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SCADA systemsdevops~30 mins

Trend analysis and reporting in SCADA systems - Mini Project: Build & Apply

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Trend analysis and reporting
📖 Scenario: You work with a SCADA system that collects temperature readings from multiple sensors every hour. Your task is to analyze the temperature trends and generate a simple report showing average temperatures per sensor.
🎯 Goal: Build a small program that stores hourly temperature data for sensors, configures a threshold for reporting, calculates average temperatures per sensor, and prints a summary report.
📋 What You'll Learn
Create a dictionary with sensor names as keys and lists of hourly temperature readings as values
Add a threshold variable to filter sensors with average temperature above this value
Calculate the average temperature per sensor using a loop
Print a report listing sensors with average temperature above the threshold
💡 Why This Matters
🌍 Real World
SCADA systems monitor industrial sensors and analyze trends to detect anomalies or optimize processes.
💼 Career
DevOps engineers often automate data collection and reporting pipelines for monitoring system health and performance.
Progress0 / 4 steps
1
Create sensor temperature data
Create a dictionary called sensor_data with these exact entries: 'SensorA': [22.5, 23.0, 22.8], 'SensorB': [19.0, 18.5, 19.2], 'SensorC': [25.1, 24.8, 25.3]
SCADA systems
Hint

Use a dictionary with sensor names as keys and lists of floats as values.

2
Add temperature threshold
Create a variable called threshold and set it to 22.0 to filter sensors with average temperature above this value
SCADA systems
Hint

Just assign the number 22.0 to a variable named threshold.

3
Calculate average temperatures
Create a new dictionary called average_temps that stores the average temperature for each sensor using a for loop with variables sensor and temps iterating over sensor_data.items()
SCADA systems
Hint

Use a for loop to calculate the average by summing the list and dividing by its length.

4
Print sensors above threshold
Use a for loop with variables sensor and avg iterating over average_temps.items() to print lines like SensorA: 22.77 only if avg is greater than threshold. Use print(f"{sensor}: {avg:.2f}") to format the output.
SCADA systems
Hint

Loop over average_temps and print only if average is above threshold using formatted string.

Practice

(1/5)
1. What is the main purpose of trend analysis in SCADA systems?
easy
A. To configure hardware devices
B. To track changes in data over time
C. To write code for automation
D. To backup system files

Solution

  1. Step 1: Understand trend analysis concept

    Trend analysis means observing how data changes over a period.
  2. Step 2: Match purpose with options

    Only tracking data changes over time fits the definition of trend analysis.
  3. Final Answer:

    To track changes in data over time -> Option B
  4. Quick Check:

    Trend analysis = track data changes [OK]
Hint: Trend analysis = watching data over time [OK]
Common Mistakes:
  • Confusing trend analysis with system backup
  • Thinking it configures devices
  • Mixing it with coding tasks
2. Which of the following is the correct command to generate a trend report in a SCADA system CLI?
easy
A. generate_trend_report --start 2024-01-01 --end 2024-01-31
B. trend report create start=2024-01-01 end=2024-01-31
C. create report trend from 2024-01-01 to 2024-01-31
D. report --trend --from 2024-01-01 --to 2024-01-31

Solution

  1. Step 1: Identify correct command syntax

    SCADA CLI commands usually follow verb_action --option value format.
  2. Step 2: Compare options

    generate_trend_report --start 2024-01-01 --end 2024-01-31 matches the expected syntax with clear flags and dates.
  3. Final Answer:

    generate_trend_report --start 2024-01-01 --end 2024-01-31 -> Option A
  4. Quick Check:

    Correct CLI syntax = generate_trend_report --start 2024-01-01 --end 2024-01-31 [OK]
Hint: Look for commands with clear flags and date ranges [OK]
Common Mistakes:
  • Using incorrect command order
  • Missing dashes before options
  • Using natural language instead of CLI syntax
3. Given this snippet of a SCADA trend report script:
data = [10, 15, 20, 25, 30]
trend = []
for i in range(1, len(data)):
    trend.append(data[i] - data[i-1])
print(trend)

What is the output?
medium
A. [10, 5, 5, 5]
B. [10, 15, 20, 25, 30]
C. [5, 10, 15, 20]
D. [5, 5, 5, 5]

Solution

  1. Step 1: Calculate differences between consecutive data points

    Subtract each previous value from current: 15-10=5, 20-15=5, 25-20=5, 30-25=5.
  2. Step 2: Collect results in trend list and print

    The trend list is [5, 5, 5, 5], which is printed.
  3. Final Answer:

    [5, 5, 5, 5] -> Option D
  4. Quick Check:

    Differences between data points = [5,5,5,5] [OK]
Hint: Subtract previous from current values to find trend [OK]
Common Mistakes:
  • Printing original data instead of differences
  • Off-by-one errors in loop range
  • Appending wrong values to trend list
4. You run this SCADA report command but get an error:
generate_trend_report --start 2024-02-30 --end 2024-03-01

What is the likely cause?
medium
A. End date is before start date
B. Missing required --format option
C. Invalid date: February 30 does not exist
D. Command syntax is incorrect

Solution

  1. Step 1: Check date validity

    February has at most 29 days; 30 is invalid.
  2. Step 2: Confirm error cause

    Invalid date causes command to fail before other checks.
  3. Final Answer:

    Invalid date: February 30 does not exist -> Option C
  4. Quick Check:

    Invalid date causes error [OK]
Hint: Verify dates exist on calendar before running commands [OK]
Common Mistakes:
  • Assuming syntax error without checking dates
  • Ignoring invalid date and blaming options
  • Confusing start and end date order
5. You want to create a report showing average temperature trends per day from hourly SCADA data. Which approach is best?
hard
A. Aggregate hourly data by day, then calculate daily averages and plot trend
B. Plot hourly data directly without aggregation
C. Calculate weekly averages ignoring daily details
D. Use raw data without any calculations for reporting

Solution

  1. Step 1: Understand goal of daily average trends

    We need daily summaries from hourly data to see daily trends clearly.
  2. Step 2: Choose method to aggregate and analyze data

    Aggregating hourly data by day and calculating averages fits the goal best.
  3. Final Answer:

    Aggregate hourly data by day, then calculate daily averages and plot trend -> Option A
  4. Quick Check:

    Daily average trend needs daily aggregation [OK]
Hint: Group data by day before averaging for daily trends [OK]
Common Mistakes:
  • Using raw hourly data without aggregation
  • Skipping daily grouping and using weekly averages
  • Ignoring calculations and plotting raw data