Video Game Sales By Name, Platform, Year, Genre, Publisher

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Video game store owner Samantha Vee requires an analysis of a video game sales dataset to understand sales patterns across various platforms and regions. The task involves creating an Excel database to organize the data, applying filters with slicers for interactive exploration, performing data extraction for specific criteria, and employing database functions to analyze sales figures. Additionally, the project includes generating PivotTables and PivotCharts to visualize regional sales data, configuring them as specified, and creating drill-down views for detailed examination of particular segments. The ultimate goal is to enable effective decision-making based on sales trends by leveraging Excel's data analysis tools.

Paper For Above instruction

Analyzing the sales performance of video games across diverse platforms and regions is essential for retail managers and industry analysts seeking to optimize inventory, marketing strategies, and sales forecasts. This paper details a comprehensive approach to data organization, filtering, analysis, and visualization using Microsoft Excel, based on the scenario provided by Samantha Vee, a local video game store owner.

Data Organization and Preparation

The initial step entails importing the provided dataset into Excel's worksheet labeled "VideoGameSales." The dataset encompasses sales figures in millions for various games, segmented by platform, release year, genre, publisher, and geographic region—North America, Europe, Japan, and other regions. To facilitate effective data analysis, the data must be converted into an Excel table—applying the "Light Blue, Table Style Medium 27." This formatting not only enhances visual clarity but also enables the creation of a structured named range, referred to as "SalesDatabase," which supports advanced database functions. Incorporating a Total Row within the table allows for the summing of sales data across specified columns, providing instantaneous totals for North America, Europe, Japan, Other, and Global Sales.

Interactive Filtering with Slicers

Slicers serve as intuitive filtering tools that improve data exploration. To analyze sales by specific criteria, three slicers—Platform, Year, and Genre—are inserted adjacent to the table. The Platform slicer is positioned near cell K1, configured into three columns for ease of selection, styled with "White, Slicer Style Other 2," and resized for clarity. Similarly, the Genre slicer is placed near cell N1 with two columns and identical styling. The Year slicer is positioned within cell K13, formatted into three columns, renamed to "Release Year," and styled accordingly. These slicers allow users to interactively filter the dataset based on platform, production year, and genre, directly influencing subsequent data analysis.

Data Extraction Based on Filtered Criteria

Utilizing the slicers, the dataset is filtered precisely to show records for PlayStation 3 (PS3) and Nintendo DS platforms, with genres restricted to Adventure or Action. The filtered data—including headers and totals—is then copied and pasted onto a new worksheet named "SelectData," starting at cell A1. The data is then prepared for further analysis by clearing filters on the original dataset and copying the headers to a worksheet called "DatabaseTotals," again starting at cell A1, establishing a clean environment for advanced calculations.

Database Functions for Sales Analysis

On the "DatabaseTotals" worksheet, Excel's database functions such as DSUM, DCOUNTA, and DAVERAGE are employed to derive meaningful insights. For instance, conditions are specified to calculate total global sales for games on the Wii platform released after 2006 (row 2) and on the DS platform within the Adventure genre (row 3). These functions utilize the "SalesDatabase" range and criteria specified in adjacent cells, enabling dynamic analysis that responds to varying parameters.

Creating PivotTables for Regional Sales Visualization

A pivotal aspect of the analysis involves constructing PivotTables, starting with a table that consolidates total global sales categorized by platform, year, and publisher. The PivotTable is arranged with filters set for publisher, row labels designated as Platform and Year, columns on Genre, and values reflecting the sum of GlobalSales, formatted as accounting with two decimal places. The PivotTable is styled with "Light Blue, Pivot Style Light 9" and renamed "PivotAnalysis" for clarity. This structured approach provides a powerful overview of sales trends across multiple dimensions.

Building PivotCharts for Visual Insights

A complementary PivotChart—specifically a clustered bar chart—is inserted to visually convey regional sales across platforms. Located on a new worksheet named "NorthAmericanSalesByPlatform," the chart's filters are set for genre, while the axis displays platforms, and values correspond to North America sales. The chart's style is set to "Style 4" with a "Quick Layout 1," and the title is explicitly renamed "North American Sales by Platform." The chart is moved to its own worksheet titled "SalesByPlatformPivotChart" to facilitate detailed examination and further modifications.

Drill-Down and Genre-Specific Analysis

To enable granular analysis, the PivotTable is drilled down into the DS sales data, and a dedicated worksheet named "NorthAmericanSalesDS" is created, providing detailed insights into sales for that specific segment. Simultaneously, the PivotChart's genre filter is adjusted to limit data to Action, Adventure, and Fighting genres, allowing a focused visual comparison among these categories. This layered analysis equips store owners and analysts with a comprehensive understanding of sales performance, fostering data-driven strategic decisions.

Conclusion

This multi-faceted analytical approach leverages Excel's robust data management, filtering, and visualization capabilities. By systematically organizing data into tables and creating interactive slicers, performing targeted extractions, employing database functions, and constructing insightful PivotTables and PivotCharts, video game retailers can gain a deeper understanding of sales trends across regions, platforms, genres, and time periods. Such insights are instrumental in optimizing stock, marketing efforts, and forecasting future sales, ultimately enhancing business performance in a competitive marketplace.

References

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