Good question. The short answer to this question…you need to use AWhere’s ‘Connect to My Data’ tool (a.k.a. Data Connection). In addition to this post, you might want to look up other references to ‘Data Connection’ here in the Forums, in the AWhere Blog, and in the AWhere help documentation (available from AWhere’s ‘Help’ menu). Also, you can click here for a printable, one-page cheat sheet with step-by-step instructions for how to establish a data connection in AWhere. Though, if you are unfamiliar with data connections, I would suggest you read completely through this forum post for a good overview of Data Connecting.
The data connection capability of AWhere is one of the primary reasons for which many people use AWhere, and one for which we have specifically designed AWhere. Since this is probably something many people will have a question about, I’ve put together an explanation that I hope will answer lots of questions regarding this capability of AWhere...why/when you would use a data connection, what needs to be in place for it to work, etc. The process of establishing a Data Connection is really very simple, so don't let the length of this post fool you. This forum post is detailed in explaining what is needed to set up a data connection, and then what you can do after a data connection is established (with some screen shots included).
Data Connection Overview - Simply put, a Data Connection creates a dynamic (live) linkage between a map layer in AWhere and some external data source, be it a 'flat-file' such as an MS Excel spreadsheet or .csv file, or a table or query in a relational database such as MS Access Database, SQL Server, Oracle, etc. (Note that with AWhere Express, you can connect only to ‘flat files’…but with AWhere Professional, you can connect to relational databases, in addition to the flat-file types as well.) After that live linkage (connection) has been established between the map and the external data source, you can then visualize the data on the map by: Coloring the map features according to the data values in the table, Labeling the map features using the data values from the table, Putting charts on the map features using the data values from the table, Graphing the data, etc (examples of these display methods are shown at the bottom of this post). Additionally, with your data linked to a map layer in AWhere, you are able to use tools within AWhere to perform analyses of your data from a spatial perspective, that is Geo-analytics. You can calculate regional statistics, aggregate features, look for spatial patterns/clusters, filter and query the map, overlay and combine your data with data from spatially coincident features of other map layers, etc. Looking at your data through the lens of a map, you are able to discern and discover aspects of your data that you would never have otherwise seen just looking at it in spreadsheet form.
In addition to establishing the data connection initially, after that data connection is established you also have the ability to make subsequent edits and updates to the contents of the external data source, and then simply ‘Refresh’ the data connection…that will immediately update the map-view to reflect the newly edited/updated data (see the post immediately below this one for more on 'Refreshing' a data connection).
What kind of map layer can you connect to? – Any map layer! It could be a:
· ‘Point’ map layer - the mapped items in point map layers represent features that are 'non-dimensional', for example cities (on large-scale maps), airports, buildings, addresses you’ve geo-coded and brought into AWhere, input from a GPS unit, etc.
· ‘Line’ map layer - the mapped items in line map layers represent features that are 'one-dimensional', for example roads, rivers, trails, etc.
· ‘Polygon’ map layer – the mapped items in polygon map layers represent features that are 'two-dimensional', for example political boundaries, territories or regions that you create, census tracts, even the foot-print of buildings in very small-scale maps, etc
Well, where do you get the map layer to begin with? - Click on any one of the several links in the above section ('What kind of map layer an you connect to?') for more about how to obtain/create any of those types of map layers mentioned. If you need political boundary map layers to which you want to connect data, know that AWhere Inc. has many, free datasets available to our licensed users, data sets that contain political boundary layers for practically every country in the world, as well as for the U.S. (state, county, census boundaries, etc)…so, you would most likely not need to hunt the internet for a basic boundary map layer to which you can connect your data…AWhere Inc should have it available unless it is something out-of-the-ordinary. Click here for more on what we have and how to obtain those.
What kind of data can your data table contain? – Any data, of any theme…doesn’t matter. You simply need to format your table so that you have only one record (row) of data per map feature in the map layer to which you are connecting the table. That is, there must be a one-to-one relationship between the features in the map layer, and the records in data table. So, for example if you want to connect a table of data to a map layer of the boundaries of the 50 states in the U.S., then your data table should have, at most, 50 records (i.e. rows)...one row for each state. You can click here to refer to a .pdf file on our website for tips on properly formatting your data table.
Need to have a Unique ID per map feature – For a data connection to be possible, you will have a map layer in AWhere that contains some features (e.g political boundaries), and you would also have some external table or database containing data that directly corresponds to the mapped features in the map layer. The critical key to being able to establish a data connection between the map layer and the data table is that each feature in the map layer must have some unique ID value (not shared by any other feature in the layer), and those unique ID values must also be present in the external data table (in the example seen below, the unique ID value is the country abbreviation). The unique ID value is the piece that enables you to establish a linkage between each feature (in the map layer), and its corresponding record in the data table. For more about the need for a unique ID value in reference to data connections, click here.
Sample Data Connection - Below is a visual example of how a data connection would work…in this case, connecting a table of country-level data for Central America to a Central America map layer in AWhere.
1) Sample Crop Data from FAO – This MS Excel (.xls) table contains some crop production data that I just grabbed from the ‘FAOSTAT’ page of the FAO (Food and Agriculture Organization) website; I selected a few different types of crops for which I wanted production information for the countries of Central America…these values are ‘tonnes produced’ for the year 2007. This is also to demonstrate to you that there is a vast amount of map-able data available out there on the internet. The file that was downloaded from the FAO website required a tiny bit of cleaning up to come away with the table you see below (refer to the .pdf file mentioned earlier in this post for tips on formatting the table correctly).
One key thing to take note of here is that each country in this table is identified by its 2-letter abbreviation (BZ = Belize, CR = Costa Rica, SV = El Salvador, GT = Guatemala, HN = Honduras, NI = Nicaragua, PA = Panama)…this will play an important role in a moment.
(Microsoft Office 2007 users…click here for some important information)
2) The Map Layer in AWhere – Below is a screen-shot of a Central America map layer in AWhere (the data connection to the above table has not been established yet), this map layer delineates the national boundaries of each country in Central America. This is the map layer to which you would want to connect the above table. The map layer is named ‘Central America’ in the image below…it is the only one loaded into this instance of AWhere, and is displayed and labeled using the ‘Abbreviation’ attribute (see the highlighted attribute in the treeview area to the left of the map...the countries are lableled here only for your visual reference, labeling is not required for establishing a data connection). You’ll notice that each attribute has a set of (Parentheses) next to it, this is the result of clicking on a feature on the map…the information about the map feature that was clicked was loaded in the treeview…in this case, you can see the I clicked on Honduras (note the cross-hair symbol on the map where I clicked).
3) Establishing the Data Connection – When connecting a data table to a map layer, you are in reality establishing a data connection to one of the map layer’s attributes. A map layer can have any number of attributes; this map layer has five…Country, Abbreviation, Currency, Population, and Area. The attribute that you choose to use for the data connection is directly dependent upon how the map features are referenced in the data table. Recall that in the sample data table above, the countries are identified using their 2-letter abbreviation…therefore, you must use the ‘Abbreviation’ attribute of the map layer to link to the table…you could not use the ‘Country’ attribute in the map layer (which holds the full name of each country) because the full country name is not present in this data table...that is, there is no field in this data table that contains the full names of the countries; you have only the 2-letter country abbreviations to work with (in this instance) in order to be able to establish a relationship between the table and the map layer.
I won't take you step-by-step through the Data Connection tool here, but it is very simple...only a few steps to establish the data connection. Basically you start the data connection tool by right-clicking on the attribute to which you will connect the data table; in this case, you would right-click on the 'Abbreviation' attribute there beneath 'Central America'. When you do that, a small context menu will appear…you would select the ‘Connect to My Data’ option from that menu…this starts the 'Data Connection Wizard' which would guide you through the remainder of the process. For more detailed instructions on how to establish a data connection, click here.
4) After the Data Connection – Once the data connection is established, the data from the table are now available for you to map within the AWhere interface. Look at the blue and red icon 
below the ‘Abbreviation’ attribute in the image below…you see the words ‘Crop Production 2007’. If you refer back to the sample data table above, and look at the tab at the bottom of that table, you will see that is the name of that worksheet in that .xls file. Thus, that red and blue icon indicates that you have established a data connection between the ‘Abbreviation’ attribute of this map layer, and that worksheet in that .xls file. All of the red icons 
listed below that represent the fields from that table; now they are ‘connected attributes’ that are made available via this data connection.
Again, I clicked on Honduras on the map, and the information about Honduras is loaded in (parentheses) next to each attribute…not only for the original (native) attributes that are part of the map layer (Country, Abbreviation, Currency, Population, Area), but also for the newly connected attributes (Bananas, Citrus Fruit, Coconuts, Coffee, Pineapples, Plantains). Compare the numbers that you see in parentheses next to those connected attributes below with the values for Honduras (HN) in the table above.
5) How to Map the Data from the Table – You can use various tools in AWhere to now visualize those crop production data values...in map form. For example, in the map image below, the ‘Bananas’ attribute is displayed using a light green to dark green color scheme (lighter greens indicating lower Banana production, darker greens indicating higher banana production). Also, the actual values are labeled on top of the countries on the map…again, compare the numbers on the map with the values in the 'Bananas' column in the table above. For more information on how to edit the Display Properties for attributes, set color settings, append Labels to the map, etc, refer to the main AWhere help documentation available from the ‘Help’ menu…look up these topics: 'Display Properties', 'Class Breaks', and 'Labels'
This next example shows the countries of Central America being displayed as just a solid grey color, but with bar charts displayed on each country, representing the relative production totals for Coffee, Citrus Fruits, and Plantains (see the legend on the left). For more information on how to add charts like this to the map, refer to the main AWhere help documentation available from the ‘Help’ menu…and look up ‘Map Charts’.
This final example shows that a separate graph of the data can also be generated in AWhere. For more information on how to create a graph like this, refer to the main AWhere help documentation available from the ‘Help’ menu…and look up ‘Graph Function’.
These are just a few examples of how you could represent the values from the dynamically connected data table in map and/or graphical form.