Write something
Pinned
Jul '23 •
Welcome to Data Alchemy - Start Here
The goal of this group is to help you navigate the complex and rapidly evolving world of data science and artificial intelligence. This is your hub to stay up-to-date on the latest trends, learn specialized skills to turn raw data into valuable insights, connect with a community of like-minded individuals, and ultimately, become a Data Alchemist. Together, let's decode the language of data and shape a future where knowledge and community illuminate our way. Rules - Don't sell anything here or use Data Alchemy as any kind of funnel - We delete low effort community posts, and posts with poor English. Proofread your post first. - Help us make the posts high quality. If you see a low quality post, then click on the 3 dots on the post and "Report To Admins". Start by checking out these links - Classroom - Introduction - Roadmap - Contribution Be Aware of Scammers - Please be aware that this is a public group. Unfortunately, some people abuse the Skool platform to send DMs or post comments to trick people. This is the internet, so always do your own due diligence. Never automatically trust someone here on the Skool platform other than @Dave Ebbelaar's official account. To kick things off, please comment below, introducing yourself. Let us know: 1. Your name and where you're from 2. What project(s) you're currently focused on See you in the comments!
Pinned
Nov '23 •
Unlock New Courses at Level 3
Hey everyone, I just completed a new course for you: "Data Science Accelerator". This course will be unlocked, together with "Building Applications with LLMs" at level 3. How to level up? Just interact with the group, get likes and comments, and watch your level go up!
4h •
Why “real-time data” is useless without real-time interpretation
Everyone wants real-time pipelines. Very few ask: What decision actually needs to happen in real time? Streaming data without interpretation is just noise at higher velocity. A mature data system separates data speed from decision speed. Here’s how advanced stacks do it: 1️⃣ Signal Timing Classification Signals are labeled as: • immediate (fraud, outages) • short-term (pricing, allocation) • long-term (strategy, retention) Not everything deserves urgency. 2️⃣ Interpretation Windows Each signal gets a time window: • seconds • minutes • hours This prevents reacting too early to unstable patterns. 3️⃣ Confidence Accumulation Decisions trigger only after: • enough corroborating signals • sufficient confidence buildup Speed without confidence destroys trust. 4️⃣ Action Throttling Systems limit how often decisions can fire. This avoids oscillation and overcorrection. 5️⃣ Post-Decision Review Every real-time decision is reviewed later: • was speed actually beneficial? • would delay have improved outcome? This trains judgment over time. Data alchemy isn’t about faster pipelines. It's about timed intelligence. Knowing when to decide is more valuable than knowing what happened.
0
0
10d •
One thing most teams misunderstand about “data-driven”
Being data-driven isn’t about reacting to numbers. It’s about deciding in advance: • which signals matter • which decisions they inform • and which ones you’ll ignore Most dashboards fail because they show everything. The strongest teams I’ve worked with do the opposite: They reduce data until only decision-critical signals remain. AI makes it easier to compute. It doesn’t make it easier to choose. That part is still human. Good data systems don’t answer more questions. They answer the right ones, consistently. Something I’ve been thinking about recently.
17h •
🚀 GPT-5.2: A New Standard for Professional Work
🔥 OpenAI introduces GPT-5.2, the most advanced model ever built for professional work and long-running AI agents. To get more, click here:🔗https://lnkd.in/e7WgexzJ
0
0
1-30 of 4,197
skool.com/data-alchemy
Your Community to Master the Fundamentals of Working with Data and AI — by Datalumina®
Leaderboard (30-day)
1
+203
2
+76
3
+32
4
+28
5
+21
Powered by