An Introduction to Analysis of Data

Analysis of data is a process with the help of which it is possible to inspect, clean, transform and model the data so as to discover important information that helps to arrive at a conclusion and support in decision making. In an analysis of data, there are many facets and various techniques are applied. Analysis of data is generally divided into three important types. They are confirmatory data analysis, exploratory data analysis, and most importantly descriptive statistics. The most important thing in the analysis of data is the process of data cleaning. Data cleaning is the process by which the outlier, as well as other unwanted information, is corrected. Thus, analysis of data deals with various things that are very important for a business. Some of those essential things are aggregation, slicing, dicing, disaggregation, etc.

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Various Phases in Analysis of Data

The analysis of data consists of five important phases which are described as follows:

  • Data Cleaning: Data cleaning is the first phase of the data analysis process. In this step, a various process such as deduplication, record matching as well as column segmentation is usually done which helps in cleaning the raw data and make it useful information.
  • Quality Analysis: In this phase, various descriptive analyses such as mean, median, standard deviation, etc. are analyzed. In these steps, normality histograms such as skewness, kurtosis, frequency, etc. are compared with the variables of the data set.
  • Quality of Measurement: This is the third step in the analysis of data. In this step, the confirmatory factor analysis and analysis of homogeneity.
  • Summarizing and displaying data: In this step, various types of data are summarized and displayed. This step plays a vital role in gathering data from various sources which helps in building a better model and gaining huge actionable insights.
  • Optimizing and repeating: It is always essential to repeat the process so that you can generate an accurate prediction. Thus, this step can help you in reaching the goal, monitoring, and reporting consistently.

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Generally, every student faces lots of problems while they attempt to write an assignment, especially on some complex topic like data analysis. It is not easy to write assignment papers on data analysis as it is completely an interdisciplinary subject. What the student generally do is that they try themselves to complete the assignment and when they cannot do they submit the assignment inappropriate for which most of the assignments of the students get rejected and given low marks. Moreover, just the subject-related knowledge is not enough. You need to take care of the following aspects too:

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