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Without databases, none of these services would work reliably. Information would
get lost, mixed up or be impossible to find. Databases bring order to the enormous
amounts of data that modern life depends on.
21 st
Century #Technology Literacy
ai in action Skills
In the game AI Data Sorting Game learn how data is sorted and categorised. Make predictions
on how to sort items and how AI makes decisions based on patterns.
Visit the given link or scan the QR code to access the application:
https://studio.code.org/courses/k5-ai-data-2024/units/1/lessons/1/levels/1
YOUR CHOICE - GOOD DATA AND BAD DATA
Now that you know where data comes from and how it is stored, it’s time to ask a
very important question: Is all data equally useful? The answer is no. Data can be
good or bad and the difference matters a lot, especially when AI systems use that
data to make decisions.
What Makes Data Good?
Good data is data that we can trust. It helps us make decisions or learn more about
something. For data to be good, it must have a few important qualities:
Accurate: The data must show the truth. It should be correct and not
contain any errors.
Complete: No important information should be missing. All details are
needed for a full picture.
Consistent: The same kind of information must always be recorded in
the same way. This makes it easier to understand and compare.
Relevant: The data must be connected to the question or problem being
studied. If it doesn’t help answer the question, it’s not useful.
Imagine a school nurse who wants to study the sleeping habits of students in Classes
4 and 5. She asks 200 students to honestly record how many hours they sleep each
night for one week. If all the students fill in the form carefully and truthfully, the nurse
will have good data.
What Makes Data Bad?
Bad data is inaccurate, incomplete or unfair. It can enter a system in many ways.
Sometimes a sensor gives wrong readings, people make mistakes when filling in
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