Skyscraper Map in Power BI, aka. bar chart map, or bar chart on a map
Have you ever seen a bar chart on a map?
I prefer to call this visualization a skyscraper map because you can picture these bars on a map as skyscrapers.
You can use a skyscraper map for displaying geodata along values. The skyscraper map is a combination of a map with locations and a bar chart. The location can represent a city, a country, or some other type of place. As with a bar chart, the height or volume of each bar is proportional to the values it represents.
How to create a Skyscraper Map with Azure Maps in Power BI
Some exciting new features in Power BI are not enabled by default. These functions are so-called preview features whose development or testing is not yet completely finished. For certain use cases, such as creating Skyscraper Maps in Power BI, it may be worthwhile to activate them.
In the following blog posts, we will check out some capabilities of the Azure Maps feature. Therefore, let’s see how you can enable Azure Maps, and other preview features, in Power BI.
A few weeks after the fantastic Tableau Conference in New Orleans, I received an email from a data scientist who attended my TC18 social media session, and who is using Azure+Tableau. She had a quite interesting question:How can a Tableau dashboard that displays contacts (name & company) automatically lookup LinkedIn profile URLs?
Of course, researching LinkedIn profiles for a huge list of people is a very repetitive task. So let’s find a solution to improve this workflow…
1. Python and TabPy
We use Python to build API requests, communicate with Azure Cognitive Services and to verify the returned search results. In order to use Python within Tableau, we need to setup TabPy. If you haven’t done this yet: checkout my TabPy tutorial.
2. Microsoft Azure Cognitive Services
One of many APIs provided by Azure Cognitive Services is the Web Search API. We use this API to search for name + company + “linkedin”. The first three results are then validated by our Python script. One of the results should contain the corresponding LinkedIn profile.
3. Calculated Field in Tableau
Let’s wrap our Python script together and create a Calculated Field in Tableau:
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Adding a URL action with our new Calculated Field will do the trick. Now you can click on the LinkedIn icon and a new browser tab (or the LinkedIn app if installed) opens.
My TC18 sessions in New Orleans: “Rock your Social Media Data with Tableau”
Anyone can analyze basic social media data in a few steps. But once you’ve started diving into social analytics, how do you bring it to the next level? This session will cover strategies for scaling a social data program. You’ll learn skills such as how to directly connect to your social media data with a Web Data Connector, considerations for building scalable data sources, and tips for using metadata and calculations for more sophisticated analysis.
Here are some key takeaways and links (i.e. additional resources) featured during my TC18 sessions to help you formulate your social media data program in order to build a stronger presence and retrieve powerful insights:
Step 1: Understand How to Succeed with Social Media
Apple has officially joined Instagram on 7th August 2017. This isn’t your average corporate account as the company doesn’t want to showcase its own products. Instead, Apple is going to share photos shot with an iPhone:
And there are plenty takeaways for every business:
Wrap your data around your customers, in order to create business value
Interact with your customer in a natural way
Understand your customer and customer behaviour better by analyzing social media data
Step 2: Define Your Social Objectives and KPIs
A previous record-holding tweet: In 2014, actor and talk show host Ellen DeGeneres took a selfie with a gaggle of celebrities while hosting the Oscars. That photo has 3.44 million retweets at the time of writing:
Social listening means that you look beyond your own content. E.g. Talkwalker offers AI for image recognition and ggregation for online/offline media: http://bit.ly/tc17_talkwalker
Are you ready for Tableau Conference 2018? Don’t miss my Social Media Analytics sessions!
Why do we need Social Media Analytics?
Social Media Analytics transforms raw data from social media platforms into insight, which in turn leads to new business value.
What will your learn in this sessions?
Once you dive into Social Media Analytics, how do you bring it to the next level? Social data can offer powerful insights right away. In this session, you will learn how to build a mature social data program from that foundation and strategies for scaling a social data programme, as well as how to connect directly to your social media data with a web data connector; considerations for building scalable data sources; and tips for using metadata and calculations for more sophisticated analysis.
Where and when are the sessions?
Do you want to learn more about Social Media Analytics with Tableau? Meet me at the 2018 Tableau Conferences in London or New Orleans and join my sessions:
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