Data compression techniques in SCADA systems - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is data compression?

Data compression is the process of making data use less space by encoding it in a smaller form. It helps save storage and speeds up data transfer.

beginner

Name two main types of data compression.

The two main types are lossless compression, which keeps all original data, and lossy compression, which removes some data to save more space.

intermediate

Why is lossless compression important in SCADA systems?

Lossless compression is important because SCADA systems need exact data for control and monitoring. No data can be lost or changed.

beginner

Give an example of a lossless compression algorithm.

An example is ZIP compression, which reduces file size without losing any data.

intermediate

What is a trade-off when using lossy compression?

The trade-off is that you get smaller files but lose some data quality, which might not be acceptable for critical systems.

Which type of compression keeps all original data intact?

A Lossy compression

B Lossless compression

C Partial compression

D Encrypted compression

Lossless compression keeps all original data without any loss.

Why is lossy compression usually not used in SCADA systems?

A It loses some data which can affect system accuracy

B It is too slow

C It requires special hardware

D It increases file size

Lossy compression loses some data, which can cause errors in SCADA systems that need exact data.

Which of these is a common lossless compression format?

A JPEG

B MP3

C ZIP

D MPEG

ZIP is a common lossless compression format.

What is the main benefit of data compression?

A Makes data harder to read

B Uses more storage space

C Increases data size

D Saves storage and speeds up transfer

Data compression saves storage space and speeds up data transfer.

Which compression type is best when exact data recovery is needed?

A Lossless

B Lossy

C Hybrid

D None

Lossless compression allows exact data recovery.

Explain the difference between lossless and lossy data compression.

Think about whether data can be perfectly restored or not.

Why is lossless compression preferred in SCADA systems?

Consider the importance of data accuracy in control systems.

Practice

1. What is the main purpose of data compression in SCADA systems?

easy

A. To reduce the size of data for easier storage and faster transfer

B. To increase the size of data for better security

C. To convert data into a different format for display

D. To delete unnecessary data permanently

Solution

1. Step 1: Understand data compression purpose

   Data compression reduces the size of data to save space and speed up transfer.

2. Step 2: Apply this to SCADA systems

   In SCADA, smaller data means faster communication and less storage needed.

3. Final Answer:

   To reduce the size of data for easier storage and faster transfer -> Option A

4. Quick Check:

   Compression = smaller data size [OK]

Hint: Compression makes data smaller to save space and time [OK]

Common Mistakes:

• Confusing compression with encryption
• Thinking compression deletes data
• Believing compression changes data meaning

2. Which of the following is the correct syntax to compress data using a function named compress in a SCADA script?

easy

A. compressed_data = compress(data)

B. compressed_data = compress data

C. compressed_data <- compress(data)

D. compressed_data = compress[data]

Solution

1. Step 1: Identify correct function call syntax

   Functions are called with parentheses enclosing arguments, like compress(data).

2. Step 2: Check each option

   compressed_data = compress(data) uses correct syntax with parentheses and assignment.

3. Final Answer:

   compressed_data = compress(data) -> Option A

4. Quick Check:

   Function call syntax = parentheses [OK]

Hint: Use parentheses to call functions with arguments [OK]

Common Mistakes:

• Omitting parentheses in function calls
• Using wrong assignment operators
• Using brackets instead of parentheses

3. Given the following SCADA script snippet:

data = "sensor_reading_12345"
compressed = compress(data)
decompressed = decompress(compressed)
print(decompressed)

What will be the output?

medium

A. compressed data bytes

B. Error: decompress function not found

C. sensor_reading_12345

D. sensor_reading

Solution

1. Step 1: Understand compression and decompression

   compress() shrinks data, decompress() restores it to original form.

2. Step 2: Follow the script flow

   Data is compressed then decompressed, so print shows original data.

3. Final Answer:

   sensor_reading_12345 -> Option C

4. Quick Check:

   Decompress(compress(data)) = original data [OK]

Hint: Decompress reverses compress, output original data [OK]

Common Mistakes:

• Thinking print shows compressed bytes
• Assuming decompress changes data
• Ignoring function order

4. A SCADA script uses compressed = compress(data) but later decompressed = decompress(data) is called instead of decompress(compressed). What is the likely problem?

medium

A. Data will be compressed twice

B. Compression will fail because decompress is called too early

C. No problem, decompress can use original data

D. Decompression will fail or give wrong data because wrong variable is used

Solution

1. Step 1: Identify variable usage error

   Decompress must use compressed data, not original data variable.

2. Step 2: Understand effect of wrong variable

   Using original data in decompress causes failure or incorrect output.

3. Final Answer:

   Decompression will fail or give wrong data because wrong variable is used -> Option D

4. Quick Check:

   Decompress(compressed) needed, not decompress(data) [OK]

Hint: Always decompress the compressed variable [OK]

Common Mistakes:

• Passing original data to decompress
• Assuming decompress auto-detects input
• Mixing variable names

5. You need to compress SCADA data but want to keep it quickly accessible for real-time monitoring. Which compression technique is best?

hard

A. No compression to avoid delay

B. Lossless compression for exact data recovery

C. Lossy compression to reduce size drastically

D. Encrypt data instead of compressing

Solution

1. Step 1: Understand real-time monitoring needs

   Real-time needs exact data quickly without loss.

2. Step 2: Choose compression type

   Lossless compression keeps data exact and fast to decompress.

3. Step 3: Evaluate other options

   Lossy loses data, no compression wastes space, encryption is different.

4. Final Answer:

   Lossless compression for exact data recovery -> Option B

5. Quick Check:

   Real-time + exact data = lossless compression [OK]

Hint: Use lossless compression for exact, fast data access [OK]

Common Mistakes:

• Choosing lossy compression for critical data
• Skipping compression to save time
• Confusing encryption with compression