Welcome to HPN Project
This project page aims to demonstrate the power and transformation that data analysis can bring to any company.
Read MoreWelcome to HPN Project
This interactive project is part of the xperiun bootcamp and aims to evolve the data analysis professionals involved
Read MoreWelcome to HPN Project
This is the second phase of the bootcamp in which only professionals who passed the first stage proceeded to the final phase, carried out as a team
Read More"The growing amount of data, considered the new oil"
The need for a data-driven philosophy at HPN to transform data into management information. Power BI was chosen for its regular updates, cost, connections, sharing, interactivity, and support for AI and ML, to assist in strategic planning and improve report visualization and analysis.
A BI solution with appropriate architecture, well-defined processes, and robust data modeling was developed to ensure standardized and consolidated data.
Denis Murphy and Steve Jackson are the key individuals for implementation, and the project team must identify the users of the solution, including general users, producers and analysts, and managers. Training plans for IT and Marketing and Sales teams will be necessary.
Our Mission
Our main objective is to develop a BI solution focused on presenting HPN’s revenue data. This solution will unify the company's global information and provide managers with insights into the brand's sales performance, best-selling products, revenue projections for 2014, and other data to enhance decision-making and information concentration.
- A revenue projection for 2014 to help HPN outline their 2014 budget. Their Goal is a 10% increase throughout the year compared to 2013, with the exception of May 2014, when they expect to double the revenue compared to May 2013, as they will participate in a major fitness event that month.
- Revenue declines over time
- Margin variations
- Products with no sales
- Customers with no purchases for a long time
- New customer acquisition rates
- Identification of outliers (customers, regions, and/or products that are out of the norm)
- Increase in sales returns
- Products and customers performing below average
- Correlations between variables
Advanced Data Visualization and Storytelling for Heavy Power Nutrition
This comprehensive report provides a deep dive into financial and sales metrics, offering a nuanced view of performance across different dimensions such as customer segments, product categories, and regional markets. By leveraging both historical data and future forecasts, this report aims to empower users to make well-informed strategic decisions that drive business growth and operational efficiency.
The dark-themed dashboard is designed to enhance visual clarity and focus, providing a clear and engaging way to interact with the data. Through a series of interactive visualizations and detailed charts, users can explore trends, identify key performance drivers, and gain insights that are crucial for formulating effective strategies.
- Gross Revenue ($): Track the total income generated from sales before any deductions. This metric helps in assessing overall financial health and revenue trends.
- Gross Profit ($): Calculate the profit earned after subtracting the cost of goods sold from gross revenue. This measure is essential for understanding profitability and cost management.
- Marketing Investments: Evaluate the amount spent on marketing campaigns and their effectiveness. This analysis helps in determining the return on marketing efforts and optimizing budget allocation.
- Sales Return Rate (%): Analyze the percentage of revenue that translates into profit, reflecting the efficiency of sales operations and pricing strategies.
- Units Sold (#): Monitor the total number of products sold over time. This metric is vital for understanding sales volume and market demand.
- Customer Segmentation Insights: Delve into the performance of different customer segments to identify high-value customers and tailor marketing strategies accordingly.
- Regional Performance Analysis: Examine sales and profitability across various regions to pinpoint areas of strength and opportunities for expansion.
- Product Performance Metrics: Assess the success of different product lines to guide inventory management and promotional strategies.
Tailored for Sales and Financial Managers, this dashboard not only provides detailed trend analysis and evaluation of marketing impacts but also facilitates the identification of top-performing products and regions. By utilizing these insights, managers can make data-driven decisions that enhance overall business performance and strategic planning.
The interactive nature of the dashboard allows for dynamic exploration of data, enabling users to drill down into specific metrics, compare performance over time, and visualize projections. This comprehensive approach ensures that users have a complete understanding of their business landscape, driving more effective and informed decision-making processes.
Description
This report provides a comprehensive analysis of financial and sales metrics, allowing users to visualize performance across different dimensions such as customers, products, and regions. The aim is to facilitate strategic decision-making based on historical data and projections.
Key KPIs and Metrics
- Gross Sales ($)
- Gross Margin ($)
- Marketing Expenses
- Return on Sales (%)
- Quantity Sold (#)
Target Audience:
Sales and Finance Managers
Use Cases
- Analyzing sales trends over time
- Assessing the impact of marketing expenses on sales
- Identifying products with the highest return on sales
Data Tables
| Name | Description |
|---|---|
| Date | Table containing a list of dates for time-based analyses. |
| Calculations | Table containing auxiliary calculations and derived metrics for use in analyses. |
| [COM]SalesHeader | Table storing sales headers, including general information about each sales transaction. |
| [COM]dimRegion | Table containing information about regions, allowing detailed geographic analysis. |
| Months Comparison | Table generating a series of months for comparing data over time. |
| [COM]dimProductAux | Auxiliary table containing additional product information for specific analyses. |
| AccountSelector | Table allowing the selection of accounts for custom analyses. |
| Regression Test | Table storing data for regression testing in financial analyses. |
| Parâmetro | Table containing parameters used in calculations and analyses. |
| Months After | Table generating a series of months after a specific date for temporal analyses. |
| Seleção Cohort | Table allowing the selection of cohorts for customer retention analysis. |
| Regression Marketing - Test | Table storing data for regression testing related to marketing. |
| Parameter Marketing Expenses | Table containing parameters related to marketing expenses. |
| _dCustomerOutros | Table grouping customers into an 'Others' category for analysis. |
| _TopGroups | Table categorizing data groups for comparative analyses. |
| _TopNState | Table generating a list of top states based on specific criteria. |
| _TopNRegion | Table generating a list of top regions based on specific criteria. |
| _TopNDepartment | Table generating a list of top departments based on specific criteria. |
| _TopNSalesPerson | Table generating a list of top salespersons based on specific criteria. |
| _dCustomerGroup | Table grouping customers for segmented analyses. |
| _dProductGroup | Table grouping products for segmented analyses. |
| _dRegionGroup | Table grouping regions for segmented analyses. |
| _dDepartmentGroup | Table grouping departments for segmented analyses. |
| _dSalesPersonGroup | Table grouping salespersons for segmented analyses. |
| _dProductType | Table categorizing products by type for analysis. |
| _dMarketingExpense | Table tracking marketing expenses across different categories. |
| _dSalesChannel | Table categorizing sales channels for analysis. |
| _dSalesMethod | Table categorizing sales methods for analysis. |
| _dDiscountType | Table categorizing types of discounts applied to sales. |
| _dSeasonality | Table analyzing sales seasonality patterns. |
| _dSalesTrend | Table analyzing sales trends over time. |
Tables
| Table | Description |
|---|---|
| [FIN]dimAccount | Table containing detailed information about financial accounts, including identifiers and related attributes. |
| [FIN]dimAccountHeader | Table storing financial account headers, allowing categorization and grouping of accounts. |
| [COM]dimCustomer | Table containing customer data, including identifiers, names, and contact information. |
| [FIN]dimDepartmentGroup | Table grouping financial departments, facilitating analysis by specific groups. |
| [FIN]FactFinance | Fact table storing financial transactions, including amounts and transaction dates. |
| [COM]dimGeography | Table containing geographical information, such as countries, states, and cities, for regional analysis. |
| [FIN]dimOrganization | Table storing data about organizations, including hierarchies and relationships. |
| [COM]dimProduct | Table containing information about products, including categories, prices, and descriptions. |
| [COM]ProductCostHistory | Table tracking the historical cost of products over time. |
| [COM]FactSalesDetails | Fact table containing details of sales, including quantities, prices, and applied discounts. |
| [COM]FactSalesReturns | Table storing information about sales returns, including quantities and reasons. |
| [COM]dimDate | Date table providing a time dimension for analyzing data over time. |
| Calculations | Table containing auxiliary calculations and derived metrics for use in analyses. |
| [COM]SalesHeader | Table storing sales headers, including general information about each sales transaction. |
| [COM]dimRegion | Table containing information about regions, allowing detailed geographic analysis. |
| Months Comparison | Table generating a series of months for comparing data over time. |
| [COM]dimProductAux | Auxiliary table containing additional product information for specific analyses. |
| AccountSelector | Table allowing the selection of accounts for custom analyses. |
| Regression Test | Table storing data for regression testing in financial analyses. |
| Parâmetro | Table containing parameters used in calculations and analyses. |
| Months After | Table generating a series of months after a specific date for temporal analyses. |
| Seleção Cohort | Table allowing the selection of cohorts for customer retention analysis. |
| Regression Marketing - Test | Table storing data for regression testing related to marketing. |
| Parameter Marketing Expenses | Table containing parameters related to marketing expenses. |
| _dCustomerOutros | Table grouping customers into an 'Others' category for analysis. |
| _TopGroups | Table categorizing data groups for comparative analyses. |
| _TopNCustomer | Table generating a list of top customers based on specific criteria. |
| _TopNProduct | Table generating a list of top products based on specific criteria. |
| _dProductOutros | Table grouping products into an 'Others' category for analysis. |
| _TopNState | Table generating a list of top states based on specific criteria. |
| _dStateOutros | Table grouping states into an 'Others' category for analysis. |
| Projection Month | Table generating monthly projections for future analyses. |
| MonthAux | Auxiliary table containing information about months for temporal analyses. |
| Projectio May | Table generating specific projections for the month of May. |
| Boxplot X Axis | Table defining the X axes for boxplot analyses. |
| Seleção Pareto | Table allowing data selection for Pareto analysis. |
| Aux Axis Disp X | Table defining auxiliary X axes for visualizations. |
| Aux Axis Disp Y | Table defining auxiliary Y axes for visualizations. |
| Aux Legend Disp | Table defining the auxiliary legend for visualizations. |
RESULTS
The Project
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Services
What we do offer
Data Visualization
Create intuitive and interactive dashboards to visualize complex data and drive insights.
Predictive Analytics
Use statistical models and machine learning to forecast future trends and outcomes.
Data Integration
Combine data from multiple sources to provide a unified view for comprehensive analysis.
Business Intelligence Reporting
Develop detailed reports and performance metrics to support strategic decision-making.
Data Cleaning and Preparation
Cleanse and organize raw data to ensure accuracy and usability for analysis.
Custom Analytics Solutions
Design tailored analytics tools and solutions to meet specific business needs and objectives.
Team
Our Hardworking Team
Contact
Contact Us
Address
Road to Nowhere, City of Nowhere, Brazil
Call Us
+55 5589 55488 55
Email Us
email@email.com.br