Shane Butler’s Post

Ready to refresh your understanding of statistical models? Join us for an in-depth exploration of "Linear mixed models - a refresher and introduction." 🚀 Step into the world of statistical modeling excellence as we decode the intricacies of Linear Mixed Models. From handling complex data structures to unlocking hidden patterns, this episode is your gateway to mastering statistical analysis. 🔍 Are you ready to level up your data analysis skills? Tune in to our podcast and embark on a journey of statistical enlightenment! 🔗 Listen now: https://lnkd.in/eby8YqDg #Statistics #DataAnalysis #LinearMixedModels #StatisticalModeling #DataScience

What does it mean to be a data scientist? Our Principal Data Scientist Dan Parshall sat down with DATAVERSITY for their "My Career in Data" podcast. While Dan always wanted to be a scientist, listen to how he ended up working with so much data. https://bit.ly/46FK7pB #DataScience #DataScientist #Podcast

Let's use Excel instead of dashboards! 😲 Out from my Plumbers of Data Science podcast episode "Why Excel should be a go-to tool for data professionals". Watch the complete episode here: https://bit.ly/3WoM2Lz #dataengineer #dataengineering #datascience #dataanalysis #excel #datadashboards

Let's use Excel instead of dashboards! 😲 Out from my Plumbers of Data Science podcast episode "Why Excel should be a go-to tool for data professionals". Watch the complete episode here: https://bit.ly/3WoM2Lz #dataengineer #dataengineering #datascience #dataanalysis #excel #datadashboards

Modeling layers are the key to overcoming complexity.

Composable data systems are not the quick and easy path. But they win the race in the end. Wes McKinney explains in this podcast: ❝ It’s like the tortoise and the hare. I think the modular data stack (horizontal integration) approach is definitely the tortoise approach. It requires a lot of open source diplomacy, a lot of coordination across projects, like getting people to agree to specialize and then work together toward productive ends. It’s definitely very laborious, but we’ve had our heads down just doing that. So now we’ve got really great open source orchestration solutions, we’ve got good modular computing engines, we’ve got open data lake formats, we’ve got open source file formats, we’ve got protocols for building database drivers and building distributed systems that use these open standards and protocols. All the pieces are falling into place. It takes a lot more time than building a vertically integrated system, but I think ultimately we’re doing the reverse Tower of Babel approach. We’re going to get to a place that’s more interesting and ultimately has a lot better staying power and lends itself also to better long-term maintainability. ❞ But you'll have to listen for yourself if you want to hear Wes's "Raiders of the Lost Ark" analogy 😂

great discussion as always. The notion of "medium code" is accurate. In most of the organizations I've been in, you find quite a lot of business logic trapped in various roles at that layer. Targeting them as first-class customers of the data can unlock a lot of value.

ClickHouse String Function Guide on the ClickHouse Podcast 💡 🚀 Looking to level up your ClickHouse skills? 📈 Check out this essential guide on ClickHouse string functions! 📚 From basic operations to advanced manipulations, this resource covers it all. 🧰 Here's what you'll find: • Introduction to string functions: 🔤 Understand the power of string functions and their role in data processing. • Basic string functions: 📏 Learn how to determine string length (length, lengthUTF8) and check for emptiness (empty, notEmpty). • String replacement functions: 🔁 Master the art of replacing substrings with replaceOne, replaceAll, replaceRegexpOne, and replaceRegexpAll. • Substring functions: ✂️ Extract specific segments of data with substring and substringUTF8, and explore advanced extraction techniques. • String concatenation: 🔗 Combine strings efficiently using concat and concatWithSeparator. • Case conversion functions: 🔠 Standardize data formats with upper, lower, upperUTF8, and lowerUTF8. • Padding functions: 📏 Format and align data effectively with leftPad, rightPad, leftPadUTF8, and rightPadUTF8. • String reversal and repetition: 🔁 Manipulate strings uniquely with reverse, reverseUTF8, and repeat. • String search functions: 🔎 Locate specific data points within strings using position, multiSearchAny, multiSearchAllPositions, and multiSearchFirstIndex. • Trimming functions: ✂️ Clean and format data by removing unwanted characters with trim, trimLeft, trimRight, and trimBoth. • Regular expressions: pattern matching: 🔣 Perform advanced pattern matching with like and regexpExtract. This comprehensive guide also provides clear explanations, practical examples, and comparisons to equivalent functions in other popular database systems. 📊 Apple Podcasts: https://lnkd.in/gbjx5g4B Spotify: https://lnkd.in/gVSJmTQv #clickhouse #database #sql #dataengineering #dataanalysis

🎙️ New Episode: Klaviyo's Data Science Podcast🎙️ https://lnkd.in/gE5UqxeY Wish you could give your younger self some advise? 4 senior members of our data science team sit down to reflect on what they know now and what they wish they'd know earlier in their career: 🎙️ How taking a more scenic or indirect career route can impart valuable experiences 🎙️ The growth and development opportunities that truly unlocked new phases of their careers, and how you can make the most of similar opportunities 🎙️ Why mistakes often make the best learning opportunities

Here is my first effort on NotebookLM to make data science easy and fun for myself and for others. This podcast beautifully explains hypothesis testing in a very easy way. I have tried to keep it short and to the point. Do listen to it and give your feedback. Happy learning! More to come.