What is Data Analytics in Housing?
Data analytics in housing involves collecting, analysing, and visualising data to inform decision-making, improve operational efficiency, and enhance tenant satisfaction. By harnessing data, housing associations can uncover trends, address issues proactively, and optimise resources.
Benefits_
- Predictive analytics: Identifies future challenges, like property maintenance needs, allowing for proactive solutions.
- Operational efficiency: Streamlines processes, reduces waste, and maximises resources.
Use cases_
- Identifying dissatisfied residents: Spot patterns in complaints or feedback to address concerns and improve tenant experiences.
- Predicting property costs: Forecast ongoing maintenance or repair expenses for better budgeting and asset management.
Key components_
- Microsoft Power BI: Transforms data into actionable insights through intuitive dashboards and reports.
- Azure Data Lake: Provides a scalable platform for storing and analysing large volumes of housing data.
BRIKHousing perspective_
BRIKHousing uses advanced analytics tools like Power BI and Azure Data Lake to help housing associations unlock the power of their data. Our solutions offer real-time insights into tenant behaviour, property costs, and operational performance, enabling informed decisions that lead to better housing outcomes and improved tenant satisfaction.
