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☸️ React JS → User Interfaces

👌🏻 Three JS → 3D on the Web

⏳ Date.js → Time & Date

📊 D3 JS → Data Visualization

🎞 Anime JS → Animation library

📱 React Native → Mobile Applications

👨🏻‍💻 TensorFlow.js → Machine learning

🚀 Next.js → Server-side rendering and static site generation

🌐 Node.js → Backend development

📄 Express.js → Web application framework for Node.js

🔍 Lodash → Utility library for simplifying JavaScript

🖼 Chart.js → Simple and responsive charts

🎨 GSAP (GreenSock Animation Platform) → High-performance animations

📦 pnpm → Package manager for JavaScript

🔐 Passport.js → Authentication middleware for Node.js

📚 Storybook → UI component development and documentation

🧪 Jest → Testing framework for JavaScript

🔄 Redux → State management for React applications

🌊 Vue.js → Progressive JavaScript framework for building UIs

🔥 Svelte → Compiler-based framework for building efficient UIs

🛡 TypeScript → Typed superset of JavaScript for scalable applications

📄 Marked.js → Markdown parser and compiler

📑 Quill.js → Rich text editor

📂 FilePond → File upload library with previews and editing

🌍 Leaflet.js → Interactive maps

📹 Video.js → HTML5 video player framework

🎧 Howler.js → Audio library for the web

📨 Axios → Promise-based HTTP client

🔄 RxJS → Reactive programming with observables

📜 Prism.js → Syntax highlighting for code blocks

📊 Chartist.js → Simple responsive charts

🖌 Fabric.js → Canvas library for interactive graphics

📐 MathJax → Displaying mathematical notation in browsers

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🛠 Rollup → Module bundler for JavaScript libraries

📄 Puppeteer → Headless browser automation

📊 Plotly.js → Advanced data visualization and charting

📄 PDF.js → PDF viewer and parser in the browser

📦 Vite → Next-generation frontend tooling

📄 Swiper.js → Modern touch slider and carousel

📄 Hammer.js → Gesture recognition for touch interactions

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📄 Tippy.js → Tooltip and popover library

Data Analysis ማለት በ አጭሩ ከ ብዙ መረጃዎች ውስጥ ጠቃሚ ግንዛቤን ማግኜት ማለት ነው።

ይህ ፊልድ በተለይ በዚህኛው ዘመን አስፈላጊነቱ ከፍ ያለ ነው። ምክንያቱም በየቀኑ የምናመነጨው የዳታ መጠን ከምንጊዜውም በላይ እየጨመረ ነው። ይህን እጅግ ብዙ መረጃ ለመረዳትና ከዚሁ ሁሉ ውስጥ ጠቃሚ መረጃወቺን ለማውጣት የ ዳታ አናላይሲስ ወሳኝ ነው።

ከ ሌሎች ዲሲፕሊኖች ለየት የሚያደርገው ደግሞ ይህ ነገር በሁሉም መረጃ ባለበት ሁሉ አስፈላጊ መሆኑ ነው። ለምሳሌ ፡ -

- ንግድ ላይ ላለ ሰው የ ደንበኞችን ባህሪ ፤ የ ገበያ አዝማሚያዎችን እና አጠቃላይ የ ንግድ አፈፃፀምን ለመረዳትና የተሻሉ እና ትክክለኛ ውሳኔዎችን ለማድረግ የ ዳታ ትንተና (analysis) ይጠቀማል።

- በተለያዩ የህክምና ምረምሮች ላይ በሺታዎችን ለመረዳት ፤ አዳዲስ ህክምናዎችን ግኜቶችን ለማዘጋጀት እና ውስብስብ ችግሮን ለመፍታት የ ዳታ ትንተና ያስፈልጋቸዋል።

- በ ማህበራዊ ጉዳዮች ላይ እንደ ድህነት ፤ ወንጀል ፤የ አየር ንብረት እና መሰል ለውጦችን ለመረዳት እና ለመፍታት የ ዳታ ትንተና አስፈልጊ ነው።

እነዚህን እና መሰል ነገሮች ተንትኖ ጠቃሚ እይታና ውሳኔ እንዲኖረን በማድረግ የዳታ ትንተና ( Data Analytics ) ወሳኝ ሚና አለው።

የ ዳታ ትንተና ይሄን ያህል አስፈላጊ ከሆነ መሰረታዊ ነገሮቹ እነዚህ ናቸው።
1. መረጃን መሰብሰብ (Data Collection)
2. መረጃ ማፅዳት ( Data Cleaning )
3. መረጃን ማደራጀት ( Data Organization )
4. መረጃን መተንተን (Data Analyzing )
5. መረጃን መተርጎም ( Data Visualizing )
6. Data Presenting.

....ይቀጥላል...

#Data_Analytics

Data Analytics Process

የዳታ ትንተና (Data Analytics ) መሰረታዊ ሂደተቶች እነዚህ ናቸው፡-

1. መረጃ መሰብሰብ( Data Collection ) : ይህ ትንተና የሚካሄድበትን መረጃ ከተለያዩ ምንጮች መሰብሰብ ሲሆን የመጀመሪይዋ ፕሮሰስ ነው። የዳታ ምንጮች የሚባሉት ለምሳሌ የዳሰሳ ጥናቶች፣ የደንበኞች ግብረመልስ፣ የሽያጭ መረጃዎች፣ ወዘተ... ሊሆኑ ይችላሉ።

2. መረጃ ማጽዳት(Data Cleaning) : መረጃው ከተሰበሰበ በኋላ ለትክክለኛ ትንተና ማጽዳት አስፈላጊ ነው። ይህ ማለት የተሳሳቱ ወይም ያልተሟሉ መረጃዎችን ማስወገድ ወይም መሙላት ማለት ነው አሊያኢም ደግሞ ወጥነት የሌላቸውን ቅርጸቶች ማስተካከል ማለት ነው።

3. መረጃ ማደራጀት (Data Organizing) : መረጃው ከተጸዳ በኋላ, ለመተንተን ቀላል እንዲሆን ማደራጀት አስፈላጊ ነው.። ይህ ማለት መረጃውን ለንባብ እና ለመረዳት ምቹ እንዲሆኑ በሠንጠረዦች ወይም በሌሎች ቅርጸቶች ማዘጋጀት ማለት ነው።

4. መረጃ መተንተን( Data Analyzing ) : ይህ ዋናው ስራ ነው። መረጃው ከተደራጀ በኋላ ወደ ትንተናው ይገባል። ትንተና ስንል ከላይ እንዳልነው ንድፎችን ፤ አዝማሚያዎችን እና ግንኙነቶችን ለመለየት መረጃውን በ ጥልቀት መመርመር ማለት ነው።

5. ውጤቶችን መተርጎም( Data Visualizing and Presenting ) : የትንተናው ውጤቶች ከተገኙ በኋላ, ምን ማለት እንደሆነ መተርጎም አስፈላጊ ነው። ይህ ማለት ውጤቶቹን በመጠቀም ስለ መረጃው ግንዛቤዎችን ማግኘት እና መደምደሚያ ላይ መድረስ ማለት ነው። ከዚያም ለ ሚመለከተው አካል መስጠት ወይም ውሳኔ መወሰንን ያጠቃልላል።


#Data_Analytics

All human language is higher order programming language.