Our client, The Australian Airports Association, appointed us for forecasting the passenger and freight traffic for the month of September 2019. Based on our forecast they intend to take the decision of whether to go ahead with investing a budgeted $1.2 Billion on building new infrastructure (including runways, facilities) and recruiting staff. As per their own business estimates, they have set a threshold of a 40% increase in their YoY traffic for both passenger and freight data to decide for a go/no go on the Investment.
Today real estate market has become very popular, but the housing recovery has pushed up home prices nearly everywhere. In Taizhong, Taiwan has not been the exception, real estate market has expanded in the past couple years to the point where it is attracting interest, not only from other parts of Taiwan but also other parts of the world. An accurate prediction on the house price is important to prospective homeowners, developers, investors, appraisers, tax assessors and other real estate market participants, such as, mortgage lenders and insurers.
The aim of this project is to forecast the monthly prices of cement in India from changes in the price of crude oil. The analysis can help construction companies and other involved players manage their inventories effectively and influence their purchasing decisions.
The goal of this project is to help banks that intend to grow through acquisition determine which banks to purchase. This is done by building a model to explore operational characteristics of different banks. Analysis is based on a dataset of over 1000 branches of the top five banks in the DC/MD/VA area
The goal of this project is to understand the perceived characteristics of apartments in Washington DC, and comparing them with apartments in DC's surrounding suburbs. This is done using data from ApartmentRatings.com
Smith Realty, LLC in Arlington, VA has experienced tight cash flows, excess inventory and a limited marketing budget. The goal of this project is to build a predictive model to help use the company's marketing dollars to go after customers whose homes would be quick sells