Introduction to Data Science Code 419 Class 9 Notes: The subject Introduction to Data Science (Code 419) is a Skill Education course offered by CBSE for Class 9. It introduces students to the world of data, its importance in decision-making, and real-life applications in technology, business, and daily life.
Introduction to Data Science Code 419 Class 9 Notes
What is data?
Whatever we can read, write, speak, and observe is data. Data refers to raw facts or figures. It can be numbers, alphabets, symbols, or a combination of all of these. For example, temperature readings, student scores, survey answers, dates, etc.
Note: Data are used to tell a story. Statisticians see the world through patterns, variation and evidence. Statistical thinking and the statistical problem-solving process are foundational to exploring all data.
Data vs. Information
The words “data” and “information” are frequently used. Data can be a number, symbol, or text, which may not mean anything to individuals on its own. However, when data are processed and put in context, they bear a meaning. This means data can be used for decision-making, calculations, or discussions. The data then becomes information. For example, suppose you have temperature reading data; it doesn’t mean anything, but when you organise and analyse it, it becomes information from the data.
Data, Information, Knowledge, Wisdom (DIKW model)
The DIKW model is used for transforming the data to information. It is also known as the data pyramid or DIKW pyramid. It is a four-step method which is known as the DIKW model, which explains how we move from data to information to knowledge to wisdom. In the DIKW model, where “D” means data, “I” means information, “K” means knowledge, and “W” means wisdom.
How does data influence our lives?
Data is everything, like shopping online, watching shows or ordering food. News and media also give us data on sports, health, education, the economy and public opinion. Data helps to make better decisions and be responsible citizens.
Data also enables business leaders to make decisions based on historical data. They analyse budgets, market demands, sales forecasts, etc., which helps them make informed choices. Below are a few of the essential aspects of our lives that are impacted by data:
- Healthcare: Data plays an important role in improving health and saving lives. It helps to:
- Tracking Medical History
- Predicting Disease and Epidemics
- Managing Treatments and Finding Cures
- Personal Health Devices
- Online shopping: Online sellers analyse customers’ historical purchases, searches, etc., to come up with targeted marketing. It also helps to compare shopping patterns and make recommendations.
- Education: Most of the college and school admission processes are now digitised. Also, students explore various career options by analysing historical records of universities and educational institutes.
- Travel: Several popular travel apps predict traffic congestion and help us plan our travel. Also, we analyse feedback from different travellers on hotels and resorts.
- Online shows: Streaming platforms like Netflix, Prime Video, etc. use data analysis to improve your viewing experience using personalised recommendations, understanding viewer preference, predicting popular shows and ratings and feedback.
What are data footprints?
The internet has become an essential part of life. Whatever activity we are doing on the internet, like watching videos, shopping, or chatting, creates trails of data. These trails of data are called data footprints. Data footprint includes:
- The websites you visit
- The emails you send or receive
- The messages you exchange while chatting
- Any clicks, searches, or actions you take online
Data footprints can be classified into two categories.
- Active: In an inactive footprint, when We regularly use several social media platforms and post images or content which are stored on the media. This is a form of active data footprint, as we have knowingly shared information about ourselves.
- Passive: In a passive footprint, browsing history and product searches may be stored by search engines. Organisations use these records for personalized marketing. This is an example of a passive data footprint.
Data loss and recovery
Data can be lost, corrupted, damaged, or deleted due to multiple reasons, like transaction failure, system crash, or disc failure. The process of restoring inaccessible, lost, corrupted, damaged, or deleted data is called data recovery. To prevent this, we should frequently back up our data. Large enterprise systems generally use backup data storage from where they recover the data in case of any loss.
Disclaimer: We have taken an effort to provide you with the accurate handout of “Introduction to Data Science Code 419 Class 9 Notes“. If you feel that there is any error or mistake, please contact me at anuraganand2017@gmail.com. The above CBSE study material present on our websites is for education purpose, not our copyrights.
All the above content and Screenshot are taken from Data Science Class 9 Microsoft Textbook published on CBSE Website, CBSE Sample Paper, CBSE Old Sample Paper, CBSE Board Paper and CBSE Support Material which is present in CBSEACADEMIC website This Textbook and Support Material are legally copyright by Central Board of Secondary Education. We are only providing a medium and helping the students to improve the performances in the examination.
Images and content shown above are the property of individual organisations and are used here for reference purposes only. To make it easy to understand, some of the content and images are generated by AI and cross-checked by the teachers. For more information, refer to the official CBSE textbooks available at cbseacademic.nic.in.