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Big Data Processing in a D2C environment
Clients: Big data processing in a D2C environment
Category: IT

Summary of the project – Big Data Processing in a D2C environment

The project involves a full lifecycle product development journey from a D2C perspective for the real estate market in the middle east. Our clients being leaders in the real estate market had the vision of using the latest technology and brining the digital age into the real estate sector which has been mostly human intensive.

Challenges of the client

More than a challenge it was the vision on the client which drives this project. They feel the need to provide services to their customers in a very professional and sophisticated manner. The question was about how you cater to the needs of a larger audience and yet ensure that quality standards and customer satisfaction level are at the highest level. This was not possible without proper technology integration into the processes and to automate mundane things but at the same time have a human approach where it was required. This involves handling massive amounts of data and automatically analyzing it with the help of a proper data analysis and science team. The ongoing project is directed with a aim to leveraging the data for the benefit of their end clients to ensure they get the best deals at the right time. Ensuring the business is next to their customers when they need them.

How we are added value

With a long term road map towards data and the value it can add to the business and their end clients, we have been involved in all the phases of implementation to help the client to have the best strategy in place for the their product as well as data journey. It involved building a solid back-end foundation for the data repository from both structured as well as unstructured data sources and internal as well as external data sources to give a 360 degree view to both their end client about their property. The project involves multiple phases and involves machine learning based recommendations and regression model based value estimations for the benefit of the users.

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