Bike Stores Are A Small Business Chain That Sells ✓ Solved

Bike Stores is A Small Business Chain That Sell

Bike Stores is a small business chain that sells bicycles at stores in California, Texas, and New York. The business owners would like several reports to be generated that provide information on company sales. These reports will leverage data currently stored in the BikeStores database. You will install Microsoft Report Builder on the same system you have Microsoft SQL Server and SQL Server Management Studio (SSMS) installed. You will then generate column chart, bar chart, line chart, pie chart, and tabular reports presenting various views of BikeStores sales.

It is very important that you watch the Module 5 videos associated with SQL prior to completing the assessment. You will need to install and use Microsoft SQL Server Express and Microsoft SQL Server Management Studio (SSMS) for this course. You can download the latest versions of these free software products here: Microsoft SQL Server Express Microsoft SSMS. Navigate to the Academic Tools area of this Module and select Library then Required Readings to access your texts and videos. You will need to install and use Microsoft SQL Server Express and SQL Server Management Studio (SSMS) for this course. You must have SQL Server Express and SQL Server Management Studio (SSMS) installed to complete this assessment.

The sample database for this module is called BikeStores. The database creation script, installation instructions, and database diagram can be downloaded below: Create BikeStores Database Script Instructions for Establishing the BikeStores Database Bikestores Database Design Diagram. Use the BikeStores database design diagram to help address applicable assessment tasks. You will need to fully understand the BikeStores database design for this assessment. You must also install the Microsoft Report Builder application. The following document provides instructions on how to install Microsoft Report Builder: Microsoft Report Builder Installation Instructions. Provide your assessment task responses in a Microsoft® Word® report document. Also, incorporate a screenshot of each completed Microsoft Report Builder report into the assessment document as proof of completed work.

Sample Paper For Above instruction

Task 1 - Generate a Column Chart Report

The first task involves creating a column chart report that displays the top five bike sales. The query in the common table expression (CTE) is designed to retrieve sales data, rank it, and filter the top results. Typically, this query employs aggregate functions like SUM or COUNT to accumulate total sales, and table joins link tables such as sales, products, and categories. The query may leverage either correlated or uncorrelated subqueries, often depending on whether it references outer queries within subqueries.

Filtering results usually involves a WHERE clause to restrict data to relevant dates or locations. For instance, the query might filter sales within a specific date range or geographic region. The CTE often simplifies readability and reusability for subsequent main queries, which sort the data based on total sales in descending order, selecting only the top five entries.

Examining the generated column chart reveals the products or categories with the highest sales volume or revenue. Such insights enable assertions like identifying best-selling bicycles, key sales regions, or seasonal trends. The visual representation helps stakeholders understand which products appeal most to customers, facilitating inventory or marketing decisions.

Task 2 - Generate a Pie Chart Report

The second task requires generating a pie chart illustrating the sales percentage for each bike category. The associated query in the CTE aggregates total sales per category, utilizing aggregate functions like SUM to compute revenue or quantity sold. Table joins connect the sales, products, and categories tables to associate each sale with its category.

Filtering may be applied to focus on a specific timeframe, such as a fiscal year or quarter. The results are grouped by category, and each segment of the pie indicates the proportion of total sales attributable to that category. The query may leverage subqueries or window functions, but typically uses straightforward joins and GROUP BY clauses to aggregate data.

From the resulting pie chart, stakeholders can interpret the market share of each category, determining which bike types dominate sales. Assertions include identifying high-performing categories or evaluating the effectiveness of marketing efforts targeted at specific segments.

Task 3 - Generate a Bar Chart Report

The third task involves crafting a bar chart that depicts monthly sales across all BikeStores locations during 2017. The query in the CTE should extract sales data filtered to the year 2017, using date functions to correctly segment months. Joins will link sales with store locations and possibly product categories.

Aggregate functions such as SUM or COUNT will calculate total sales per month per location. The grouping parameters include year, month, and store location, enabling the visualization of seasonal and regional sales trends. Filtering involves a WHERE clause stipulating the year 2017, ensuring only relevant data appears.

The bar chart will display distinct bars for each location's monthly sales, revealing patterns like peak sales months or regional differences. This facilitates assertions about product performance in different markets and seasonal influences.

Task 4 - Generate a Line Chart Report

The fourth task involves creating a line chart that shows monthly sales by bike category during 2016. The query in the CTE summarizes total sales per category on a monthly basis, again employing date functions to extract month-year components.

Existing table joins link sales, categories, and date/time dimensions. Aggregate functions like SUM sum the sales, and the results are grouped by category, month, and year. Filtering limits data to the year 2016. The visualization indicates how sales evolve throughout the year for each category, highlighting seasonal fluctuations or emerging trends.

From this Excel or Power BI style line chart, business analysts can make assertions such as seasonality effects, category growth trajectories, or the impact of marketing campaigns during specific months.

Task 5 - Generate a Tabular Report

The final task involves creating a tabular report displaying bike category sales by year. The CTE employs aggregate functions on sales data, grouped by category and year. Joins connect sales to categories, and filtering may be applied if analyzing specific date ranges or regions.

The report will present total sales figures per category for each year, facilitating straightforward comparison across periods. Key insights include identifying annual growth, sales declines, or stable categories. These results underpin strategic planning related to inventory, marketing, or product development.

Conclusion

In constructing each report, understanding SQL operations like table joins, subqueries, aggregate functions, and filtering is essential. Microsoft Report Builder enables the visualization of complex data, turning raw numbers into actionable insights, crucial for informed decision-making in retail operations.

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