Merv Adrian’s Post

Just because we can catalog data assets does not mean they are easy to find. The sea is full of fish, but they take time and effort to catch. It should not be the same for data – we need to think carefully about our audiences, what they need, and how they might search. Enjoy the video: https://lnkd.in/eHecDXww #datacatalog #data #datagovernance #metadata #datamanagement

My contribution for the #30DayChartChallenge | Day 16 - Weather, using R. Given my humor's susceptibility to sunshine, I created this visualization to make more adequate future plans 😉 #DataVisualization #DataViz #DataVizSociety #RStats #ggplot2Tutorial

🐦🔎 Want to predict the distribution of a species in R using ALA data? ⚡ Learn how to run a species distribution model using a modern tidymodels workflow in a new ALA Labs post by Dax Kellie & Shandiya Balasubramaniam! 🔗 http://spr.ly/6046jHA7n #rstats #dataviz #quartopub

I can totally relate to her experience (well apart from not being a woman) and share her thoughts on academia. My saving grace was that I always liked to study and explore different things which is very bad if you want to get a tenure track but it is the "data-scientist" job description: I was a data-scientist before being a data-scientist become a thing. Luckily for me "data science" became a thing before I could starve, and here I am. Today, I just publish articles about rainfall and its statistical modelling because I like it and I can :D. My last article involves the analysis of the largest amount of disdrometer data ever done: https://lnkd.in/e__28V-T and you can reproduce it too: https://lnkd.in/eYeCZjiX https://lnkd.in/eQtSVV2q

We wanted to share about Using Intricate Weather Data in Caspio and how we do it. Using the extensive Visual Crossing data source, WorkMovr can display intricate current, historical, and forecasted Weather information for any specific narrow Location. The cost of water and fertilizer can be surprisingly high for agriculture, cities, golf courses, and even small housing developments. In this video, our CTO, David Talbot, will talk in more detail about how it works. Let us know if you have any questions! Contact us for more - workmovr.com/contact/ https://lnkd.in/e_qfpSBG #caspio #caspiopartner #workmovr #caspiodeveloper #weather #weatherdata #lowcode #nocode #api

🌌 Day 2 of "Data Science Nuggets": Diving into the Core - Samples, Populations, and Distributions 🌌 Ever wondered how data scientists make predictions about the future, understand current trends, or infer behaviors of a whole population from a small dataset? Today's nugget unfolds the magic behind Samples, Populations, and Data Distributions.

"Excited to share this Probability Distribution helpful sheet! Whether you're a seasoned analyst or just diving into statistics, this resource simplifies complex concepts. Enhance your understanding and ace your next analysis." Created by Raze Bagheri #Statistics #DataAnalysis #Probability

From Cattle to Clarity: Visualizing Thousands of Data Pipelines with Violin Charts https://bit.ly/3XieaiE #dataops #dataobservability

Bigfoot was first sighted in 1958 but has never been caught—could the answer to this elusive beast lie in the data left behind? 🐾📊 With growing data analysis responsibilities and recent projects at work pushing my skill set to new limits, I’ve taken some personal time to develop these new capabilities—especially in data storytelling and visualisation. 📊 To put these skills to the test, I explored an interesting dataset: Bigfoot sightings, provided by the Bigfoot Field Researchers Organization (BFRO). 🐾🔍 Check out the dataset here: https://lnkd.in/e7VSZ4wc View the full report here: https://lnkd.in/e_6vEjE4 This report delves into: 🔎 Trends in sightings over time 📍 US State hotspots for Bigfoot sightings 📆 Seasonal fluctuations in sightings This project has been an exciting opportunity to apply lessons from my recent professional work—like analyzing location data and generating actionable insights—in a creative and engaging way. I'm eager to continue growing my expertise in data analytics and visualisation and seeing where this journey takes me! #PowerBI #DataAnalytics #Cryptid #DataVisualization #DataStorytelling #LearningAndGrowing #ProfessionalDevelopment

Edward Tufte, one of the pioneers in the field of data visualization, considers Minard’s chart as “probably the best statistical graphic ever drawn.” Why is it considered magnificent? Why is Tufte’s chart a good visualization? – The visualization depicts Napoleon’s army departing the Polish-Russian border. It’s a bitter and cold winter. You can see the trajectory of the march and the geography of the landscape such as rivers. There is a thick band that illustrates the size of his army at specific geographic points during their advance and retreat. It displays six types of data in two dimensions: ✔The number of Napoleon’s troops ✔ The distance traveled ✔ The temperature ✔ Latitude and longitude ✔ Direction of travel ✔ Location relative to specific dates without making mention of Napoleon Here is Charles Minard’s 1869 chart showing Napoleon Bonaparte’s 1812 Russian campaign of his army and their movements. https://lnkd.in/dgyMXHgT Source: https://lnkd.in/d-VTAsM2 #datavisualisation #datavis #data #visualizations #narrative.#visualize #Datastorytelling #visualizeandtellastory #chart #graph #map FYI ! Paolo Ciuccarelli