Distilled Side-Effects

Data Storytelling Tips Data Storytelling Challenges Raise your hand if you find telling stories with data challenging. For data analysts (or those aspiring to be), much of your day involves taking numbers and giving them meaning. If I say “150” and just leave that number hanging, what does it mean? Is it the price of a watch, a percentage increase in stock, or the distance a train has traveled? As an analyst, your job is to define numbers and give them context. For example, “150” could be the number of cars your company didn’t rent out over the weekend. That might represent 50% of your rentable vehicles, which in turn means revenue could be down by 30% compared to last weekend. While those insights can be verbalized or written down, the real challenge comes when you have to present them visually. What type of graph should you use? Which colors, data points, and legends will best convey the story behind the numbers? Why even use graphs, you might ask? One reas...

Azure, Microsoft's cloud platform, offers a comprehensive suite of tools and services designed to manage data throughout its lifecycle. As a data engineer, your role involves integrating, transforming, and consolidating data from diverse structured and unstructured sources. Azure is engineered to ensure that your data pipelines and data stores are high-performing, efficient, organized, and reliable, while meeting specific business requirements and constraints. Why Use Azure's Tools and Resources? Azure's tools simplify the data engineer's life. For instance, you can use Azure alongside Visual Studio Code to manage data pipelines, and Azure can handle much of the data analysis, provided the data is appropriately cleaned and structured. One of Azure's standout features is its ability to work seamlessly with structured, semi-structured, and unstructured data: Structured Data: Typically comes from table-based source systems. Se...