Question

Big data is becoming more and more popular with the presence of mobile technology and internet of things (IoT). It offers new tools and perspectives for market analysis.

Question:

1. provide your thoughts on how can we use big data for residential demand analysis? Provide a brief review for the general issues on residential demand analysis, or focus on one or two special issues in residential demand.

2. Provide the proof of your argument, and explain how and which kind of big data can be helpful.

Two Pages, give insightful information by following plagiarism policy.

Thats what i got, Everything is on the question. Thank you

Answer 1

Answer 1.
Big data can be used for residential demand analysis in many ways-
1. Reduce Risk- analysis has shown that big data is helpful in reducing the risk when it comes to residential demand. Real estate sellers have access to critical information about a property.
2. Fast evaluation- real estate use property evaluation to set the price of the properties and investors use them to put forward day offers for the property. Big data also helps Financial Institutions to calculate loan and minimize losses.
3. Real estate dealer identify the customer needs in a better way- predictive analysis by a big data helps the agent to understand the customer and respond them with offering based on the data.
4.Better marketing strategy- real estate agents can make marketing strategy by identifying the consumer need trend.
5. Big data and social media- many social media advertiser use the powers of social media to target the potential demand in real estate.
The general issues for residential demand analysis which are arising these days is transparent data democratization. real state Agencies have to give the customer access to real data,such as the recent survey list of the home for sale and rent. Important information ,that is important to the investor of the seller must also be given by realtors.
Answer 2.
The types of big data that can be helpful for residential demand analysis geographical data. Geographical data can be helpful for residential demand analysis. Information about the link between the place time and attributes. It has huge benefits over traditional data. This type of data is easy to transform process and analyze. This type of data is helpful for residential demand analysis and monitoring the Environmental effects.
The details of a particular Geography can be helpful to analyze what kind of demand will arise in the future. The people living in a particular place will grow over time and the demand for residential properties will also increase. An Geography data is the best suited for analyzing the demand in the residential properties.
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