Upon initiating my first experience with ArcMap, I was initially intimidated by the foreign program layout and the multitude of powerful features it possesses. However, those were the two things that gave me much appreciation to the program after I had completed the tutorial in its entirety. It functions not only as a database management system, but one that could store, manipulate, analyze and store data in a spatial format. The spatial distributions, connections, and associations of information presents data in a different light than what statistics could offer. The effective use of GIS formulates new questions and hypothesis, not previously seen without a spatial perspective. For example, in a hypothetical situation, say we map out the distribution of Republican/Democratic voters throughout the United States and observe that there are more Democrats in coastal regions. A conclusion of that nature would be relatively difficult to encounter without the implementation of GIS.
Another feature that had really impressed me was the plethora of features that ArcMap had to offer, enabling one to customize the output of spatial data to their liking. This enables to analyze data in a method that brains, calculators, statistics programs, and other programs can’t compete with. A sociologist, geologist, geographer, politician, scientist, engineer and/or many other professionals could find the specific answer to the specific question they are asking.
Despite its impressive potential, GIS has several pitfalls. One hindrance towards maximum efficiency and the universal implementation of ArcMap is its learning curve and its complex code translation among developers working on a big project. Finding, hiring, training, and maintaining skilled candidates who are intellectually capable of processing such tools can be costly and time consuming. In large GIS projects, developers usually work in large teams splitting up different facets of map. This could the potential for overlap, miscommunication, confusion with different developer’s intentions and coding styles. This could lead to missed deadlines, reduced efficiency and misinformation regarding the spatial analysis of data.
GIS is also costly from a hardware and software standpoint. I had wanted to install ArcMap on my own personal computer for convenience, however it was extremely expensive, and I needed a computer with a relatively fast processor to handle the bulk of the program. Making a more compact, cheaper GIS program would sacrifice its current functionality. This is similar to neogeography, where the average person could afford and understand with minimal work.
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