Maximizing Efficiency: Streamlined Property Management

Introduction

The client is a property management company based in Michigan, USA, and primarily generates revenue from rent collection from the properties they manage. In 2018, the company reported an annual revenue of over $2 million. The company collects several crucial real-time business data, which is then exported to an Excel spreadsheet for analysis by the managers.

However, this process was cumbersome and time-consuming. As a result, the company enlisted Assystant’s help to make reporting and analysis less complex, freeing managers from spending too much time on this tiring task.

Our Solution

Our team collaborated with the client’s managers to understand their current processes and elicit their requirements. After careful analysis, we devised a plan to work with multiple databases by integrating data from various sources into a single data warehouse.

Building the Data Warehouse

To create a successful data warehouse, we began by identifying the data sources and types of data that needed to be collected. We then designed the data architecture, which included the processes for data extraction, transformation, and loading (ETL). Our team created a robust ETL process that collected data from various sources, transformed it into a consistent format, and loaded it into the data warehouse.

Creating the Report

After building the data warehouse, we created a report using Google Data Studio for all the metrics. The report included key performance indicators (KPIs) such as revenue, occupancy rates, and rental income, which were updated automatically in real-time.

Outcome

After implementing our solution, managers can now analyze the reports directly, which get updated automatically. The new system freed them from the earlier cumbersome process of manually exporting data to Excel and creating reports. This led to a surge in productivity by the managers. They could now spend more time analyzing the data and making informed decisions, rather than spending countless hours creating reports.

Conclusion

By working with the client’s managers and understanding their requirements, we were able to create a successful data integration strategy that streamlined the reporting and analysis process. Our team’s expertise in data warehousing and Google Data Studio allowed us to build a robust system that automated the data collection and analysis process, leading to a surge in productivity. Our solution enabled the company to save time and resources while making better-informed decisions based on real-time data.