| Data - Frequently Asked Questions |
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| Questions and Answers | ||
| What is GIS data? |
Data is the foundation of all GIS analysis. There are two classes of data:
spatial and attribute. In the simplest terms, spatial data is the pictures that define the shape and location of places, and therefore allows you to draw a map. This data is based on numeric information, but it's presented in geographic pictures. For example, a dot on a map is a piece of data. It has a unique geospatial location in the world: in other words, no other data shares that same latitude and longitude. The point represents some factual data, for example, a store's address, its sales, or its phone number. Attribute data (also know as alphanumeric data) is usually what most people think of when they think of data. This data describes the geographic places, the people who live there, and what happens there. It could be your sales figures, your market's population counts, or your market's demographics. Essentially, attributes are what make the spatial objects of a map meaningful. Either type of data, spatial or attribute, by itself is interesting, but where businesses reap the most rewards is when they merge the two through the science of desktop mapping to produce a map of useful information. 
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| What kinds of GIS data do I need? |
There are essentially two levels of GIS data: infrastructure data and
decision-making data. Infrastructure data is the foundation of your GIS
system. Just as an architect starts a building with the foundation, you need
to start building your GIS system by establishing your data infrastructure.
Nearly every GIS database begins with a street file of a trade area. From
there you can add an assortment of data as helpful orientations, such as
geographic boundaries, waterways, and transportation lines. You decide the
level of detail you need in your foundation, based on the types kinds of
analysis you want to do. While establishing your infrastructure data, it makes sense to be forward-thinking and plan for your analysis needs both today and in the future. You will invest more up-front, but you will save money in the long run because you will not have to rebuild your entire infrastructure later when your needs expand. Once your foundation is established, you can begin adding your GIS decision-making data based on what business decisions you anticipate you'll have to make. Examples of decision-making data are the sales figures associated with your stores, lifestyle segmentation data, and regulatory facts that impact your business.
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| How often do I update my GIS data? |
This varies according to the nature of your particular business and your use
of desktop mapping. The reality is that data changes, for example, new streets
are added to cities, competition comes and goes, and population demographics
shift. You have to decide how relevant the most recent data is to your business
decisions.
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| What is meant by 'manufactured' data? |
Through your GIS research, you may have uncovered a vast amount of data
formats, but usually in their raw form. To take this raw data and convert it
into useful business tools requires a significant manufacturing process. For
example, the raw data frequently has errors and omissions. It may take a staff
of two to four people several months to fix the problems and covert the data
into usable formats. Also, just like any product, the manufacture of data
requires common business overhead expenses such as labor, marketing, and
warehousing. In the long run, the price you pay for error-free, high-quality,
highly-useful data from a reputable company is a bargain.
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| How do I determine what data I need? |
Selecting the data you need to accomplish your goals begins by determining
what it is you need to know about your business. Then you must identify your
company's success factors, for example, your ideal customer demographics,
competing store locations, and complimentary stores locations.
Determining your business's success factors usually requires company-wide input from various departments including operations, marketing, and real estate. You'll set yourself up for failure if you base your data needs on one person or one department's perception of your success factors. Once your success factors are identified, it becomes pretty clear what your data needs are going to be. For example, if your best-performing stores are located near certain mass merchandisers, then you need a database that locates those merchandisers in your target markets. Today there is a wide range of data products available. Each business should search the possibilities to ensure it's not leaving a stone unturned in its quest for the maximum understanding of its marketing and the sales potential available there.
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