Client wanted large volume of data relevant to the real estate projects for cities such as (Ramsey, Carver, Hennepin, Dakota and Anoka). All the data from PDF files has to be entered in excel sheets without missing a single record. Within the settled time frame, the data has to be entered into online database based on client’s requirements.

Large volume of real estate data has to be collected for different cities like Hennepin, Anoka, Carver, Ramsey, Dakota etc.
Collection of such a large volume of data, processing it and entering it into relevant field out of 23 fields was a challenging task.
All this has to be delivered within the tight time frames while maintaining enhanced quality and efficiency.
From such a large database, repeated or duplicate records have to be removed and this was another big challenge.
Highly enhanced and efficient quality of data has to be maintained without incurring additional cost.
In the restricted time frame, we have to enter the data with zero errors.

Highly skilled work force worked 24/7 for entering accurate data as per the specifications.
Even the minutest detail was included in the data as extensive research was conducted for the same.
The client gets access to systematic and detailed database of real estate that was easy to access.
Extremely cost effective results were obtained by the clients and that too within the estimated time frame.
Clients got streamlined data as a result of accurate handling of real estate statistics combined with online entry of data.
Desired work of highest quality within short timeline helped the clients with the processes.

For such a huge amount of work, dedicated team of around 50 experts of data entry was employed to generate high quality results.
The username and password provided by the client was used for the collection of data from specific websites.
The PDF files were used for getting some of the basic information such as:
Mortgage name
Date of Publish
Address
First Name
Last Name
Phone number
City
State
Zip Code
Disposal Date
Payable Amt
Original date
Original Amount
We got the sold amount, PID and phone number on the basis of above information. For this purpose, we took help from just the website of government and reliable online resources for the collection of all the information.
If any information is not found or is missing then same is marked via comments.
In the Postponed column, any deferred records were entered.
Duplicate records were to be removed. For this purpose, we used the file of “master list.xls” in which the day to day collection was kept. When the fresh data collection is done, all the records are copied in the master file. After this, duplicate records were removed by using the vlookup formula with the column of PID.
After the complete data collection, phone search is done.
The files were mailed to 30 email ID’s without any fail.