Digital Marketing Data Analytics Assignment Help

Data Analytics Assignment Help

TASK OVERVIEW Context: You are a Digital Marketing Analyst. You request for marketing information, from the Enterprise IT Dept. You received seven data files (collectively a dataset), which are extracted from the company’s Customer Relationship Management System (CRM) system.

Your Tasks

This project requires you:

• To identify at least ONE (1) business issue of your choice based on the given dataset.
• To explore, extract, transform and load the data into a dimensional model using Power BI.
• To create interactive Data Visualizations using Power BI to gain insights on the business issue you have identified.
• To produce a Report using Microsoft Word to document the following:
• the business issues
• the data exploration
• the data preparation
• the data modeling done
• the data visualization works done
• the business insights found
• the business recommendations

Step by step assignment help for data analytics assignment as a Digital Marketing Analyst.

Here's a step-by-step guide on how you can approach this assignment:

1. Identifying a Business Issue:

• Start by examining the dataset you've received from the CRM system. Look for potential areas where data analytics can provide insights or address business challenges. These could include customer retention, sales trends, marketing campaign performance, or customer segmentation.
• Choose at least one specific business issue to focus on. Make sure it's something that can be addressed using data analysis and has a meaningful impact on the company's marketing efforts.

2. Data Exploration:

• Use tools like Power BI or Excel to explore the dataset. This involves understanding the data's structure, identifying missing or erroneous data, and gaining a general sense of what insights might be hidden within it.
• Create summary statistics, visualizations, and exploratory data analysis (EDA) plots to better understand the data. This will help you identify trends and patterns.

3. Data Extract, Transform, and Load (ETL) Process:

• Design and execute an ETL process to prepare the data for analysis. This may involve cleaning the data, handling missing values, and transforming it into a format suitable for building a dimensional model.
• Load the transformed data into Power BI, which will serve as your analytics platform.

4. Building a Dimensional Model:

• Define the structure of your dimensional model. This typically involves creating fact tables and dimension tables. For example, you might have a fact table for sales transactions and dimension tables for customers, products, and time.
• Establish relationships between these tables within Power BI to enable efficient data analysis.

5. Creating Interactive Data Visualizations:

• Use Power BI to create interactive dashboards and reports. Build visualizations like charts, graphs, and tables that are relevant to the business issue you identified.
• Ensure that the visualizations provide insights into the chosen business issue. You can create slicers, filters, and drill-through functionality to allow for interactive exploration.

6. Producing a Report:

• Document your findings and the entire process in a Microsoft Word report. The report should include:
• A clear description of the identified business issue.
• Details of your data exploration, including any interesting insights or anomalies you discovered.
• An explanation of the ETL process, including data cleaning and transformation steps.
• An overview of the dimensional model you created.
• Screenshots or embed Power BI visuals to showcase your data visualizations.
• A summary of the business insights you derived from the visualizations.
• Concrete business recommendations based on your findings.

7. Presentation:

• If required, prepare a presentation summarizing the key points from your report. This can be done using PowerPoint or another presentation tool.

8. Review and Finalize:

• Carefully review your report and presentation to ensure they are well-structured, concise, and effectively communicate your findings and recommendations.

9. Submission:

• Submit your report, presentation, and any other required materials according to the assignment guidelines.

Remember to maintain a logical flow in your report, and use visualizations effectively to support your analysis. Properly cite your data sources and any external references used in your report. Good luck with your data analytics assignment!