https://store-images.s-microsoft.com/image/apps.54894.e0e55044-a41f-47bf-a401-2d5215529c66.1d5ebb7e-6108-4a74-b81c-4f6dc139dfbc.5f87a087-664a-4e32-91e6-64cf4813ec3c

Power BI Retail Dashboard Accelerator: 6 Wk Assessment & Implementation

Prelude Systems Inc

Empowering Retail Success with Actionable Insights and Rapid Analytics

The Power BI Retail Accelerator is a package of several pre-built data models, data sets, and visualizations that streamline the sales, shipment, returns, inventory, product forecast, and customer profiling processes. Our accelerator package is built with a simple user experience and rapid adoption capability.

Key Dashboards and Visualizations:

  • Sales summary dashboard with insightful KPIs (gross margin, conversion rate, average transaction value, etc.).
  • Sales performance dashboard comparing actual vs. targeted sales by month.
  • Interactive filtering options for sales performance based on regions, categories, and customer types.
  • Line chart for actual vs. forecast sales by year.
  • Bubble chart showing total sales, profit, and orders by product category.
  • Detailed product information table.

Insights and Analytics:

  • Captures insights on reordered and returned products.
  • Antecedents and consequents chart for products purchased together.
  • Basket analysis using the Apriori algorithm for customer buying patterns.
  • Shipping, inventory, and returns dashboards with actionable insights.

Retail business face the following challenges:

  • Lack of standardized reports and KPIs complicates performance tracking and progress.
  • Legacy reporting infrastructure such as Excel, SSRS, and disparate data sources affect data quality.
  • Time-consuming data analysis and predictive model building delays time-to-market.
  • Reports sharing and collaboration within teams are daunting.
  • Manual report execution causes data errors and inaccuracies.

Business benefits

  1. Extensible, pre-built, and plug-and-play data models easily map with customer data models and speed up the process.
  2. Built-in predictive analytics with proven ARIMA, SARIMA, Linear regression and data science algorithms.
  3. Easily customizable reports and dashboards with various chart types and filter selections to improve data visualization.
  4. Centralized and standard reporting structure with 45-60% functional coverage for the retail domain.
  5. Simple Excel to Power BI migration allows users to access extensive collaboration and sharing features quickly.
  6. Highly improved performance compared to Excel, SSRS, and other legacy reporting tools resulting in better, faster, and more accurate analysis.
  7. Predictive visualizations with Python-based analytical data models allow users to create custom predictive models.
  8. Near real-time data synchronization ensures that reports are always up-to-date and accurate.
  9. Retail sub-functions dashboards and reports are built based on insights from industry experts and extensive research.

Note: The cost provided is based on our experience with similar programs. We will provide you with a detailed estimate and timeline once we have evaluated your specific needs and requirements.

The cost includes one week of assessment and five weeks of delivery for four dashboards, including two highly complex and two medium complexity dashboards.

概览

https://store-images.s-microsoft.com/image/apps.50461.e0e55044-a41f-47bf-a401-2d5215529c66.1d5ebb7e-6108-4a74-b81c-4f6dc139dfbc.a1a0f22e-10b1-4481-821f-7e3ab907960f
https://store-images.s-microsoft.com/image/apps.17.e0e55044-a41f-47bf-a401-2d5215529c66.4543f3b8-de1f-4527-a181-bb205c7d8cfe.11c38e97-95e8-4d54-931e-6bab698c5a8f
https://store-images.s-microsoft.com/image/apps.49858.e0e55044-a41f-47bf-a401-2d5215529c66.4543f3b8-de1f-4527-a181-bb205c7d8cfe.458fd4f4-600f-4f94-bdbc-acf1d129d3bd
https://store-images.s-microsoft.com/image/apps.33196.e0e55044-a41f-47bf-a401-2d5215529c66.4543f3b8-de1f-4527-a181-bb205c7d8cfe.0217e30f-f9f9-4886-bed5-591c606ff80e
https://store-images.s-microsoft.com/image/apps.20759.e0e55044-a41f-47bf-a401-2d5215529c66.4543f3b8-de1f-4527-a181-bb205c7d8cfe.67530782-074c-47fa-866e-17cb21f379e3