شرح ICT الصف الثاني الاعدادي لغات - الفصل الدراسي الثاني
شرح ICT تانية اعدادي - ترم تاني

لينك تحميل الملزمة
https://drive.google.com/file/d/1A473d0EimSe1o0eOXFKe9k6-nYDIGJTW/view?usp=sharing

لينك تليجرام
https://t.me/mrahmedelbashagroup

in this lesson:
The concept of big data:
A collection of large, complex data that cannot be efficiently processed using traditional technology (such as Excel) to make meaningful use of it. Analyzing big data allows analysts, researchers, and entrepreneurs to make better, faster decisions.

Sources of big data:
Internet-connected devices (IoT):
Internet-connected devices such as smart refrigerators, smart watches, or connected cars continuously generate data by collecting information about their location, temperature, behavioral patterns, and energy usage.
Example: A smart watch measures heart rate, physical activity level, and temperature and collects this data to send it to the relevant application.

Social Media:
Social media generates data from users' daily activities, such as posts, comments, photos, videos, and likes (and these sources may be unreliable).
Example: when someone posts a photo on Instagram or shares an opinion on Facebook, data is generated about the time, location, reactions, and hashtags.

Financial Data:
Electronic payments, banking transactions, and stock trading contribute to the generation of massive amounts of data by collecting information about amounts paid, users, locations, and times.
Example: when someone makes an online purchase using a credit card, data is recorded about the amount, store, and geographic location.

Data from Smart Devices:
Devices such as mobile phones, cameras, and smart home devices generate data about usage, location, and interactions.
Example: A mobile phone constantly tracks your geographic location and collects data about the places you've visited and the apps you've used.

Digital Content:
Videos, images, and audio content uploaded or viewed online generate big data such as the number of views, interactions, comments, and shares.
Example: When someone watches a YouTube video, data is collected about the viewing time, video interactions, and comments.

Government Data:
Governments generate data through population registers, statistics, tax data, and censuses.
Example: Data about the population of a particular area or information about income and expenditures is collected through government surveys.

Geographic and Spatial Data:
Satellites and GPS devices collect data about geographic locations, roads, and the environment.
Example: a mapping application like Google Maps collects data about traffic, vehicle speed, and congested roads to improve routing.

 
The 5Vs of Big Data
1- Volume
Refers to the massive amount of data collected and stored. As technology advances, we have greater capacity to collect data from multiple sources such as smart devices, social media, and others.

2- Velocity
Refers to the speed at which data is generated and processed. In the internet age, data is generated very quickly, such as electronic payments, social media updates, and data streams from connected devices.

3- Variety
Refers to the variety of data types collected. This includes structured data (such as databases) and unstructured data (such as text, images, and videos).

4- Veracity
Refers to the reliability and quality of the data. Sometimes, data may be inaccurate or contain errors, making it difficult to extract accurate information from it.

5- Value
Refers to the usefulness that can be derived from the data. It is essential to extract and analyze data in a way that delivers actual value to the organization or individual.

 
Types of Big Data
1- Structured Data:
Data that is organized and arranged in tables with rows and columns, similar to traditional databases.
Examples: Customer data, financial data, transaction records.

2- Unstructured Data
This is data that does not come in a structured form, such as tables or databases. This type of data is difficult to analyze using traditional tools.
Sources: Text, images, videos, and social media posts.
Example: A Facebook post containing text, images, and videos.

3- Semi-Structured Data
Semi-structured data is a hybrid of structured and unstructured data.
Emails are a good example because they include unstructured data in the message body, as well as additional structural features such as sender, recipient, subject, and date.

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