Lisa Hoving
Big Data Engineer @ Rabobank| Microsoft Data Platform MVP
Hilversum, The Netherlands
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Your friendly neighbourhood Data Engineer. My background is in Finance, but I have had the pleasure to be working in IT for the past 5 or so years. In my daily life, I design and build scalable data solutions in the Azure cloud.
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Autism, ADHD, and the workplace: The pleasures and pain of unmasking
Let’s face it. The public view on autism and ADHD is not all that great. In the media, we tend to be portrayed as quirky at best, and robot-like at worst. All this misinformation makes it difficult for our co-workers to get a grasp on what neurodivergence really means. Knowing this, is it really that surprising they struggle to accommodate us too?
So, how does a neurodivergent person navigate in a work environment that is (most likely) not accommodating? Unmasking! What that means? I will explain it to you in this talk. Spoiler alert: unmasking is not an easy feat!
During this session, I will tell you more about what my autism and ADHD diagnosis meant to me. Next, I will speak about what masking is, and how this prevented me to function properly at work. Lastly, I will talk more about unmasking: what it is and why it’s so difficult. But also: why it’s so important, and how it helped me.
Note: This session will have an open format. If you want, you are more than welcome to share your own unmasking story with the audience.
Azure Data Factory, Azure Databricks, or Azure Synapse Analytics? When to use what.
Have you ever found yourself at the start of a data (engineering) project, unsure about what tool to choose? Speak no more! In this session we will discuss three often used (data engineering) tools on Azure:
- Azure Data Factory
- Azure Databricks
- Azure Synapse Analytics
First, I will give a brief introduction to each tool, including for what use cases they are commonly used. Next, we will talk about what makes these tools different, and where they overlap (and believe me, they do). Lastly, we will arrive at our conclusion: when to use what. Of course, a slide on differences in costs will be included as well.
What my pet python taught me about Data Lakes on Azure
Have you ever looked at a snake and thought… this one needs a Data Lake? Me neither! That is, not until I got my pet Python. It was when I got him, I realized that taking care of reptiles requires special care, using very specific equipment. However, as we all know, technology is prone to failures. This got me thinking… how am I going to give my pet python the best care, day in day out, even when technology fails? As a Data Engineer, the answer was easy. My snake needs a Data Lake! … wait what? You implemented a Data Lake for your pet python? Yes!
Why? How? We will speak about it during this session. First, we will talk about what Data Lakes are, why they exist, and how I intended to use Data Lake architecture on Azure. Next, we will talk about the technology used, and the lessons learned.
All in all, it will be a talk about my favourite topics:
- Snakes
- Data Lakes
- Azure:
o IoT Hubs
o Azure Data Lake Storage
My pet python’s name is fluffy, by the way. Just in case you were curious 😉.
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Lisa Hoving
Big Data Engineer @ Rabobank| Microsoft Data Platform MVP
Hilversum, The Netherlands
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