Final answer:
Data marts are faster and less costly to construct than data warehouses due to their focus on specific business functions, simplified design, and lesser storage needs.
Step-by-step explanation:
A data mart usually can be constructed more rapidly and at lower cost than a data warehouse because it focuses on specific business functions or departments. This narrower focus means that a data mart will consist of only the data necessary for its purpose, which simplifies the design, reduces the amount of data to be stored, and consequently the storage cost. Moreover, the specialized nature of a data mart allows for more rapid development compared to a broader and more complex data warehouse that would need to serve a wider range of purposes and integrate a larger variety of data sources including historical data. While data marts can leverage different data modeling approaches if needed, the key reasons they can be deployed more quickly and at a lower cost primarily relate to their targeted scope and scale. Regarding data analysis, once you have a data collection, a common step is to summarize the data to make it more understandable. Utilizing measures such as the median and variation of the dataset allows for a better understanding of the data's distribution, which is more insightful than looking at raw data directly, especially in the context of real-world scenarios such as gauging house prices in a particular area.