Скачать или смотреть 🔥 ✨Data Science inEmerging Part 2# Structured, Semi-Structured & Unstructured Data

Welcome to Part 2 of our deep dive into the fascinating world of Emerging Technology (እየወጡ ያሉ ቴክኖሎጂዎች - IyeWet’u Yalu Teknolojiwoch), focusing on Data Science (ዳታ ሳይንስ - Data Science)!
In this essential lesson, we're unlocking the secrets behind the different Data Types that power modern applications. Data isn't just one thing—it comes in many forms, and understanding these forms is the first step to becoming a successful Data Scientist.

We break down the core differences between:

Structured Data (የተዋቀረ ዳታ - Yetewaqere Data): Think of spreadsheets and databases—neat, organized, and easily searchable.

Semi-Structured Data (ከፊል-የተዋቀረ ዳታ - Kefil-Yetewaqere Data): Data that has some organizational tags, like JSON or XML files, but isn't strictly confined to a table.

Unstructured Data (ያልተዋቀረ ዳታ - Yaltewaqere Data): The vast majority of the world's data! This includes text documents, videos, social media posts, and more. We'll explore how modern technologies handle this complex type of data.

But a Data Scientist's job is more than just categorizing. It’s about managing data throughout its entire existence. That’s why we also cover the Data Structure Life Cycle. We detail the critical stages:

Creation/Acquisition: How is data born or collected?

Processing: Cleaning, transforming, and preparing data for analysis.

Storage: Where and how do we keep all this valuable information?

Analysis: Turning raw data into actionable insights and knowledge.

Disposition/Deletion: When and how should data be securely removed?

We use clear, simple examples to make these complex concepts accessible to everyone, from students taking the Emerging Technology course to professionals looking to upskill. Don't miss this crucial second part!

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🤯 ሶስቱ የዳታ አይነቶች (The 3 Data Types): Structured, Semi-Structured, and Unstructured Data—What are they and why do they matter for Big Data?

📊 የተዋቀረ ዳታ (Structured Data): How to work with neat, organized data found in traditional relational databases (e.g., SQL tables).

📑 ያልተዋቀረ ዳታ (Unstructured Data): Learn about the biggest challenge in Data Science: analyzing videos, audio, social media text, and emails!

🔄 የዳታ ሕይወት ዑደት (The Data Life Cycle): A step-by-step breakdown of how data moves from Creation to Deletion (Acquisition, Processing, Analysis, Storage).