Exercises

Created course website with honor pledge to publish work

Obtained Raspberry Pi 3+ to use for course

Installed NOOBS and other software to get the Pi running

Objective: Create a program to provide more insight and statistics on the residential real estate market in Norway

Background: Does not currently exist. Uses data from existing sources

Methodology: Create the program using several different programs. Back end would be python for web scraping, Excel or MySQL for data and R for statistical analysis. Front end would likely be in js.

Expected Results: A program that is interactive, providing insight into different areas of Norwegian markets.

Cost: Development costs, server costs, API fees, promotional costs, publishing costs and likely legal fees if put into production.

Problem Statement: People should have more information about the real estate markets

Present/Desired State: There are many applications such as Zillow and Redfin that do a great job at providing insight into the real estate market within the US markets. Outside of the US, there are not as many technologies available. The main technology that is used for browsing real estate listings is a classifieds service.

Source/Cause: I traveled to Oslo, Norway at the end of 2019, and I was very surprised at how expensive everything was. Eventually I became more interested in the cost of living and the cost of homes. After discovering how homes the process involved with buying or renting a place in Norway, I decided to try to improve upon this.

Kepner Tregoe Analysis:

• Timing: The timing of this product would not be extremely lucrative. It would be important to continually create new and updated features to ensure that your clients are receiving the most up to date information. With that being said, I do not think that there is an urgent timing push for development.

• Impact: The impact of this product is one that would be very positively received in certain areas. Obviously it doesn't really affect many people outside of a certain market, but it could have an enormous impact on real estate investors in the country of Norway. Even though the rest of the world may not be able to benefit from this product as much as Norwegians, it would also give foreigners a better insight into the economy and housing markets.

Primary Goal:

• Create a program that is able to compute several metrics involving the Norwegian housing market such as average price per square meter and median home value.

• Use external API services to create a heat map that demonstrates which locations are the most expensive depending on average price per square meter.

• Use the service to find the most expensive and least properties for sale within given locations

Secondary Goal:

• Create a database using something such as MySQL or other type of query language to provide historical industry standards for housing market trends

• Have a clean graphical user interface throughout HTML, CSS, JS and other front end design elements.

Intellectual properties for this project are very unique because the data that was gathered comes directly from another existing service that may have rights to that data. Given that there are other ways to obtain this data such as through the individual realtors, this data could be collected from a variety of sources. It is essential to ensure that the data can be owned by one party.

Would be worthwhile to patent the pricing algorithms that determine which houses are the most overvalued or undervalued. Other than algorithms and sorting methodologies used to value houses, not much else should be patented, as it is readily available to the general public.

Need to confirm ownership of the following data:

• Address

• Price (NOK)

• Square Meters

The rest can be calculated through additional computations

Back End:

• Most of the work will be done on the back end of the program, as that is where all of the data is being gathered, processed and compiled into useful information

• The back end will not interact that much with the front end, as once the data has been collected, processed and compiled, it will not be altered until it more information is added

• The back end program will use Python to pull the data, Excel to process and organize the data and R to analyze and visualize the data

Front End:

• The front end will utilize the finalized data set and key elements from the R computation to clearly publish online

• Using HTML, CSS and JavaScript

• The front end will have a clean UI that focuses on simplicity and ease of use

• The main thing that it will highlight is the key metrics of Norway such as median price per square foot and median home value. Additionally it will also provide navigation for other cities, so that the data can be analyzed in a smaller context rather than every property.

Created a morphological chart to analyze how I could achieve some of my main goals

See chart here

There are not a ton of concerns on ethics or liability for this particular service

Given the online and data driven nature, there are little to no concerns for this section

This is a critical element to address throughout the software design process of this potential product

Because of the value of certain data sets, it is essential to prioritize cyber-security and ensure that no one is able to hack into the servers where this data is stored

Unlike other sensitive data types such as medical or financial data, the data for this project would be from sources available to the general public

• This ensures that even if someone were able to breach the system and gain access to sensitive information, the only people who would be affected would be the people involved in the program rather than the customers. This would ensure that the magnitude of a breach would not be terribly hazardous (such as the Equifax data breach for example)

Since it is a SAAS product, there is no issues regarding an actual electrical failure or hazard to users

Utilized a KT Matrix to illustrate design goals and overall intentions of product performance - View matrices here

Used the Decision factor formula to gain more insight on the product goals

• Decision factor (D) = Weight Factor (W) * Rating Factor (R)

• D = W*R

• Found the three biggest decisions were profitability, ease of use and frightfulness

Used threat factor analysis to determine some of the biggest concerns involved upon the creation of this service

• Threat Level (T) = Probability of occurrence (P) * Severity of Threat (S)

• T = P*S

• Found the three biggest threats to be server hacks, data errors and internal programming errors