A tool for data visualization developed within Salesforce to connect to any database, whether SQL or MongoDB, and allow for interaction is known as Tableau. It is primarily used within business intelligence. The business intelligence industry and raw data can be easily converted into any format users understand. Visualizations are created as dashboards, and data should be displayed in tabular form. It can also be used for reports and is generally referred to as an instrument for reporting. It assists in exploring data and visualizing and creating reports using the same information. It is designed using C++.

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The exponential growth rate of data volumes available and the urgent necessity for decision-makers across all research and business areas to make fast and precise decisions have increased the possibility of using tools to visualize data to comprehend data using graphics. In the end, the time and effort required to develop and maintain graphics programs and the amount of knowledge required to grasp the language of graphics are greatly reduced.

The main features offered to users of Data Visualization tools are:

1. First, the simplicity of the tools' functions eliminates the requirement for extensive training on the use of technology in creating or interacting viewpoints to gain insight.
2. Scalability to rapidly increase data volume and complex data types, including vector, scalar, and tensor data types, without impacting the program's speed.
3. Ability to handle heterogeneous information by using data connectors and parsers for different sources of data that are stored or held.

• Structural data is stored in Relational Databases (Oracle, MySQL, PostgreSQL).
• Semi-structured information like XML file formats, JSON payloads.
• Unstructured data is stored in NoSQL databases such as MongoDB, Couchbase, etc.
• Cloud data storage includes Oracle Cloud, AWS and Microsoft Azure, etc.

4. The integration of manipulation functions like slicing and cutting, rolling up to the required degree of detail, and filtering the data to aid in an in-depth analysis of the data.
5. The support for semantic visualization allows an automated selection of the most suitable visualization tools like bar charts, line diagrams, scatter plots, Tree diagrams, and more for nominal, ordinal, as well as numerical data.

Several renowned tools for visualizing data have proven to be the most effective for data exploration using visuals.

Working using Tableau

A brief overview of the key ideas to work on is:

1. Dimensions and Measures

It categorizes information into Dimensions and Measures. The fields that are not independent and cannot be aggregated are classified as Dimensions, while those that can be aggregated and are context-dependent are known as Measures.

2. Level of detail

The three expressions used by Tableau to navigate depths of detail are:

• Include: Aggregation is performed after grouping the INCLUDED list of dimensions fields.

• EXCLUDE: Aggregation is done after grouping dimension fields that aren't included within the EXCLUSION list.

• Fixed: Unlike Include and Exclude expressions, the FIXED aggregated values are unaffected, i.e., they remain in the same form regardless of the change in the dimensions (addition of a dimension or hiding the existing dimensions) within the display.

3. Parameters

Interactive visualization can be enhanced by adjusting a few elements of the visual view.

Common use-cases that require the use of parameters are:

• The inclusion of Top-N-Filters.
• Adjusting the size of bins for histograms.
• Reference line definitions for classification based on thresholds.

The list or range of values users may modify or select must be the same data described in the properties of the parameter.

The process used to determine the parameters utilized in Tableau includes the following steps:

• Create New Parameter Any time you input a constant in the creation of the view, you can select 'create a new parameter' to allow tuning of the relevant aspect of the published view.
• Show parameter control Parameters such as Filter box gauges, sliding bars, gauges, and more. The view shows the option to show parameter control by clicking on the parameter in the pane of parameters.
• Use Parameters to calculate: Values for parameters returned by the parameter control may be utilized to calculate, perform functions, or the form of logical statements, to offer users for display desired measures or statistics.

4. Sets

Sets are manually created or calculated conditionally from input data to allow for customized representation elements within the view.

The main features of these sets include:

• Dynamic Groups differ from categorical categories because a grouping is static and may be formed within the dimensions that have an extensive membership; they can be computed sets based on conditional logic defined on either dimensions or measures that dynamically categorize fields when the data underlying changes.
• Usability Although filters can conditionally support the categorization of dimensions, as well as measures, the use of the filters is limited to the dimension that is in the workbook. Sets can be stored and used in calculations or as an element in a different set.
• Priority Order: Sets have higher precedence over dimension filters and filtering measures in the queries pipeline so that the values displayed for users to select from the filter of view will be the most optimal per the set definition.

5. Table Calculations

Table Calculations operates on data that is locally visible in Tableau. It uses data locally visible in Tableau view to calculate metrics like running totals within sub-categories, cumulative sums moving average with adjustable window length and the order of fields, percent variations, etc.

Tableau Products

Different products are classified into:

• Visualization Development products include Tableau Desktop and Tableau Public (Desktop).
• Visualization Publishing products include Tableau Server, Tableau Reader, Tableau Online, and Tableau Public(Server).

1. Tableau Desktop

Tableau Desktop allows users to build, format, and integrate different interactive dashboards and views with the help of the many visualization techniques. It also allows live-up-to-date analysis through querying data in live-connected and native databases.

The visualizations created are released through publishing with the Tableau Packaged Workbook with extension .twbx that consists of:

• Tableau Workbook with extension .twb is an XML document describing visualization templates.
• Tableau Data Extracts have an extension .tde file that is a compressed data file source.
• Other supporting files like images etc.

2. Tableau Server

Tableau Server is a reliable, well-managed, secure, and well-controlled enterprise environment that allows you to share and publish visualizations developed with Tableau Desktop. It acts as a central repository of diverse data sources inside the engine for data, user security roles and access information, and also every visualization across the enterprise.

3. Tableau Public

Tableau Public is a cloud-hosted free version with limitations on tool usage and comes with two other products, Tableau Public (Desktop) and Tableau Public (Server). The views are built in Tableau Public (Desktop) which are then saved and uploaded to Tableau Public(server).

The main limitations of Tableau Public are:

• Locally accessible data extracts are the only sources of data that are supported.
• The maximum amount of rows that can be entered is one million.
• In contrast to Tableau Desktop, users cannot save their workbooks locally. They can only save the workbook to Tableau Public(Server) which is available to all users.

4. Tableau Online

Tableau Online is a cloud-hosted view-sharing platform that can connect to cloud-hosted databases, such as Amazon Redshift, Google BigQuery, and Google BigQuery. Extracts are scheduled to refresh, and live connection to on-premises datastores can be accomplished with the tableau bridge.

• The primary benefit of the cloud base solution is the reduction of the infrastructure costs for users, as it eliminates the associated patching, upgrades, and maintenance tasks.
• Contrary to Tableau Server, editing workbooks and visualizations require a connection to a data server to be performed and are restricted by the limit on rows.

5. Tableau Reader

It's a desktop application that allows users to access and perform view interactions such as roll-up and drill-down from OLAP cubes and filters based on dimensions. However, it cannot edit the embedded content of the published visualizations included in Tableau Desktop.

Conclusion

It provided a great customer experience and established its company as an industry leader in Business Intelligence (BI) vendor space. The amazing capability of translating raw data into visual representations was made possible by providing a broad set of data connectors and an easy-to-access collection of visualization basics. It aims to support machine-learning-enabled data preparation and smart data discovery by changing customer needs and growing user expectations. If you need assistance in learning this tool, you would need to enroll in a Training program, which can make you job-ready and will teach you this skill. You can check out the Tableau Training for understanding. 

In addition, it is focused on addressing the shortcomings in features for enterprises. These can be found below:

• Achieving a high-performance integration of massive and complicated data from diverse data sources must be considered.
• The goal is to enhance the capability to manage large in-memory extracts by replacing TDE data formats with an in-memory engine named Hyper.
• Scheduling based on events and conditional alerts to be highlighted.
• The development of API interface services allows for greater flexibility.
• The packaging is simplified and easier to allow for massive deployments of customers with lightweights.