Parcel Data Aggregation Solutions for High Performing Database

The Company: Leading Real Estate Data Aggregator

Industry: Real Estate

Company Headquarters: US

Parcel Data Aggregation for Leading Data Aggregator Led to High Performing Database

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The Objective:

The client a leading real estate parcel data aggregation company empowering its global clientele with real estate data and insights.

They were looking to partner with a data management company who could capture 650,000+ records every month from disparate data sources and input it in a structured manner.

The client looked to replace manual, time consuming process with automated process leading to enhanced accuracy and speed.

The Challenges:

Processing huge volumes of unstructured data
Getting on board resources with strong analytical skills and domain knowledge
Managing 225 full time skilled resources deployed for this project
Implementing tools and technology to improve accuracy and enhance speed
Putting up real time data from multiple online sources
Capturing, verifying, validating and integrating data from disparate real estate sources

HabileData’s Solution

A seamless workflow was planned for entering data from property documents.
- The process was automated and semiautomated with custom logic and macros, saving time on predictable and repetitive tasks.
- Data was captured from images and other disparate sources both structured and unstructured.
- Data was further classified, standardized, validated, integrated and entered in structured manner.
- Resources with high level of analytical and comprehension skills and eye for detail along with pre-defined 80 logical rules and 52 micros created internally ensured following deliverables:
  - More than 650,000+ records processed monthly
  - 98% accuracy
The workflow was broken into modules and resource allocated as per the expertise of the team member.
Classification and tagging:
- Client uploaded the images on the FTP server.
- The images were classified and routed through custom macros to different folders based on their counties; macro ensures 100% accuracy in county-wise data segregation.
- Folders were auto created; custom macros ensure that only the valid images move to the assigned folder.
- Valid documents taken for data entry in the specified fields.
- Real estate data was scraped from multiple real estate sites and collected from property document images as well.
- Scheduled web crawlers paced up online data capture process.
- Parcel data was validated and mapped against GIS mapping, location tracking details, and data from other real estate multi listing sites.
- New property information was added with help of programmable bots.
The data to be entered was categorized into three sections – Yellow entry, Double D entry and Gray entry.
- Double D Entry – These are the extremely critical fields where two teams entered the same data and the files were verified and merged using macros.
- Gray Entry – The lesser critical fields such as buyer info and property data etc.
- Yellow Entry – Complex data fields requiring significant comprehension skills and hence addressed by specialized teams.
- All the three fields (Gray, Double D and Yellow) are merged using in house developed macros.
Quality check and audit
- Automated quality check through predefined rules ensured accuracy.
- Additional audits were done before submission.
Submission
- The files submitted into the client interface/application.
- Append property parcel data on client’s portal through API credentials.
- Reports/dashboards at granular level were shared with client.

Business Impact

Updated and comprehensive property data pool
Enhanced customer experience and engagement
Improved operational efficiency

Value Addition

Automated parcel data aggregation helped the leading MLS put-up real-time data from multiple online sources on their portal assisting customers with relevant information and connect with real estate professionals.

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Parcel Data Aggregation for Leading Data Aggregator Led to High Performing Database