Introduction to Analytics - D491
Questions and Answers Latest Version
100% Pass
What is the main objective of analytics?
✔✔a) To transform data into actionable insights
b) To store large datasets
c) To clean and preprocess data
d) To create complex data models
What does "data visualization" help with?
a) Storing data
✔✔b) Presenting data in a graphical format for easier understanding
c) Cleaning raw data
d) Predicting future outcomes
What is the first step in the analytics process?
✔✔a) Define the problem or goal
b) Analyze the data
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,c) Collect data
d) Visualize the data
What is an example of unstructured data?
a) Data in a relational database
✔✔b) Text data from social media posts
c) Data in a CSV file
d) Data in an Excel spreadsheet
Which of the following best describes descriptive analytics?
a) Predicting future trends based on historical data
✔✔b) Summarizing and analyzing past data to gain insights
c) Visualizing relationships between variables
d) Making decisions based on large datasets
What is predictive analytics used for?
a) Summarizing historical data
✔✔b) Forecasting future outcomes based on past data
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,c) Cleaning and preprocessing data
d) Identifying patterns in unstructured data
Which of the following is a key component of a data dashboard?
a) Machine learning algorithms
✔✔b) Key performance indicators and visualizations for quick insights
c) Data cleaning techniques
d) Data storage solutions
What is an example of structured data?
✔✔a) Data in a relational database with rows and columns
b) A series of tweets
c) Audio recordings
d) Customer feedback in text format
What does the term "data wrangling" refer to?
a) Storing data in a cloud system
✔✔b) The process of cleaning and transforming raw data into a usable format
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, c) Visualizing data
d) Creating data models
What does the "correlation coefficient" measure in data analysis?
a) The mean of the data
b) The size of the data
✔✔c) The strength and direction of the relationship between two variables
d) The distribution of the data
What is a key challenge when working with big data?
a) Storing the data on a single device
✔✔b) Managing the volume, variety, and velocity of data
c) Analyzing small datasets
d) Cleaning the data
What is a common method for handling missing data in analytics?
a) Ignoring the missing data
✔✔b) Filling in missing values or removing the rows with missing values
4
Questions and Answers Latest Version
100% Pass
What is the main objective of analytics?
✔✔a) To transform data into actionable insights
b) To store large datasets
c) To clean and preprocess data
d) To create complex data models
What does "data visualization" help with?
a) Storing data
✔✔b) Presenting data in a graphical format for easier understanding
c) Cleaning raw data
d) Predicting future outcomes
What is the first step in the analytics process?
✔✔a) Define the problem or goal
b) Analyze the data
1
,c) Collect data
d) Visualize the data
What is an example of unstructured data?
a) Data in a relational database
✔✔b) Text data from social media posts
c) Data in a CSV file
d) Data in an Excel spreadsheet
Which of the following best describes descriptive analytics?
a) Predicting future trends based on historical data
✔✔b) Summarizing and analyzing past data to gain insights
c) Visualizing relationships between variables
d) Making decisions based on large datasets
What is predictive analytics used for?
a) Summarizing historical data
✔✔b) Forecasting future outcomes based on past data
2
,c) Cleaning and preprocessing data
d) Identifying patterns in unstructured data
Which of the following is a key component of a data dashboard?
a) Machine learning algorithms
✔✔b) Key performance indicators and visualizations for quick insights
c) Data cleaning techniques
d) Data storage solutions
What is an example of structured data?
✔✔a) Data in a relational database with rows and columns
b) A series of tweets
c) Audio recordings
d) Customer feedback in text format
What does the term "data wrangling" refer to?
a) Storing data in a cloud system
✔✔b) The process of cleaning and transforming raw data into a usable format
3
, c) Visualizing data
d) Creating data models
What does the "correlation coefficient" measure in data analysis?
a) The mean of the data
b) The size of the data
✔✔c) The strength and direction of the relationship between two variables
d) The distribution of the data
What is a key challenge when working with big data?
a) Storing the data on a single device
✔✔b) Managing the volume, variety, and velocity of data
c) Analyzing small datasets
d) Cleaning the data
What is a common method for handling missing data in analytics?
a) Ignoring the missing data
✔✔b) Filling in missing values or removing the rows with missing values
4
