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Role of Data Analysts in Data Analytics

by Linda D. Yelverton

Data Analytics

Role of Data Analysts in Data Analytics

Data Analytics is not only about collecting data and creating reports. There are different roles, which are required in the process of collecting, interpreting and presenting data. Data Analysts also have the important role of sharing their knowledge with the users. They provide tips to analyze the data and help users in gaining insights into the processes.

Data Analysis has to be done properly and using the right analytical approach. In order to gain this knowledge, a user must always learn the various types of data which can be collected and how it can be analyzed. Data Analysis is about analyzing the data collected.

Analysis usually does not work on its own. It is vital to get a good computer with an excellent internet connection so that the analysis can be conducted by itself. There are a number of methods which can be used for data collection and this includes, sampling, basket design, dispersion modeling, multivariate analysis, psychometric methods, discrete random variables, clustered random effects and hierarchical models.

In some cases, Statistics is the most important role to play. Statistics allows the user to find out factors which help determine the reliability of the data collected. For example, suppose a random sample is collected for the purpose of determining the level of diabetes in a particular area. The probability of finding a high or low number of people who have diabetes in the area is highly likely and the method of determining the probability of finding high or low numbers should be analyzed.

A Statistical Model will help identify the factors that lead to the probability of the results being in one of the two categories. Data analysts use statistical models to analyze and discover the factors that determine the data. This analysis has many uses and helps to identify the factors that lead to predictive results.

Data Collection and Analysis are two phases, which are also known as steps. These steps will be discussed in the following sections. Step One: Data Acquisition or the Gathering phase – The user wants to get the data that has been collected and has to be organized so that it can be appropriately analyzed. They should keep in mind that not all the data collected must be analyzed at the same time.

The data that has been collected must be in the correct format in order to be analysed. People using Data Analytics must always make sure that they capture the data in the correct format. This can be done by providing the data to a data analyst. Sometimes, after the user has collected the data, there is a need to save it in another format such as Excel to make it more easily available.

The next step needs to be based on the input of the user. The steps will be given in the following sections. Step Two: Interpreting or the interpreting phase – Now the user needs to understand the data that has been collected and interpret it.

The Data Analyst will ask the user to solve the analytical problems that were raised while analyzing the data. The inputs to the analysis are analysed using the three steps in order to determine the results. This stage is crucial and helps in providing the valuable information to the users.

The analysis of the data and results generated during the interpreting phase can help the user in the decision making phase. This is done by evaluating the data and come up with a decision. The user will then discuss the results with the analyst.

Data Analysis has to be done correctly and the analysis must be done using the right techniques. There are various online resources where users can seek help from qualified and experienced data analysts. Some of the most popular sites are: SuperPipe, SEOdata, Data.com and Data Factory.

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