Question

Part 1 – How PowerBI can be used to provide insights into online and retail-based data 1. Provide insights into the current online sales related data using PowerBI outputs. 2. Provide insights into the retail data using PowerBI outputs. Part 2 – Combining Retail and Online Data Produce insights joining retail and online data: • identify the key KPIs in this data and; • show how the retail and online data could be analysed and visualised together in a power bi dashboard

Part 3 - Suggestions for Digital Technologies to be Used by the Company in Years to Come.

Answer 1

PowerBI is used to analyze and visualize online and retail sales data, identifying key trends and KPIs. It can combine data sources to provide a comprehensive view of business performance. Future technology considerations include AI, machine learning, and predictive analytics for enhanced decision-making.

Step-by-step explanation:

Part 1 - Online and Retail Data Insights Using PowerBI

PowerBI can be utilized to gain insights from online sales data by enabling the analysis of sales trends, customer behavior, and product performance. Visualizations such as bar charts, line graphs, and heat maps can be created to present median sales figures, the variation in sales, and other metrics such as website traffic or conversion rates. Similarly, for retail data, PowerBI can help visualize in-store sales performance, peak shopping hours, customer demographics, and inventory levels through interactive dashboards.

Part 2 - Combining Retail and Online Data

Key Performance Indicators (KPIs) for combining retail and online data include total sales, customer acquisition cost, conversion rate, and customer lifetime value. By integrating both sets of data in PowerBI, businesses can analyze and visualize overarching trends and patterns, comparing and contrasting online and in-store performance to inform strategic decision-making.

Part 3 - Digital Technology Suggestions

Looking to the future, companies should consider adopting technologies like artificial intelligence (AI), machine learning, and predictive analytics to stay competitive. These technologies can provide advanced customer insights, optimize supply chains, and improve personalization in marketing strategies.