Unlocking Customer Insights at GlobalMart with Google BigQuery

GlobalMart, a fast-growing e-commerce startup, faces challenges in efficiently accessing and analyzing data stored across different systems. With large volumes of data stored in various locations, extracting valuable insights has become a time-consuming and inefficient process. How can GlobalMart centralize its data and enable faster, more accurate analysis to drive better decision-making?

GlobalMart is revolutionizing the retail and online shopping experience for its customers, but as the company continues to expand, its reliance on data-driven decision-making has grown. However, obtaining accurate and timely data for analysis has become a bottleneck, causing delays and frustration among stakeholders who need quick insights.

Currently, GlobalMart is grappling with the following challenges:

• Scattered Data Storage: Data is stored across different systems, making it difficult to access and analyze in a unified way.
• Time-Consuming Data Access: Extracting, processing, and analyzing data from multiple sources is slow, preventing real-time decision-making.
• Limited Analysis Capabilities: Without a centralized data store, it’s difficult to perform comprehensive analyses across various datasets.

These challenges hinder GlobalMart’s ability to leverage data effectively. In this project, you will explore how to connect data stored in data lakes, perform simple analysis to extract insights, and create a foundation for more advanced data exploration and reporting in the future.