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.
Welcome to the fascinating world of data visualization, where even maps can take the form of bar charts! I prefer to call this visualization a Skyscraper Map because you can picture these bars on a map as skyscrapers. Also known as a Bar Chart Map, this type of visualization brings your geodata to life, giving it the appearance of skyscrapers dotting a cityscape.
Why Use a Skyscraper Map?
You can use a skyscraper map to display geodata along with its corresponding values. This innovative visualization combines a map indicating various locations (be it a city, a country, or any geographical place) with a bar chart. Like a traditional bar chart, the height or volume of each bar in a skyscraper map is proportionate to the values it signifies.
Crafting a Skyscraper Map with Azure Maps in Power BI
Step 1. Click on the Azure Map icon in the Visualization pane.
Step 2. Drag the lower right corner to extend the filled map visual.
Step 3. From the Fields Plane, select PostalCode.
Step 4. Now, choose TotalSales from the Fields Plane.
Step 5. Head over to the Format your Visual section.
Step 6. Toggle off the Bubble layer switch.
Step 7. Enable the Bar chart layer switch.
Step 8. Expand the Bar chart layer pane.
Step 9. Expand the Size pane.
Step 10. Under the Size pane, set the Height to 4 px.
Step 11. Under the Size pane, set the Width to 3 px.
With these steps, you’ve created a skyscraper map showing sales by zip codes in your dataset. Want to try it out? Download the PBIX file here.
If you’re keen on diving deeper into Power BI, don’t miss my book, Teach Yourself VISUALLY Power BI (Amazon), filled with more insightful tutorials like this one. Got any feedback, ideas, or questions about creating bar chart maps in Power BI? I’d love to hear from you:
Microsoft’s Power BI is known for its data visualization capabilities, but many exciting features are not enabled by default. These under-the-radar features are known as Power BI Preview Features, and they often have the potential to significantly enhance your data analysis efforts. Some of these exciting features include Azure Maps, which is essential for creating impactful Skyscraper Maps with Power BI.
Follow this Step-by-step Guide
To leverage the power of these Preview Features, you need to enable them in your Power BI interface. Here is a quick guide to help you activate Azure Maps and other Preview Features:
Step 1: Navigate to the File tab on Power BI’s menu bar. Note: There is no need to have a data connection, the opening modal can be closed.
Step 2: Choose Options and Settings from the dropdown menu.
Step 3: From the subsequent options, click on Options.
Step 4: In the new dialogue box, select Preview Features from the list on the left-hand side.
Step 5: Check the box next to Azure Map Visual to enable it.
Step 6: Confirm your changes by clicking the OK button.
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:
How can a Tableau dashboard that displays contacts (name & company) automatically look up 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…
Step by Step: Integrating Azure Cognitive Services in Tableau
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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This tutorial is just the tip of the iceberg. If you want to dive deeper into the world of data visualization and analytics, don’t forget to order your copy of my new book, Visual Analytics with Tableau (Amazon). This comprehensive guide offers an in-depth exploration of data visualization techniques and best practices.
I’d love to hear your thoughts. Feel free to leave a comment, share this tweet, and follow me on Twitter and LinkedIn for more tips, tricks, and tutorials on Azure Cognitive Services in Tableau and other data analytics topics.
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:
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