Designing an interactive Geographical GUI for a Real Estate Private Equity Sponsor
Industry Challenge/ Challenges
Private equity firms have been glitchy in the digitalization process, and a lack of uniform data at scale is the most commonly cited barrier to broader AI adoption in the industry. AI has nothing to work with when there is no underlying data in digital format. Although good data accumulation (like bad debt, concessions, revenue, and expenses, among other things) sets the foundations for using AI and ML in private equity, an abundance of useless non-unified data from multiple sources is nothing more than a roadblock to the effective performance of AI and ML technologies.
- Unification
There was unavailability of unified data with the client.
- Sources
There were a variety of data sources available along with different data schema and structures.
- Blocks
The data sources want to own the data, and put in blocks/ blockers to prevent open access to this data [this is not private data].
Problem Statement
The client was looking to build a data warehouse system for an end client that would store all data provided by numerous sources and allow them to visualize data using the database in a geographical format. To move data into the database from single or several sources, ETL pipelines were required to be developed.
Our Solution
- Algoscale began with scraping the data from multiple sources and creating a consolidated database with the required data.
- We consolidated all the data in a custom format which made reading/ understanding the data easier for the client.
- Our experts created a custom GUI using Mapbox with filters for custom analytics.
- To circumvent the blocks put in by source websites and prevent the remote desktop IP from being blocked, we created custom scraping code.
Technology
Tech Stack
Business Impact
- Our experts are building data pipelines for AI to be used for cost calculations, resulting in informed purchase decisions and increased client conversions.
- Algoscale is assisting the client in conducting an in-depth analysis of the market to forecast trends and future property buying/ renting costs by collating data from various sources such as census and demographic data, as well as profiles of people residing in these areas to get a complete overview of a specific location.
- The custom data warehouses created by us allow the user to dive deep into the data and perform NLP or other data science operations with high accuracy.
Also Read: AI Transforming The Construction Industry with a SaaS-based platform
Designing an Interactive Geographical GUI for a Real Estate Private Equity Sponsor
