The challenge: timely process the data collected from different sources
Real Plaza, the main mall operator in Peru, posed a challenge framed in the need for a technological renewal. Although the company had the ability to collect information from various sources (connection by customers to the Wi-Fi networks provided in shopping centers, data on sales in stores by location, on-site surveys via tablets, etc.), said data It was not adequately exploited under an on-premise scheme and, consequently, it was not useful for the management decision-making of the company's executives.
Real Plaza had a set of information about the people who go to shopping centers and who use the public internet service inside them. The need? Do analytics on said data. Specifically, they wanted to find patterns of public attendance at malls. This with the idea of taking attraction and retention actions.
Thus, Google Cloud was found to be the most attractive option for working with data in the cloud in terms of simplicity, robustness and cost.
The solution: data analytics through GCP implementation
To satisfy the need raised by Real Plaza, Xertica proposed an architecture based on a VPN to Amazon Web Services to extract data (server used by the company that gathered the huge data generated by the company), Cloud Storage, BigQuery and Compute Engine. Finally, the new dashboards that were created were structured from Google Data Studio.
4 Dashboards were created in Data Studio:
- Surveys
- WiFi access
- Status DataSet Surveys
- Status Dataset WiFi
The benefits: timely information with fewer resources required
The expertise of the Xertica engineering team in the implementation of architectures with GCP allowed the project to become a reality in less than three months. In contrast, a previous attempt by Real Plaza's in-house team was unsuccessful for five months, without reaching the expected port. Likewise, it led to a reduction in the operating costs associated with the project: while in the past five people were required to develop the incipient dashboards prior to Data Studio, currently only one person is needed for such a task.
Finally, the main benefit consisted of having managed to adequately exploit the data generated by Real Plaza under an on-premise scheme and, consequently, obtain useful information for decision making.
