What is Tableau: Sense Perception
Data Visualization is the representation of data in the form of charts, figures, images to create different kinds of reports. There are many visualization tools in the market due to the current pressing need in the analytics platform to make data-driven decisions.
So, What is tableau? Tableau is one of the leading data visualization tools used to analyze the studies, research and findings for an assigned business problem and create highly advanced visualizations.
We use five basics senses to perceive the world around us. Sight is one of the most important sense perceptions which helps us to explore the world around us. Danish physicist Tor Norretranders proposed Bandwidth of Senses showing the comparison in computer terms at which each of the senses responds to outside stimuli. He proposed visual interpretation (sight ) at the highest bandwidth of 1250 MB/s.
As per him, sight processes information the fastest, which is 10 times faster than the next sense perception- touch. It shows the power of vision compared to other senses. This breeds the extensive need for visual insight for any kind of information. Likewise, any kind of research, analysis and findings is not complete without being visually acceptable by the stakeholders.
What is Tableau? : Introduction
Tableau is one of the most powerful and effective data visualization tools for communicating results as reports, charts and dashboard. It derives insightful, easily understandable and helpful business insights from raw business-centric data. We can use it as an exploratory and explanatory analytical tool due to its simple and efficient usability. In Tableau, we can quickly view, understand and analyze the data, change the data points and accordingly ask relevant and deep questions about the data. The strength of Tableau lies in its visually interpretive interface and easily accessible reports and dashboards. It can help the organization solve their data issues and subsequently come up with data-driven solutions and business insights.
What is Tableau ?: Visual Encodings
Visual encoding is simply the mapping of data to display elements or structures. We use visual encoding to build different images on the screen. Basically, we use the position like x and y coordinate to display visual structure. These are considered planar variable as it locates points in space. They work well with two variables but have limitations working with more than two variables.
Retinal variables are used to encode more than two variables in any data set. They have multiple options to encode data with more than two variables. Three dimension models (x,y,z coordinates) are not easily understandable. We can use retinal variables in these kinds of three-dimensional models too. The various retinal variables are as follows.
- Size: This is used to differentiate the quantitative data.
- Color hue: This is effectively used to differentiate categorical data.
- Color value: It differentiates the data based on color saturation.
- Shape: Different shapes used to separate categories.
- Orientation: This is used to differentiate between a set of data on the basis of orientation.
These are the attributes in preattentive processing to make the visualization more effective and understandable. This part of the perception helps us instantly recognize visualization parts and structures. It is a System 1 (Automatic) type of thinking and perception which happens without our conscious being in action. These attributes help us to determine which information catches the attention of the users. Thus it enables us to direct users’ attention towards the most important information in our visualization.
In the latest Gartner Magic Quadrant report in 2018, Tableau has been placed as the leading tool in the Business and Analytics platform. Tableau scores above others in big margin due to it’s intuitive and interactive visual analytical ability. This shows the importance of using tableau as the latest tool for analysis, visualization and communication.
The above data proves that Tableau is a market leader due to the successful usage by the customers to understand and consequently use the data.
- Tableau is simple to use and easy to learn. The learning curve is not steep and therefore intuitively helps naive users to explore data. Thus it helps in Data discovery.
- The strongest feature is as discussed above is the use of preemptive attributes using both planar and retinal variables which gives it a bigger edge over other contemporary visualization and analytics tool.
- We can create a variety of advanced visualizations using different charts and functions available in Tableau.
- Similarly, we can create reports and dashboards in tableau for valid business information.
- It can be used for disparate data sources whether be it different databases, warehouses or flat files.
What is Tableau?: Tableau Products
Let’s go through the various products of the Tableau suite.
Tableau desktop is the developer tool used to create and customize reports and dashboards. It provides connection to various databases and variety of file sources. We can use this for data analysis, storyboards, workbooks and more.
This is a sharing tool use to create and share reports and dashboards in any organization in a highly secure fashion. The visualizations are created in the desktop version and then published in the server. All the reports and dashboards can be accessed by logging into the server by authorized users through the cloud.
This is a public free tool offered by Tableau. It has all the developer functionalities of the desktop version. The reports and dashboards are published online and are accessible by anyone. This is used to store the reports for public use. Anyone can access and download the workbook.
This Tableau version is hosted on the cloud version of SaaS. It works in a highly secured environment. Organisations don’t need to spend on resources for hardware and maintenance and directly use this online version.
Tableau is a very powerful and effective Data Analytics and Visualization tool which is currently in extensive use due to the reasons discussed in the post. Still, Tableau needs to keep improving itself and not just keep basking in its own glory to keep itself on the path of success. One of the challenges for Tableau is how it is going to handle large datasets and Big Data. Only time will tell how much it is able to cope with the fanatic level of the data generated and still remain one of the better tools in the market. For now, we can rest assured if we are working on this tool is that we are doing the good work.
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