Enhance Your Data with Geo Maps – SAP Web Intelligence

Adding Geospatial Maps to your Business Intelligence reports and dashboards can provide a great way to visualize and ultimately better understand what drives or impacts your business. If any part of your organization is distributed geographically (e.g. Customers, Patients, Stores, Plants) layering your internal metrics onto a dynamic map view will certainly improve insights.

Geo-Maps are available in all of the core BI suite tools (except, strangely, Crystal Reports natively). This short blog series will aim to differentiate the features by tool and highlight some strengths and weaknesses of each one. First, we will look at Web Intelligence, then Lumira Discovery, and finally Lumira Designer.

Working with Geo Maps in Web Intelligence

SAP added basic Geo Maps to Web Intelligence in version 4.2 and have slowly improved the available features. 4.2 Service Pack 3 saw the much-needed addition of Latitude and Longitude binding; this allows us to get down to the street address level rather than being limited to large cities. However, we the report developers, need to provide the lat/long data. The map does not “geo-code” address information like Google Maps does (I’ll talk more about this later!). In this blog, I’m going to create a very simple geospatial map in Web Intelligence and show “By Name” binding. I’ll talk about some of the features and limitations and in the follow up I’ll contrast that to the By Latitude / Longitude binding.

The Basics

There are three types of Geo Map in Web Intelligence:

  1. Geo Bubble
  2. Geo Pie
  3. Chloropleth

In the first example, we will use Choropleth which shows color range or density in proportion to the measure being displayed on the map, such as population density or per-capita income.
First, we need to have a dataset/query that contains, at a minimum, one of the following: City, Region (e.g. State in North America), Country – and, of course, something to measure (e.g. Sales Revenue, Student population, Inventory). We can add more measures and dimensions for additional analysis.

Once we have the results data, we need to change the following dimensions into geo-dimensions by right-clicking and choosing ‘Edit as a Geography > By Name…’

Sale Country, we choose ‘Country’ from the Level drop-down.

We ensure all country values have been resolved to a known value.

Warning: Web Intelligence does quite well at identifying locations at the Region and Country level, but is limited in this mode to Cities with more than 100,000 population – This may cause issues if you’re working with a smaller detailed analysis. Don’t worry though, we have a workaround for this!

We repeat the geo-dimension process for ‘Sale State’ (Level: Region).

We now add a Geo Choropleth chart to the report canvas, to the right of the column chart.

Now, we Assign Data to the chart and choose the following:

  1. Main Item Key: Sale Country (geo)
  2. Map Item Value: Sales Total

Finally we can adjust additional properties of the map, let’s say we want to change the number of bands for the alerting, we can right click on the geo map and select Format Chart Plot Area (just like any other WebI chart).

There is a host of custom settings here, and it can be a bit confusing finding the exact part of the map to customize. Make sure you familiarize yourself with all of the options as it is very flexible.

We’re going to select Palette and Style to change the Ranges to a more detailed segmentation.

Wrapping it up

So, we have our first geo-map in Web Intelligence! In the next blog, we will add latitude and longitude data for more fine-grained analysis and we’ll also look at some of the additional formatting features. In the meantime, if you like the look of geo-maps and what to learn how to add then to professional looking reports, then read our relative position blog. Alternatively, visit our Web Intelligence page.

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By |2018-09-02T17:39:44+00:00December 19th, 2017|Business Intelligence, Geo Map, Kingfisher, Web Intelligence|0 Comments

About the Author:

Shaheen has more than 13 years of experience with a strong background in BI Analytics, Data Warehousing, and ETL Architecture. She enjoys working with clients finding solutions to their BI reporting problems. She has helped many healthcare clients with data cleansing projects, along with designing data marts and establishing BI reporting infrastructure. When she’s not cooking delicious food or enjoying hikes in the mountains, you can reach her at Shaheen.Makandar@kingfisherinc.com.