Analysis Of Data

Data Analysis is a process of collecting, transforming, cleaning, and modeling data with the goal of discovering the required information.

Data Analysis is a process of collecting, transforming, cleaning, and modeling data with the goal of discovering the required information.

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The data analysts can choose data visualization techniques, such as tables and charts, which help in communicating the message clearly and efficiently to the users.

The analysis tools provide facility to highlight the required information with color codes and formatting in tables and charts.

Data Analysis Process consists of the following phases that are iterative in nature − The data required for analysis is based on a question or an experiment.

Based on the requirements of those directing the analysis, the data necessary as inputs to the analysis is identified (e.g., Population of people).

For example, if a clothing brand is trying to identify the latest trends among young women, the brand will first reach out to young women and ask them questions relevant to the research objective.

After collecting this information, the brand will analyze that data to identify patterns — for example, it may discover that most young women would like to see more variety of jeans.

Here are a few methods you can use to analyze quantitative and qualitative data.

The first stage of analyzing data is data preparation, where the aim is to convert raw data into something meaningful and readable.

This includes structuring the data as required for the relevant Analysis Tools.

For example, the data might have to be placed into rows and columns in a table within a Spreadsheet or Statistical Application. The processed and organized data may be incomplete, contain duplicates, or contain errors.