- Tableau Introduction
- Data Visualization
- Tools and features of Data Visualization
- Advantages and Disadvantages of Tableau
- Tools of Tableau
- Download and Installation process of Tableau
- Tableau – Data Terminology
- Tableau Architecture
- Difference between Power BI and Tableau
- Data Types in Tableau
- Tableau Navigation
- Tableau Aggregation
- Tableau String Function
- Tableau Logical Function
- Tableau Expression Function
- Tableau Joins
- Data Extraction In Tableau
- Data Blending In Tableau
- Tableau Sorting
- Tableau Filters
- Tableau Bar Chart
- Tableau Histogram
- Interview Questions And Answers Of Tableau Part 1
- Interview Questions And Answers Of Tableau Part 2
Tools and features of Data Visualization
There are technologies available that can help us analyze all of the data in a short amount of time. They’re already there; all we have to do now is choose the best information visualization tool for business needs.Users can engage with data via visualization techniques. Google, Apple, Facebook, and Twitter all use visualization tool to communicate better of its data and improve business processes.
Tableau, QlikView, FusionCharts, HighCharts, Datawrapper, Ploty, D3.js, and other data visualization tools are available.
Tableau is a tool for visualizing data. Graphs, charts, maps, and a variety of other graphics can be created. For visualizations, there is a tableau desktop application. A servers solutions allows users to view the results online and on mobile devices if the software is not installed in laptop or desktop.
Datawrapper is a simple visualization tool that doesn’t require any coding. We may quickly upload our data and generate and release a map or chart using it. Customized templates are accessible to completely integrate our visualizations on our site, as well as access to local area mapping.
Features of Data Visualization tools
The following are some of the most important aspects that Data Visualization tools provide:
- Firstly, itseasy of use of tool functions eliminates the requirement for in-depth technical knowledge in order to get insightful information from the development or engagement of view points.
- Flexibility to accommodate rapidly increasing data sizes and enhanced information variety, including scalar, vector, and exponential types of data, without harming the tool’s functionality.
- Owning personal information or parsing for numerous sources which hold or store integration of data allows the user to manage it.
- Relational database management systems use structural information (Oracle, MySQL, PostgreSQL).
- XML files and JSON packages are examples of semi-structured data.
- MongoDB, Couchbase, and other NoSQL databases store complex data.
- Oracle Cloud, AWS, and Microsoft Azure, among others, provide cloud – based system.
- View modification tools such as slicing and dicing, rolling up to the desired amount of precision, and sorting the data are all included to aid in comprehensive exploratory data analysis.
- Ability in conceptual visualization, which allows for the automatic selection of appropriate visualization primitives for conceptual, qualitative, and numerical data, including such flowcharts, bar graphs, scatter graph, Decision trees, and so on.
- And among the most widely used data visualization tools was shown to be the most effective in visual data analysis.