Big Data Analytics - Data Quality

Quiz
•
Professional Development, Computers
•
University - Professional Development
•
Medium
Malarvizhi K C
Used 16+ times
FREE Resource
6 questions
Show all answers
1.
MULTIPLE CHOICE QUESTION
20 sec • 2 pts
What is 'data about data'?
Metadata
Pseudodata
Personal data
2.
MULTIPLE CHOICE QUESTION
30 sec • 3 pts
Consider that you have a dataset. If you want to understand whether the data is timely, which of the following questions would you consider?
Are there missing values?
Is the data consistent?
When was the dataset updated?
Are there replicated values?
3.
MULTIPLE SELECT QUESTION
45 sec • 5 pts
Take a look at the sample dataset. There are three different colours: Red, Yellow and Black. The weight value needs to be above 20. What are the obvious issues with Data quality? Select all that apply.
The data is not consistent with the Properties table.
Some of the weight values are not within the range.
The dataset is not timely.
Some of the color and weight values are missing.
4.
MULTIPLE CHOICE QUESTION
30 sec • 3 pts
Ben is provided with Low quality metadata about glass manufacturing. He is not an expert in this area. What are the possible issues with data quality?
There is no issue with data quality.
There is a high risk of misuse of data.
There is need to improve the metadata quality based on Ben's understanding
There is low risk of misuse of data.
Answer explanation
The possible issues with data quality in this case are related to the high risk of misuse of data. Since Ben is not an expert in glass manufacturing and the metadata provided is of low quality, it becomes difficult for him to accurately interpret and utilize the information, leading to potential errors and misinterpretations.
5.
MULTIPLE CHOICE QUESTION
20 sec • 3 pts
Making sure that right people have access to the right data by restricting access to specific records of data is known as _____
Sharding
Fine-grained access control
Personal data
Anonymisation
6.
MULTIPLE CHOICE QUESTION
1 min • 5 pts
Ben and Amy are working on a project that uses data from sensor A. Ben's dataset is the top one and Amy's dataset is the bottom one. Today is the 1st of November and both Ben and Amy present their project results. The manager rejects Ben's results. What could be the reason?
Ben's dataset has some issues regarding consistency.
Ben's dataset is not timely.
Ben's dataset is missing values.
Ben's manager did not check his results properly.
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