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Data Analysis


Data analysis is a method in which data is collected and organized so that one can derive helpful information from it. This type of data collection involves watching or observing something or someone. For example, Cane might observe how many people come to buy hunting licenses and note their age. Data analysis has two prominent methods: qualitative research and quantitative research. Each method has their own techniques. Interviews and observations are forms of qualitative research, while experiments and surveys are quantitative research. Data collection and analysis tools are defined as a series of charts, maps, and diagrams designed to collect, interpret, and present data for a wide range of applications and industries. There are many types of data analysis. Some of them are more basic in nature, such as descriptive, exploratory, inferential, predictive, and causal. Some, however, are more specific, such as qualitative analysis, which looks for things like patterns and colors, and quantitative analysis, which focuses on numbers.The process of data analysis uses analytical and logical reasoning to gain information from the data. The main purpose of data analysis is to find meaning in data so that the derived knowledge can be used to make informed decisions.

Four Type of Data analysis

  • Descriptive Analysis.
  • Diagnostic Analysis.
  • Predictive Analysis.
  • Prescriptive Analysis.

 Advanced Analytics helps you develop strategies that turn your data assets into a true competitive advantage. Our Advanced Analytics practice is supported by our Advanced Analytics Group, a highly skilled team with advanced degrees in fields ranging from statistics and applied mathematics to computer science, who apply state-of-the-art techniques, tools and technology to ensure that you derive powerful insights from your data.

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