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Individual Contribution Report

Pradeep Peddnade Id: 1220962574

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Reflection:

My overall role in the team was Data Analyst where I was responsible for combining

theory in the group and practices to make and communicate data insights that enabled my

team to make informed inferences regarding the data. Through skills such as data analytics and

statistical modeling, my role as a data analyst was crucial in mining and gathering data. Once

data is ready, performed exploratory analysis for native-country, race, education, and work

class variables of the dataset.

The other role was charged with as a data analyst in the group was to apply statistical

tools to construe the mined data by giving specific attention to the trends and the various

patterns which would lead to predictive analytics to enable the group to make informed

decisions and predictions.

Another role that I did for the group was to work on data cleansing. The specific role

involved managing data though procedure that ensures data us properly formatted and

irrelevant data points are removed.

Lessons Learned:

The wisdom that I would share with others regarding research design is to ensure that

the design is straightforward and aimed towards answering the research question. Having an

appropriate research design will assist the group to answer the research question effectively. I

would also share with the team that it is very appropriate to consider at the time of data

collection from sources and analyze the data into something that the researcher the team

would want to consider. On how to best apply them is to consider that it is appropriate for the

team to ensure that the data is analyzed appropriately and structured appropriately. Make sure

data is cleansed and outliers are removed or normalized.

From the group, we can conclude that the research was an honest effort that was

established to identify how the lessons learned are beyond the project. The data analytics skills

ensured that the analyzed data was collected from the primary sources of data, this prevent

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the group from the biasedness of another research that was previously conducted. In this, data

world there is unlimited data choosing right variable among the data to answer the research

questions is very important by using correlation and other techniques.

Assessment:

Additional skills that I learned from the course and during the project work is choosing

the visualization type and variables from data set, which is a very important in the analysis of

data. Through this skill, I was able to conceptualize and properly analyze and interpret big data

that requires data modeling and management. Despite that is through the group that I was able

to develop my communication skills since the data analytic role needed an excellent

communicator who would interpret and explain the various inferences to my group.

Group members are in different time zones, scheduling a time to meet was

strenuousness. Everyone in the team was accommodating.

Future Application:

In my current role, I will analyze the metrics of the cluster and logs to monitor the health

of the different services using Elasticsearch Kibana and Grafana. The topics I learned in this

course will be greatly useful and I can apply it in building metrics based Kibana dashboard for

Management to see the usage and cost incurred for each service running in the cluster. And I

will use statistical methods on picking the fields interested among thousands of available fields.

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