Data Analytics & Visualization

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Course Outline Big data and analytics promise to change virtually every industry and business function this new decade. As businesses are constantly being faced with massive amounts of data in structured and unstructured forms, effective data analysis and visualization has become imperative today. While data analytics tools help extract valuable information from raw and unstructured data and represent it in an intelligent manner, data analysts must learn how to leverage on these tools and to adopt a comprehensive framework to transform data into valuable assets to assist organizations in improving revenues, reducing costs, and in seizing opportunities. Keeping in mind the significance of data analytics to businesses, course participants can pursue this professional certification that can help build their skills in this arena, enabling attractive job prospects. Course Objectives By the end of the course, participants will be able to: * Examine the importance of data analytics in different professional fields * Recognize how data and analytics can be used to extend different professional domains * Recognize the importance of making room for empirical inquiry when solving problems * Examine characteristics of an analytical mindset in business contexts * Evaluate a framework for making data-driven decisions with big data * Recognize factors that make data useful * Transform data from unstructured to structured * Examine fundamental principles that underlie data visualizations * Identify use cases for different charts, and then build those charts * Create basic and advanced charts in Microsoft Excel and Tableau * Add dimensions and analytics to charts * Discuss how data science will shape the future of analytics and decision-making​ Target Audience Data analysts, marketers, accountants, controllers, business executives and any other person assuming a business functions that requires data-driven analysis for decision-making. Key Topics The key topics covered in the course are: * Big data * Data analytics ​* Empirical inquiry * Developing analytical mindset * FACT framework * Data types ​* Structured versus unstructured data ​* Data relationships * Data visualization * MS Excel Pivot tables * MS Excel Pivot charts ​* Visualization in Tableau * Communicating analysis an visualizations to target audience Examination * Two assignments * Final exam

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