{"id":12540,"date":"2022-01-24T17:01:00","date_gmt":"2022-01-24T11:31:00","guid":{"rendered":"https:\/\/www.mygreatlearning.com\/blog\/beginners-guide-to-tableau-desktop\/"},"modified":"2024-09-27T14:56:52","modified_gmt":"2024-09-27T09:26:52","slug":"beginners-guide-to-tableau-desktop","status":"publish","type":"post","link":"https:\/\/www.mygreatlearning.com\/blog\/beginners-guide-to-tableau-desktop\/","title":{"rendered":"Tableau Tutorial: Beginners Guide to Tableau Desktop"},"content":{"rendered":"\n

Data Visualization and its Importance<\/strong><\/h2>\n\n\n\n

Data Visualization<\/a> is a graphical representation that explains the relationship and behavioural patterns in the data. The goal is to communicate the data analysis through easy visualizations effectively and aesthetically.<\/p>\n\n\n\n

With the advent of Industrial Analytics, a paradigm shift has been observed in data-driven decisions. Analytics inevitably play a paramount role in effective decision enablement. Data visualization is an integral part of any analytics, including Data Science. Data visualization compresses a huge amount of virtual data, either big or small, that is difficult for the human brain to grasp and represent the essence of the data. The visual format is easier to understand and identify trends, correlations, anomaly detections, and pattern recognition<\/a> in data analytics.<\/p>\n\n\n\n

An increase in data analytics<\/a> and data integration has made way for more specialized visual analytical tools<\/a>. Typically, flat files like excel are very good with data analytics and visualizations but come with their limitations. Specialized software leverage easy operations on both static and live data feeds. Huge computational speeds, self-service functions, and interactive visualizations facilitate users to pull up a report or dashboard and freely drill down to granular levels of information. Integrations and huge data computation from multiple sources are now possible without the knowledge of coding.<\/p>\n\n\n\n

\n