Data analysis is a process for obtaining raw data, and subsequently converting it into information useful for decision-making by users. And, it is a process of inspecting, cleansing, transforming, and modeling data to discover useful information, informing conclusions, and assist in decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains.
Data Analytics is the method of examining datasets to find trends and draw conclusions about the information they contain. Data Analytics courses will equip the learners to assist a firm in making better business decisions and assessing consumer patterns and satisfaction, leading to the development of finer products and services. The course syllabus is specifically designed to help learners acquire skills for how to set achievable goals in the business field.
This course is ideal for all working professionals. Prior programming knowledge is not required. It covers job-critical topics like data analytics, data visualization, regression techniques, and supervised learning in-depth via our Bootcamp learning model with live sessions by leading practitioners’ industry projects.
Big Data analytics is a process used to extract meaningful insights, such as hidden patterns, unknown correlations, market trends, and customer preferences. Big Data analytics provides various advantages—it can be used for better decision-making, and preventing fraudulent activities, among other things.
Types of Data Analysis are Text, Statistical, Diagnostic, Predictive, and Prescriptive Analysis. Data Analysis consists of Data Requirement Gathering, Data Collection, Data Cleaning, Data Analysis, Data Interpretation, and Data Visualization.
To improve your data analysis skills and simplify your decisions, execute these five steps in your data analysis process:
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