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The limitations of using Tableau are:

• Not cost-effective: Tableau is not that cost-effective when we compare it well with the other available data visualization tools. In addition to this, it has software upgrades, proper deployment, maintenance, and ALSO training PEOPLE for using the tool.
• Not so secure: When it comes to data, everyone is extra cautious. Tableau focussed on security issues but fails to provide centralized data-level security. It pushes for row-level security and creates an account for every user which makes it more prone to security glitches.
• BI capabilities are not enough: Tableau lacks basic BI capabilities like large-scale reporting, building data tables, or creating static layouts. It has limited result-sharing capabilities, EMAIL notification configuration is limited to admins, and the VENDOR doesn’t support trigger-based notifications.

Load testing in Tableau is done to UNDERSTAND the server’s capacity with respect to its environment, DATA, workload, and use. It is preferable to conduct load testing at least 3-4 times in a year because with every NEW user, upgrade, or content AUTHORING, the usage, data, and workload change. 

Tabjolt was created by Tableau to conduct point-and-run load and performance testing specifically for Tableau servers. Tabjolt:

• Automates the process of user-specified loads
• Eliminates dependency on script development or script maintenance
• Scales linearly with an increase in the load by ADDING more nodes to the cluster

DATA blending is viewing and analyzing data from multiple sources in ONE place. PRIMARY and secondary are two TYPES of data sources that are involved in data blending.

TABLEAU WORKSHEETS contain VARIOUS named ELEMENTS like columns, rows, marks, filters, pages, etc. which are called shelves. You can PLACE fields on shelves to create visualizations, increase the level of detail, or add context to it.

Groups are CREATED to visualize larger MEMBERSHIPS USING dimensions. Groups can CREATE their own fields to categorize values in that specific DIMENSION.

SETS are custom fields created as a SUBSET of the data in your Tableau desktop. Sets can be COMPUTED based on CONDITIONS or created manually based on the dimensions of the data source. 
For example, A set of customers that earned REVENUE more than some value. Now, set data may update dynamically based on the conditions applied. Learn More

The following data TYPES are supported in Tableau:

The SUPPORTED file extensions used in TABLEAU Desktop are:

• Tableau Workbook (TWB): contains all worksheets, story points, dashboards, etc.
• Tableau Data SOURCE (TDS): contains connection information and METADATA about your data source
• Tableau Data Extract (TDE): contains data that has been extracted from other data sources.
• Tableau Packaged Workbook (TWBX): contains a combination of the workbook, connection data, and metadata, and the data itself in the form of TDE.  It can be zipped and shared.
• Tableau Packaged Data Source (TDSX): contains a combination of different files.
• Tableau Bookmark (TBM): to earmark a specific worksheet.

There are TWO types of data connections in Tableau:

LIVE: Live connection is a dynamic way to EXTRACT real-time data by directly connecting to the data source. Tableau directly creates queries against the database entries and retrieves the query results in a workbook.

EXTRACT: A snapshot of the data, extract the file (.TDE or .hyper file) contains data from a relational database. The data is extracted from a static source of data like an Excel Spreadsheet. You can schedule to refresh the snapshots which are DONE USING the Tableau server. This doesn’t need any connection with the database.

Tableau is pretty similar to SQL. Therefore, the types of joins in Tableau are similar:

• Left Outer Join: Extracts all the records from the left table and the MATCHING rows from the RIGHT table.
• Right Outer Join: Extracts all the records from the right table and the matching rows from the left table.
• Full Outer Join: Extracts the records from both the left and right tables. All UNMATCHED rows go with the NULL value. 
• Inner Join: Extracts the records from both tables.

Learn More

Aggregation of data means displaying the measures and dimensions in an AGGREGATED form. The aggregate functions available in the Tableau tool are:

• SUM (expression): Adds up all the values used in the expression. Used only for NUMERIC values.
• AVG (expression): Calculates the average of all the values used in the expression. Used only for numeric values.
• Median (expression): Calculates the median of all the values ACROSS all the RECORDS used in the expression. Used only for numeric values.
• Count (expression): Returns the number of values in the SET of expressions. Excludes null values.
• Count (distinct): Returns the number of unique values in the set of expressions.

Tableau, in fact, lets you alter the aggregation type for a view.

Disaggregation of data means displaying each and every data field separately.

Tableau’s specialty LIES in displaying data differently either in continuous format or discrete. Both of them are mathematical terms used to define data where continuous means without interruptions and discrete means are individually separate and distinct.

While the BLUE color INDICATES discrete behavior, the green color indicates continuous behavior. On ONE hand, the discrete view defines the headers and can be easily SORTED, while continuous defines the axis in a graph view and cannot be sorted.

Image - tableau.com

In Tableau, when we connect to a NEW data source, each field in the data source is either mapped as measures or dimensions. These fields are the columns defined in the data source. Each field is ASSIGNED a dataType (integer, string, etc.) and a role (discrete dimension or continuous measure).

Measures contain numeric values that are analyzed by a dimension table. Measures are stored in a table that allows storage of MULTIPLE records and contains FOREIGN keys referring uniquely to the associated dimension tables.

While Dimensions contain qualitative values (name, dates, geographical data) to define comprehensive attributes to categorize, segment, and reveal the data details.

The parameter is a variable (numbers, strings, or date) created to replace a constant value in calculations, filters, or reference LINES. For example, you create a field that returns true if the sales are greater than 30,000 and false if otherwise. Parameters are USED to replace these numbers (30000 in this CASE) to dynamically set this during calculations. Parameters allow you to dynamically modify values in a CALCULATION. The parameters can accept values in the following options:

• All: Simple text field
• List: List of possible values to SELECT from
• Range: Select values from a specified range

Tableau like other BI tools has a range of products:

• Tableau Desktop: Desktop product is used to create OPTIMIZED QUERIES out from pictures of data. Once the queries are ready, you can perform those queries without the need to code. Tableau desktop encompasses data from various sources into its data engine and creates an interactive DASHBOARD. 
• Tableau Server: When you have published dashboards USING Tableau Desktop, Tableau servers help in sharing them throughout the organization. It is an enterprise-level feature that is installed on a Windows or Linux server. 
• Tableau Reader: Tableau Reader is a free feature available on Desktop that lets you open and views data visualizations. You can filter or drill down the data but restricts editing any formulas or performing any kind of actions on it. It is also used to extract connection files. 
• Tableau Online: Tableau online is also a paid feature but doesn’t need exclusive installation. It comes with the software and is used to share the published dashboards ANYWHERE and everywhere. 
• Tableau Public: Tableau public is yet another free feature to view your data visualizations by saving them as worksheets or workbooks on Tableau Server.

The basic difference between the traditional BI tools and Tableau lies in the efficiency and speed.

• The architecture of Traditional BI tools has hardware limitations. While Tableau does not have any sort of dependencies
• The traditional BI tools work on complex technologies while Tableau USES simple associative search to MAKE it dynamic. 
• Traditional BI tools do not support multi-thread, in-memory, or multi-core COMPUTING while Tableau supports all these features after integrating complex technologies. 
• Traditional BI tools have a pre-defined data view while Tableau does a predictive analysis for business OPERATIONS.

Data visualization is a way to represent data that is visually appealing and interactive. With advancements in technology, the number of business intelligence tools has increased which HELPS users understand data, data sets, data POINTS, charts, GRAPHS, and focus on its IMPACT rather than understanding the TOOL itself.