CapitalRise is a UK-based property investment and lending firm. It was launched in 2016 and controls a premium property portfolio worth more than £500 million. CapitalRise was set up with a clear mission: To disrupt the old way of investing in property and give investors easy and direct access to prime property-backed investments with attractive potential returns.
CapitalRise was experiencing problems creating reliable business intelligence reports.
Staff were spending hours generating relevant insights by collecting data from multiple separate sources and then manually merging them.
The company was storing its transactional, customer, and property data on Amazon Relational Database Service (Amazon RDS) - a scalable, cloud relational database - and Amazon Simple Storage Service (Amazon S3), but was experiencing problems trying to access that data in a meaningful way.
We worked with CapitalRise to build a data warehousing platform using Amazon Web Services (AWS).
Creating a single source of reliable, clear information and reducing the time taken to generate reports and discern clear insights from hours to minutes.
The project was completed in two sprints. In the first sprint, our specialists worked with CapitalRise to clarify the business objectives and data strategy, with the project then being implemented in the second sprint.
CapitalRise investigated several BI tools and visualisation options but after consulting with us, decided to build on its existing AWS infrastructure. We advised CapitalRise to maintain control of its data by building its own data asset, using tools available on AWS. That would mean CapitalRise could manipulate and transform its data into a visual format while retaining ownership and full control.
We used AWS Glue for simple, scalable, and serverless data integration and AWS QuickSight - a cloud-native, serverless BI service - to clean and prepare the data respectively. The use of QuickSight meant that CapitalRise could also create interactive and shareable visualisations.
CapitalRise was using Amazon RDS to store all of its transactional data and Amazon S3 as a simple file store. In the second sprint, we created a landing zone for the data in Amazon S3 and used AWS Glue to clean and prepare the data into a format that could be read by analysis and visualisation tools.
Once the data had been properly formatted, we used AWS QuickSight to pull it in for analysis and visualisation. This allowed us to build the required charts and dashboards, adding interactive elements so that the CapitalRise team can drill down into components on the main dashboard to see further details.
Improved decision making and data ownership
Within a limited timescale we worked closely with the team at CapitalRise to enable them to self-manage their data platform. They can now quickly and simply visualise data and derive invaluable insights.
Upon completion of the project, CapitalRise were left with the ability to self-manage the data platform. This allows them to continue on their journey to data maturity and maintain ownership of their data.
We considered different use cases before producing the initial design. We did this by working closely with the team at CapitalRise to determine what data they needed to see visualised on their dashboards and then used that to prioritise our build focus, ensuring that we could complete the implementation within the limited timescale set out by CapitalRise.
Generating business insights is no longer a slow and manual process. The CapitalRise team are now able to quickly extract valuable insights from multiple sources that help them make better decisions, faster. They can generate accurate, reliable, and attractive BI reports in a matter of minutes.
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