Welcome to the Data & Analytics Tutorials section of my blog, where I share my knowledge and expertise on all things related to data and analytics. As someone who has spent over a decade in the data domain, I’m passionate about sharing what I’ve learned with others and helping them succeed in this exciting field.
In this section, you’ll find a wide range of tutorials on topics such as data visualization, machine learning, data analysis, and more. Whether you’re a beginner just starting out in the field, or an experienced professional looking to expand your knowledge, these tutorials will provide you with the practical skills and insights you need to succeed.
My goal is to make these tutorials as accessible and easy to follow as possible, with step-by-step instructions and real-world examples. I believe that everyone should have the opportunity to learn and grow in the world of data and analytics, and I’m committed to making that a reality through these tutorials.
So, whether you’re looking to improve your skills, expand your knowledge, or just learn something new, join me on this journey as we explore the exciting world of data and analytics together.
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.
Visual traceroute (aka. tracert) from Frankfurt to Ukraine shows redirection via Russia
Earlier today I read the news from NetBlocks (via Reuters) that since the weekend parts of the Ukrainian internet traffic are rerouted via Russia. To be precise, it’s about Ukrainian Kherson Oblast, which is occupied by Russia since March.
Now I wanted to trace the internet route myself and ideally visualize it. Here I came across the service of GeoTraceroute, which does a great job in visualizing traceroutes (aka. tracert). For the trace, I chose Frankfurt as starting point, and skynet.ua, the local internet provider in Kherson, as the endpoint.
Of course, you can also include the URL of GeoTraceroute as a web element in your Power BI report or Tableau dashboard and parameterize it for dynamic interactions. You can see the format as in my example:
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
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