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This project involves data of distinct phone brands including their- transaction pattern over some given years, quarters and states using where SQL query is used for data extraction, manipulation , analyzing and Power BI for generating key insights .

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NabobiA7/State-by-State-Distinct-Brand-Interaction-Analysis-using-SQL-Power-BI

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State-by-State Distinct Brand Interaction Analysis using SQL & Power BI

Project Objective

Identify trends, growth, count, and their changes throughout some given period, within geographical boundaries, and provide actionable insights for business decision-making. ##Features -Data cleaning and preparing using SQL. -Deriving metrics to evaluate brands, transaction, and interaction records within states and years, as well as quarters for advanced analysis using MySQL workbench. -Interactive Power BI dashboard with filters for state, time, and brand with custom-made SQL query. -Data-driven insights for business strategy optimization.

Tools and Techniques

  • SQL: Data extraction, manipulation, analyzing.
  • Power BI: Data visualization and dashboard creation.

Dataset Used

The data was sourced from [Kaggle] -Dataset

Process

-Used SQL queries to clean and preprocess the raw data. -Wrote SQL queries to calculate cumulative count, percentage growth, and brand transaction tendency by state and over time. -Imported, and organized data into Power BI. -Created custom SQL queries after testing their efficiency on MySQL. -Loaded custom queries and pivoted their data labels in the format pane to create visuals. -Built an interactive dashboard for users.

SQL Query

- Query Text File

Dashboard

-Power BI Visual Screenshot

Project Insight

  • The key observations based on the insights:
  1. State Maharashtra & Uttar-Pradesh have the highest concentration of Xiaomi and Samsung and Rajasthan & Gujrat have the highest count of Vivo nationwide.
  2. “Xiaomi” is also the most dominant brand in Manipur, Jammu, and Kashmir, Mizoram, which are interestingly situated in the North & Northeastern parts of India.
  3. The sum of the cumulative count from the year 2018 to 2022 is 9.55 billion.
  4. Xiaomi, Vivo, and Samsung have the highest count in terms of max count by year-end & also by quarter.
  5. Brands with the least count in every segment are Lenovo, Gionee, Motorola, and Coolpad mostly in the states of Lakshadweep, Ladakh & Mizoram which are remote areas as each share borders with neighboring nations.

Conclusion

  • The most economically developed regions of India are situated on the West side as it includes the states of Maharashtra, Gujrat, and Rajasthan which are known as the home of stock markets, headquarters of corporate entities, tourism industry, and also mineral-based industries. Brands like Xiaomi, Samsung, and Vivo hold their dominance as these brands offer mid-range to high-end models as well.
  • Meanwhile, brands with the lowest counts are concentrated in the geographical extremes like Lakshadweep and Mizoram which have narrow populations in comparison to mainland states which calls for a demography-based survey that will allow Austo to recognize whether this event is caused by low economic activity or preference or lack of knowledge.

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This project involves data of distinct phone brands including their- transaction pattern over some given years, quarters and states using where SQL query is used for data extraction, manipulation , analyzing and Power BI for generating key insights .

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