called WordPress can be downloaded and installed. You need a web host in order to do this. WordPress can be totally customized and almost everything can be used. There's also a www. WordPress.com service, allowing you to start with a new free blog on WordPress, but it's less flexible than downloading and installing WordPress. Blogs on Wordpress.com website are not using JavaScript-using tools such as Tableau.

Tableau allows flexible time analytics with a comparative date filter. But, sometimes, you may wish to view the values for a specific measurement in the same perspective for each year-to-date (YTD) and month to-date (MTD). You can generate date calculations to complete this assignment. Create a computed column that converts weeks from string to integer and use it in another YTD calculation. YTD: YTD:

MTD:

Christopher Hanrahan, Christian Chabot and Christopher Stolte established Tableau in 2003. The NYSE ticker DATA is traded in Tableau Software. It was published in the first $31 bid price per share on May 17, 2013. The following advantages are offered by Tableau Software: 1. Tableau Software is quicker than other alternatives. 2. Tableau Software is an intuitive instrument that has a drag and drop tool for you to see any changes you create. 3. You can create intelligent, fit and lovely dashboards with Tableau Software. 4. Tableau allows you to immediately connect to databases, cubes, data warehouses, files, and spreadsheets. 5. Tableau promotes: Android, iPhone-iPad Tableau software Tableau products are used by people of diverse skill levels across all kinds of organizations, including Fortune 500 corporations, small and medium-sized businesses, government agencies, universities, research institutions, and nonprofits. Organizations employ our products in a wide spectrum of applications such as growing revenues, improved activities, client service improvement, investment management, quality, and security assessment, disease study and treatment, a scholarly study completed, environmental issues addressed and education improvement. They have the following pricing information for Tableau Software: Starting from:$999.00/year

Pricing model: Subscription

Free Trial: Available

Data blending takes place when you mix information on one worksheet from several information sources. The information on common sizes is combined. Data Blending does not generate row levels, nor is it a means of adding fresh sizes or rows. We use this when we want to collect data from various sources and use the same worksheet. We don't have any joints as such, but only offer references to columns, such as main and external main relationships. For instance, the two data sources may share a date field in the combination of actual and target sales data. You must use the Date field on the sheet. Afterward, Tableau automatically links areas that have the same name if you move to a secondary source in the information window. You can identify a custom connection between areas if they do not have the same name. A default mix can look like a left outside join. The correct left and internal joints are likely to be reproduced by filtering nulls and turning the main source.

Context Filter

You can enhance efficiency by setting context filters when you apply filters to a big information source. A context filter is used first for the information source and only for the resulting documents are used the other filters. This sequence prevents each filter from being applied to each information source record.

A context filter may be created to- Performance enhancement. If you set many filters or have a big information source, the query may be slow. To enhance efficiency, you can set one or more context filters.

Create a numerical or N-top dependent filter–a context filter can only be set to include interesting information and then a numeric or N-top filter can be set.

Dual axis

Multiple steps can be compared using dual axes, two separate axes laid up on top of each other. When two measures are measured in distinct scales, double axes are helpful. For instance, the following perspective displays Dow Jones and NASDAQ closing time values. Drag the field to the right of the perspective and drop it if you see a black dashed line to add the measurement as a two-axis. In the field menu, you can also pick the Dual Axis.

The two axes are separate but the layout of the marks is the same.

A perspective that displays key progress indicators (KPIs) can readily be created. To do so, you can finish the following assignments: With the areas to be measured, create the base perspective. Construct a calculated field that sets out the figure you are measuring for the information that you evaluate. The Tableau uses forms specifically intended for KPIs. Two steps are taken to create a calculated field:

The first step includes-

• Click the drop-down to the right of Dimensions on the Data pane and select “Create > Calculated Field” to open the calculation editor
• Name the new field and create a formula. Take a look at the example.

The below example shows how to build a KPI view that shows a green checkmark for any sales figure over $125,000, and a red X for any sales figure under$125,000.

Heat Map: Heat map is a sort of viewing instrument that is very suitable for comparing various categories. With the help of colors and sizes, it allows you to compare one or several sizes and up to two measurements against dimensions. The design is comparable to a text table with color-coded values. A broad range of data can be found rapidly on the thermal map. In a heat map, a color can be determined by one criterion and the size can be allocated by another.

The below example shows sales and profit for the distinct categories and subcategories of goods in all areas. Visualization analysis: the profit is shown in color and varies from red to loss to yellow to profit. Total sales are shown by the dimensions.

The output of distinct products in distinct areas is therefore very simple to comprehend, at one glance only by looking at the heat map.

Tree Maps: Treemaps in Tableau, which appeared in release 8.0, are a fairly fresh function. A "treemap" is a sort of diagram that shows the relations through rectangles in a hierarchy and/or in part. These rectangles are nestled in the event of hierarchy (tree-structured) information. The view room is split into large and ordered rectangles. The measurements are ordered. Nested rectangles mean that hierarchic concentrations in the information are expressed in bigger (above hierarchical) rectangles that contain lower (below hierarchical) rectangles. The rectangles on the treemap range between the top-left corner of the diagram and the lower right-hand corner, with the biggest rectangle located at the top-left corner.

To generate such a map, a treemap with 1 or more dimensions and up to 2 measures are used.

A below example shows sales and profit for distinct categories and subcategories of goods in all areas.

Visualization Analysis: Profit (colour) and product sales (size) are provided at the level of category and sub-category. When the node is larger, sales in that state are higher. Likewise, the greener the node, the more benefit there is.

Aggregation is referred to as the method of viewing numeric values or measures at greater and more resumed information rates. When a measure is placed on a shelf, Tableau adds the information automatically, normally by adding it in sum. The aggregation applied to a field can be determined easily, since the feature always appears on the shelf before the field name. Sales become, for instance, SUM(Sales).  You can only add measures for relational data sources using Tableau. Only aggregated data is contained in multidimensional data sources. Only Windows supports multidimensional information sources in Tableau.

According to Tableau, the disaggregating of your information allow you, when evaluating steps that you may want to use separately and dependently in the perspective, to see every line of the information source that is helpful. For instance, you can analyze the results of a product satisfaction survey along a single axis with the age of participants. You can add the age to determine the median age of respondents or broken down information to determine the age of respondents with the item most satisfied.

Tableau offers numerous methods to generate a story. Each point of story may be based on a different view or dashboard, or the whole story may be based on the same visualization, seen at various stages, with filtered marks and annotations. It is possible to create a business case with story or simply tell a series of occurrences.

• Click the New Story tab.

• Select a size for your story in the lower-left corner of the display. Select or set custom pixel-size from one of the predefined dimensions.

• Your story receives its title by default from its name. Double click on the headline to edit it. You can alter the font, color, and alignment of your title too. To see your modifications, click Apply.
• Drag a sheet from the story tab at the left and put it into the middle of the view to begin constructing your tale. Click add a title in order to summarize the story.

• Drag a text item into your story worksheet and type your review to highlight the main takeover for your spectators.
• You can alter a filter or type a field on the viewer in order to emphasize the primary concept of this tale by clicking on Update in the navigator box and then save your modifications.

In web pages, blogs, wiki pages, web applications, and Intranet portals you can include interactive tableau views and dashboards. Embedded views update with the modifications underlying information or with their Tableau Server workbooks updated. Embedded views obey the same limitation on Tableau Server licensing and authorization. This means that the user who has access to the perspective must also have a contact with Tableau Server to view a tableau perspective that is integrated in the webpage.

Alternatively, a Guest account is accessible if your company utilizes a core permit from Tableau Server. This enables individuals in your organization, without having to sign up for the server, to view and communicate with tableau views built into web pages. To find out if your guest user is activated for the website that you post, please contact your server or site manager.

To integrate opinions and modify their default appearance, you can make the following:

• Get your embed code with a perspective: The Share button at the beginning of the perspective contains embed code that you can copy and paste into your site.
• Customize the embed codes: The embed codes can be customized using parameters that control the toolbar, tabs and more (The Share button doesn't appear in the embedded views when the showShareOptions parameter is changed to false). See Embed Code parameters for additional data.
• Use the JavaScript tableau API: In web applications, web developers may use JavaScript tableau objects. See the Tableau Developer Portal for access to the API, paperwork, software examples and the developer community.

The following is an example of the dashboard that refreshes every 5 seconds.

You just need your API src and your URL server to match.

<!DOCTYPE html >
< html lang="en ">
< title >Tableau Refresh Example </title >
< script type="text / javascript" src="http:/*servername*/ *Java script libraray Path*/tableau v8.js"></script >
< div id="tableau_Div"></div >
< script type='text / javascript' >
var exampleDiv= document.getElementById("tableau_Div)";
var url=" http:/*servername(/*view path *";
var options={
hideTabs: True,
width:"100%",
height:"1000px "
};
var viz= new tableauSoftware. Viz(exampleDiv, url, options);
setInterval (function)({ viz.refreshDataAsync()},5000);
</script >
</body >
< /html >

## Description

Tableau is a fast-growing data visualization too. It is very popularly used in the Business Intelligence industry, as it simplifies raw data into easy, understandable format. The visualisations formed by Tableau are in the form of worksheets and dashboards. Non-technical users can create a customised dashboard as well, no coding is required for the same. The best features include data blending, collaboration of data and real-time analysis.

Candidates can opt to become a Tableau Developer, Business Intelligence Developer, Tableau Analyst, etc.
According to Ziprecruiter.com, professionals who are working as a Tableau Developer make an average of \$107,311 per year.
Top companies who use Tableau extensively are ZS Associates, Tableau software inc., Verizon, etc.

The following is a collection of the most commonly asked tableau interview questions by interviewers. It’s important to be prepared to respond effectively to the questions that employers typically ask in an interview. Since these tableau interview questions are commonly asked, your prospective recruiters will expect you to be able to answer all of them. These tableau interview questions will increase your confidence to ace the next interview.

Going through these interview questions for tableau will help you land your dream job and will definitely prepare you to answer the toughest of questions in the best way possible. These basic and advanced level tableau interview questions are suggested by experts and have proven to be of great value. A few tricky questions are also discussed in the following sections, starting from the intermediate level.