114
RAData should fit the work, not the other way around.
#UseCaseData #DataProducts #AnalyticsEngineering #QuestSoftware #erwinByQuest
@randyjrouse
#Web Analytics Basic Concepts
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145
SUSo when you ask Claude or Cursor to add a feature, it might scaffold a whole new table or completely change your existing database relationships without you even realizing it.
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And once you have real user data in production, migrations can be really painful. Like really, really painful.
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So before you let AI just generate database code, take 30 minutes and sketch out your data model on paper. What are your core entities? How do they relate to each other? What's the source of truth for each piece of data?
⠀
That 30 minutes of thinking will save you literally weeks of refactoring later. Trust me on this one.
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Follow me if you want help making sense of tech/AI and to actually use these tools more confidently and intentionally.
@sunnysaysyas
2.4K
DUMarc Lou just turned web analytics into a Severance episode.
Every page on your website is a department. Visitors are innies. They arrive through the elevator. Navigate to another page, they walk to the next department. Bounce, they walk out.
It's called Macrodata. Built on his own API, DataFast.
A month ago he opened up all of DataFast's endpoints. He thinks the future of SaaS is backends only.
AI will generate the UI layer on the fly. Personalized for each user. Every dashboard looking different because the interface gets built in real time.
So the Severance skin is proof that the same backend data can power completely different experiences depending on who's using it.
He's "you can just do things" personified. He shipped a working product that proves a thesis about where software is going.
If AI can generate any interface on demand, the companies that own the data layer win. The ones that only built pretty dashboards lose.
Follow if you build things
@dubibuilds
7.0K
NE“Misc” is usually a red flag.
It means:
• We didn’t define categories properly.
• We didn’t standardize inputs.
• We postponed a data decision.
• We gave up on cleaning.
And when you ignore it, three things happen:
1️⃣ Signal gets buried.
2️⃣ Models learn noise.
3️⃣ Insights become unreliable.
Here’s how to fix it properly:
Step 1 - Audit frequency.
Check how many records fall into “misc.”
If it’s > 5-10%, you have a taxonomy problem.
Step 2 - Re-cluster intelligently.
Look for patterns inside “misc.”
Group similar values into meaningful new categories.
Step 3 - Go back to source.
Why is “misc” being created?
Fix it at data entry level (validation rules, dropdown constraints, schema updates).
Advanced move:
If “misc” still holds value, encode it separately and test its impact on feature importance.
Clean data isn’t aesthetic.
It’s strategic.
Before you build a dashboard.
Before you train a model.
Kill the “misc” column.
#DataScience #DataCleaning #Analytics #MachineLearning
@newtonschoolofficial
3.6K
COColors can tell powerful data stories.
Heatmaps turn raw data into instant insights. Spot trends, patterns, and variations in seconds.
#DataVisualization #Heatmap #BusinessIntelligence #BI #DataAnalytics #DashboardDesign #Analytics #DataStorytelling
@codebasicshub
195
SU5 seconds. 9 interactive visuals. 1 career upgrade. 🚀
Custom visuals? ✅
AI visuals? ✅
Zoom, drill-down, Q&A? ✅
Your dashboard is incomplete without these. 📊💥
Quick question:
👉 Custom visuals or AI visuals – which team are you on? 🛠️ vs 🧠
Drop your answer below! 👇
Save this guide before you build your next report. Trust me. 🔖
Follow @SuhaniInsights for daily data truth bombs! 💣🔥
@suhaniinsights
4.2K
DSCombine charts and narratives for compelling data reports
@dswithdennis
744
DSSequence modeling capturing temporal dependencies in data streams
@dswithdennis
2.0K
DSTransform raw data into impactful visual narratives
@dswithdennis
605
TTEver wondered what really happens after you click “Refresh” on a dashboard? 🤔
Behind every clean chart and KPI lies a journey — queries firing, APIs responding, pipelines processing, and data transforming in milliseconds.
From raw rows in a database to meaningful insights on your screen — it’s not magic, it’s architecture. ⚙️📊
#DataEngineering #Analytics #Databases #BusinessIntelligence #TechExplained
@ttfaacademy
14.9K
SL📊 Day 23 of 30 React Projects — Analytics Dashboard
Raw data is useless until you turn it into a story.
Most apps collect data — great apps make it understandable. Dashboards do exactly that by turning numbers into insights you can actually act on.
What you’ll build:
• Stat cards for key metrics
• Line, bar, and pie charts for trends
• Clean dashboard layout with reusable components
• Tables for detailed breakdowns
You’ll use chart libraries like Recharts or Chart.js to transform raw data into visuals — while learning layout structuring, component reuse, and clean UI spacing that real SaaS products rely on.
By the end, you’ve built the same type of dashboard used in admin panels, analytics tools, and startups — the kind of project recruiters instantly recognize as real-world experience.
👉 Day 24 tomorrow: We’re building an E-commerce Product Page — where React meets real money.
Want the GitHub repo or tutorials? Comment “Day 23” and I’ll send them.
#ReactJS #DashboardDesign #DataVisualization #SaaS #Fr
@slashdevhq
38
ENFrom Data Chaos to Business Clarity
The Client: a platform that connects IT infrastructure, services, and business metrics into a single system.
The problem? Most monitoring videos focus either on engineers or executives - rarely both. And raw dashboards alone don’t explain why this matters for the business.
The Challenge:
- huge volumes of technical data
- multiple user roles (engineers, service owners, managers)
- complex hierarchies: services, layers, KPIs, events
- a need to visually explain cause → impact → decision in minutes
This couldn’t be another screen-recording demo.
The Solution:
A cinematic demo video that turns invisible processes into a clear visual story.
✨ abstract data streams transform into structured systems
✨ business and IT metrics visually connect in real time
✨ events evolve into alerts - without noise or “alert fatigue”
✨ one critical issue → one clear notification → one responsible engineer
Every scene was designed to reduce cognitive load while increasing understanding - from raw signals to actionable insight.
Since release, this video has become a frequent reference - and other monitoring & SaaS companies keep asking for the same structured, cinematic approach.
Because clarity sells. Especially in complex systems.
📩 Building a platform that’s powerful but hard to explain?
Let’s turn complexity into a story your audience instantly understands.
#motiondesign #demovideo #saasvideo #itmonitoring #productvideo #b2bvideo #animationstudio
@endorphin_studios
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