The three expressions supported by Tableau to traverse levels of detail are: The independent fields that cannot be aggregated are considered as Dimensions and those fields that can be aggregated and are context-dependent are referred to as Measures.įor example, consider the Superstore dataset in which Region, Year are dimensions that provide context to add meaning to the Sales figure, which is a summarizable measure. It classifies the data into Dimensions and Measures. One of the most popular data visualization tools proved to be the best in visual-based data exploration.Ī brief description of key concepts to work is: 1. Support for semantic visualization to perform an automatic selection of suitable visualization primitives such as line charts, bar charts, scatter plots, Tree diagrams, etc., for nominal, ordinal, and numerical data. Integration of view manipulation features like slicing and dicing, roll up to the required level of detail, filtering the data to help in detailed explorative data analysis.ĥ. Cloud data storage like Oracle Cloud, AWS and Microsoft Azure, etc.Ĥ.Unstructured data in NoSQL databases like MongoDB, Couchbase, etc.Semi-structured data like XML files, JSON payloads.Structural data as in Relational Databases (Oracle, MySQL, PostgreSQL).Ability to handle heterogeneous data by possessing data-connectors or parsers for various sources that hold or store.
Scalability to the rapidly growing data size and to the increased data complexity comprising scalar, vector, and tensor data types without compromising the performance of the tool.ģ. First, ease use of tool functionalities avoids the need for in-depth training on technology for the creation or interaction of views in order to derive valuable insights.Ģ. The salient features offered by Data Visualization tools are:ġ. Hadoop, Data Science, Statistics & others As a result, the requisite efforts and time to create and maintain graphics packages and the level of expertise to understand graphics jargon is greatly reduced.
The overwhelming growth rate of available data volumes and the pressing need for the decision-makers in all domains of business and research to make quick and accurate decisions increased the scope for data visualization tools to understand data with graphics. It helps to explore data, visualize and prepare reports for the same data. It is also used in reporting and is mostly called a reporting tool. Visualizations are made in the form of dashboards, and data should be represented in tabular format. It is mostly used in the Business Intelligence industry, and raw data is simplified easily to any format understandable by the users. A data visualization tool developed in Salesforce to connect with any database, be it SQL or MongoDB, and interact freely is called Tableau.
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