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Practical Connection 2

I have been working as a Full Stack .Net Developer for 3 years for an insurance company, by developing different web applications which are used by other clients like Cigna, Hartford. Previously I was working with an airline company on a training management system project in which we have to collect data from different sources and load into the application process all the different data files and give the output back to the user. This is all done through C# code and stored procedures. When working with this data, I felt there is a lot of unwanted information that was collected, which is not necessary for generating the output. Instead, we can clean the raw data and then start processing it would help developers to efficiently, and also the performance of the application will also increase. With this thought in mind, slowly, I wanted to learn more about how the data mining process works, how the data storage works, and how we can attract the users with the data visualization. I felt sticking to one single technology will not help in my career growth. I must have badges with multiple skills, and so I decided to learn more about data mining.

In addition, I have also done a project during my bachelor’s on the Performance comparison between the variance of the K-Means Algorithm. I have Gathered five clustering algorithms, developed code for these five algorithms using MATLAB. Five algorithms, such as K-means, Kruskal’s, etc., are applied on two datasets, such as the Iris and Wine data set, and compared the efficiency of the algorithms using different parameters. Among all the algorithms, I felt the K-Means algorithm is the have better computational performance. By taking initial points in the cluster, finding the centroid for these points, which is called as K-clusters, and repeating the same process until the values of the centroid do not change.

However, during my first semester, I was assigned to an Analyzing and visualizing data course. I have learned how to use the data reporting tools like Tableau and learned the basics of R programming language. I have taken the Zomato Restaurants dataset and performed various techniques like data extraction, data cleaning, data restoration, data transformation on the raw data. I have also created charts on the Zomato data set like a pie chart, bar chart, heat map, spatial chart, etc., using both Tableau and R programming language. By looking into the data, I have drawn a few predictions on the editorial perspective, like angle framing and focus. I have also learned on what basis data need to be selected based. We must ensure data must be trustworthy by always collecting data from a trusted source. It must be accessible to the audience, and another important factor is visualization must be elegant so that it is easy for the audience to draw conclusions based on the picture.

To summarize, in this course, I will do a deep dive into data mining, its concepts, its importance, and how it is used throughout the world. With a master's in data mining program, I can apply these concepts more efficiently in a real-time environment. Instead of just simply working on the raw data, I can involve myself in data mining and data analysis work going forward.

References:

· Minewiskan. “Data Mining Concepts.” Microsoft Docs, docs.microsoft.com/en-us/sql/analysis-services/data-mining/data-mining-concepts?view=sql-server-2017.

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