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There are many data analysis tools available which you can use to work efficiently. These are mentioned below in the table.
| Type of assignment | Used For | Recommended Tools |
|---|---|---|
| Basic analysis and visualisation | For simple tasks like making charts, diagrams, organising, collecting and updating data, pivot tables, etc. | Google sheets, Ms Excel |
| Web analytics | To understand user engagement and website traffic. Used for checking performance metrics. | Google analytics |
| Business intelligence | Widely used for visualising data and making interactive dashboards. | Power BI, Tableau |
| Programming and advanced analysis | To do statistical analysis and more programming-based data analysis. | R, Python, SPSS, Stata, SAS |
These tools are widely used by our experts while offering data analysis assignment help to students. You can make use of these tools to work on your data analysis assignment and enhance its quality.
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If you use ChatGPT for a data analysis assignment, then your assignment might be rejected on the grounds of plagiarism. So it’s better to avoid depending entirely on AI tools. However, you can use them for understanding and learning difficult concepts.
Firstly, you should use the right tools for that, like R, Python, Excel, Power BI, Tableau, SQL, Tableau, etc. Then, you should focus on cleaning and arranging data properly. Incorporate a structured process like a 7-step data analysis process. All these things make data analysis easier.
They are defining the problem, collecting data, data preprocessing, analysing the data, evaluating outcomes, data visualising, and making data-driven decisions. If you need help with any of the steps, get our data analysis assignment help from experts.
Descriptive, diagnostic, predictive and prescriptive analytics are the 4 areas of data analysis. They have different use cases. For instance, predictive analytics focuses on forecasting future outcomes using machine learning and statistical models.
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