Difference between revisions of "IS428 AY2019-20T1 Assign Sean Chai Shong Hee Q5"
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Analysing data as a static collection was particularly useful in this case as it was easier to gather insights based on patterns and trends. With a dynamic stream of data, data is continuous being added to your visualisation, which makes it difficult to determine relationships and patterns. | Analysing data as a static collection was particularly useful in this case as it was easier to gather insights based on patterns and trends. With a dynamic stream of data, data is continuous being added to your visualisation, which makes it difficult to determine relationships and patterns. | ||
− | [[File: | + | [[File:Mobile & Static.png|500px|thumb|center]] |
I was able to see with certainty how radiation values varied over the 4 days, and most observations made required looking at how one factor affected another. | I was able to see with certainty how radiation values varied over the 4 days, and most observations made required looking at how one factor affected another. | ||
− | [[File:Visualising path.png| | + | [[File:Visualising path.png|500px|thumb|center]] |
Using a dynamic stream of data was useful when I wanted to determine the path of travel of contaminated cars over time. I could visualise by changing the time slider the exact path of the contaminated car. | Using a dynamic stream of data was useful when I wanted to determine the path of travel of contaminated cars over time. I could visualise by changing the time slider the exact path of the contaminated car. | ||
+ | [[File:Missing Values Mobile.png|500px|thumb|center]] | ||
Ultimately, analysing data as a static collection allowed me to have a clearer picture of gaps in data (such as visualising the many missing values in the data for mobile sensors). I was able to relate outcomes of radiation leakage to their causes when analysing the data as a static collection. | Ultimately, analysing data as a static collection allowed me to have a clearer picture of gaps in data (such as visualising the many missing values in the data for mobile sensors). I was able to relate outcomes of radiation leakage to their causes when analysing the data as a static collection. |
Latest revision as of 19:46, 13 October 2019
This section will answer questions for Mini Case 2
Question 5
Data Analysis
For Mini Case 2, I analysed the data mainly as a static collection.
Analysing data as a static collection was particularly useful in this case as it was easier to gather insights based on patterns and trends. With a dynamic stream of data, data is continuous being added to your visualisation, which makes it difficult to determine relationships and patterns.
I was able to see with certainty how radiation values varied over the 4 days, and most observations made required looking at how one factor affected another.
Using a dynamic stream of data was useful when I wanted to determine the path of travel of contaminated cars over time. I could visualise by changing the time slider the exact path of the contaminated car.
Ultimately, analysing data as a static collection allowed me to have a clearer picture of gaps in data (such as visualising the many missing values in the data for mobile sensors). I was able to relate outcomes of radiation leakage to their causes when analysing the data as a static collection.