Guest Post: GeoFlow using Panama’s Census Data

imageIntro from Rob

Very busy week for me.  Fortunately Miguel is at the ready with another guest post.

It occurs to me that we’ve now had guest posts from the US, the UK, Holland, Canada, and Panama.  That’s pretty cool. 

Miguel told me that I was going to LOVE the first picture in this post.  And I do.  But I must say that, once I saw the title, I expected something along the lines of the picture at the right.  The picture below is better.

OK, over to Miguel…

image001

Figure shows the population distribution for Panama in 2010
Made Entirely in Excel!

If you read my latest guest post at Powerpivotpro’s blog, you’ll know that I’m working on a personal project trying to get a more visual aproach of the latest census Data for the country of Panama (where I’m from and I currently live in).

So far, I’ve managed to map more than 600 points on my map with their respective coordinates and I was able to use the heat map but then I found out that we couldn’t use the Choropleth map style (the ones that color the entire region) but instead we could play with the point’s radius and the intensity of the colors in the heatmap.

What’s GeoFlow anyway?

It’s a tool that complements what Power View hasn’t been able to bring to the table which is:

  1. 3D Mapping
  2. Heatmaps
  3. Predefined Scenes and story-telling like scenarios (record cinematics)

which translates into enriching the current experience of the user by bringing a new way of interacting with your data (data exploration and more story-telling).

Moreover, what I find extremely useful is that if I wasn’t aware of the territory, I’d be able to go deeper into the map and really dig into the areas surrounding the most heated locations so I could see if there’s any correlation between the point being mapped and perhaps another destination.

Perhaps there are blank spots because these are ‘protected forest areas’?

The Chart types that you get are:

  1. Bubbles
  2. Columns
  3. HeatMap

Click here to download the add-in if you haven’t done it yet.  (NOTE that GeoFlow is 2013 only!)

Interactivity and Sharepoint Integration? No? Okay…

One of the most ambitious efforts put into the latest tools of Excel 2013 like Power View and Powerpivot, it’s the interaction that the end-user has with the tools themselves. With Power View you get incredible dashboards like this one:

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Where the end-user could slice and dice the data either on Excel 2013 or even on the web with the Sharepoint Integration but, on the other hand, there’s no corporate story behind GeoFlow as it’s only an end-user tool for now with Excel 2013.

What about the filtering inside GeoFlow? well, I haven’t been able to see this feature yet so in order to filter data you’ll need to do it from the source before using GeoFlow

Understanding how BING works to map your location points

Now, here’s where the tricky part comes. In a nutshell, your dataset is not likely to get a 100% accuracy when your points get mapped. Bing will take your data and try to find an exact match or an approximate match.

Why? Because it depends on how unique the name of the Place that you’re trying to map is. For example, I tried mapping a location within Panama by the name of Paris and BING ended up mapping Paris, France. On a second attempt I tried using a concatenation of that place and the name of my Country but we ran into a new issue.

Thankfully, GeoFlow gives us some Geocoding alerts in case there were some mismatch or close matches when you click in the link that has the % of results mapped:

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This is the window that you get:

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alert, caution, exclamation, exclamation mark, sign, triangle, warning icon= there was a close match and it will be mapped using the location shown in the Result column

cross, delete, remove icon= there was no match at all and it will not be mapped

Fundamentally, in order to get better mapping results you’ll need to learn how BING works and how you can try to make things easier for BING to map your data. (if you have coordinates, use them)

This will be a completely new post on better practices when trying to use maps with Power View and GeoFlow!

Using Layers

Whenever you use GeoFlow, you’ll notice that you’re basically creating:

  1. Scenes
  2. Each one with 1 or more layers

and the layers can be mixed, let’s say that I have a heatmap and on top of it I want to have some 3D Columns based on something else.

Practical Case

Let’s say that I have the population distribution for Panama and I want to use it as my base-layer and then on top of it I’d like to analyze the sales of my product just to see if there’s any correlation on amount of population and the amount of sales. I could change the measure used from population to let’s say, amount of resellers or stores within a particular area and so on. You get the idea Smile

More Population = more sales? or perhaps I’m selling more in an specific place for specific customers?

Power View or GeoFlow ? Why not blend them together as Power View 2.0 ? (a switch to show your map in 2D or 3D)

I’d love to have the 3D Mapping and heatmaps as part of Power View in order to provide an extremely immersive yet dynamic way of data discovery but it seems that the immersive experience in a 3D Map it’s what Microsoft is heading towards to and as a completely separated tool from Power View. But, wouldn’t be cool if Power View could support heatmaps and 3D Maps?

Either way, GeoFlow tries to give you the most immersive experience that you can possibly find to interact with your geographical data and it’s something that is worth trying.

Also, I’ll be posting a more in-depth analysis about the Panama Census data on my blog using GeoFlow and Power View in case you’re interested in that.

2 Responses to Guest Post: GeoFlow using Panama’s Census Data

  1. Don Wise says:

    Thanks for this post; I’ve been following your site for some time. I work for a 9-1-1 (Fire/EMS Comm. Center) in the greater Los Angeles area and data analysis is a big thing these days for justifying continuing use of Fire/EMS resources and maintaining certain levels of service in the community. Who’d of ever thought that Police/Fire budgets would be reduced!

    I was able to successfully use both of these add-ins with some raw data and achieve good and meaningful results. These two tools are great by themselves, but notedly each have their drawbacks; it would be ideal if they were combined as you suggested. Someday I hope to have the time to dive into more PowerPivot and DAX understanding…again, thank you!

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