I will hire a person to perform a research task related to a large data set (Big Data).

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Marek Bąk
Employer
1 deal
Job category:
Data processing
Expected budget:

Negotiable

Published:
Finished

Job description

A task related to a large data set (Big Data).

Task description:

Choose a dataset that is large in size and diverse. It can be a set of data downloaded from the Internet or self-created data. The data can be textual, numerical or a combination of both.

Data operationalization method:

Use an appropriate method to operationalize Big Data. This can be the method discussed in class, such as Gephi, Wordij, Brand24, Voyant Tools or any other method that will allow you to analyze large data sets. Make sure that the method you choose will allow you to generate little obvious inferences and deepen your understanding of the data.

Data analysis and inference:

Conduct an analysis of the selected dataset using the selected method of operationalization.

Accurately describe the data analysis process and present the resulting conclusions.

Separate conclusions that reflect the research process and include insights that are not so obvious.

Develop recommendations for using this type of data in further analysis.

The report should include:

A description of the selected dataset, including its characteristics, size and diversity.

A description of the chosen method of operationalizing the data and justification for the choice.

A description of the data analysis process and a presentation of the conclusions reached.

Conclusions that reflect the research process and generate little obvious insights.

Recommendations for the use of this type of data in further analysis.

The job in figures:

Description of the selected dataset, including its characteristics, size and diversity. Description of the selected method of data operationalization and justification of the choice. A description of the data analysis process and presentation of the conclusions reached. Conclusions that reflect the research process and generate little obvious insights. Recommendations for the use of this type of data in further analysis.

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