p.18
Data Representation Techniques
What are examples of data objects in graph (network) data?
An online social network, the Internet, and the Web.
p.32
Python Programming for Data Analytics
What are Python functions used for?
To facilitate calculations.
p.20
Python Programming for Data Analytics
What type of programming language is Python?
A high-level, general-purpose programming language.
p.32
Python Programming for Data Analytics
What should you be aware of when using inputs in Python functions?
In some functions, you should use a collection of items, like a list, instead of separating inputs with commas.
p.2
Definition of Data Analytics
What is data analytics?
The science of analyzing raw data to make conclusions about that information.
p.2
Definition of Data Analytics
What are the key processes involved in data analytics?
Collecting, cleansing, transforming, modeling, and communicating data.
p.18
Data Representation Techniques
What is an example of a graph (network) data?
High school dating network.
p.13
Data Representation Techniques
What is an example of a data object in vector data?
A user’s ratings of products or course grades of a student.
p.11
Data Representation Techniques
Are Python data structures sufficient for data mining?
No, they are designed for data storage and processing but not sufficient for data mining.
p.5
Characteristics of Big Data
What are the three key characteristics of Big Data according to Doug Laney?
High volume, high velocity, and high variety.
p.16
Data Representation Techniques
What is 1D spatial data?
Just the name of the location.
p.32
Python Programming for Data Analytics
What does the function round(3.475, 2) do?
It rounds 3.475 to two decimal places.
p.21
Jupyter Notebook as an IDE
What is Jupyter Notebook?
A web-based interactive computational environment for creating notebook documents.
What is a string in programming?
A collection of characters.
p.11
Data Representation Techniques
What can you learn about data representation with Python?
How to collect, store, and process data using data structures and tools like arrays, lists, and data frames.
p.22
Jupyter Notebook as an IDE
What is Jupyter Notebook?
A web-based interactive development environment that supports various programming languages.
p.12
Data Representation Techniques
What are some forms of Data Representation?
Item Set, Vector/Matrix, Sequence, Time Series, Spatial/Spatiotemporal, Graph/Network, Stream.
p.32
Python Programming for Data Analytics
How are functions called in Python?
In the form of XXX(), where XXX is the name of the function.
How do you add comments to your code?
By adding '#' into the cell, making all input after it treated as comments.
p.22
Jupyter Notebook as an IDE
What integrated access does Jupyter Notebook provide?
Access to your operating system’s shell and file system.
p.8
Characteristics of Big Data
What does velocity refer to in the context of data?
The speed at which data is generated and the pace at which it moves from one point to the next.
p.2
Definition of Data Analytics
How have many techniques of data analytics evolved?
They have been automated into mechanical processes for human consumption.
p.3
Importance of Data Analytics
How does data analytics help in decision-making?
It allows you to make better predictions about the future and provides insights on factors affecting your industry.
p.25
Jupyter Notebook as an IDE
How can you organize the structure of your code in Jupyter Notebook?
By adding headings before the cells.
p.23
Python Programming for Data Analytics
How can you perform a simple calculation in Python?
By inputting code like 1+2 into the cell.
p.1
Data Analytics vs. Data Science
How does Data Analytics differ from Data Science?
Data Analytics focuses on interpreting existing data, while Data Science involves creating new data models and algorithms.
p.5
Characteristics of Big Data
What is the purpose of processing Big Data?
To enhance insight and decision making.
p.21
Jupyter Notebook as an IDE
What does IDE stand for?
Interactive Development Environment.
p.10
Characteristics of Big Data
Why does analysis become more complicated with heterogeneous data?
Due to the variety of data types and formats.
p.15
Definition of Data Analytics
What is an example of spatial data?
GPS trajectory of a vehicle.
p.12
Data Representation Techniques
What does Data Representation refer to?
The form in which data is stored, processed, and transmitted.
p.8
Characteristics of Big Data
How fast is data created, stored, and analyzed?
Velocity addresses the speed of these processes.
p.30
Boolean Logic in Data Analysis
What is the significance of Boolean values in data analytics?
They help determine the truth value of expressions.
p.1
Importance of Data Analytics
Why is Data Analytics important?
It helps organizations make informed decisions based on data-driven insights.
p.5
Characteristics of Big Data
What is the primary demand of Big Data?
Cost-effective, innovative forms of information processing.
p.25
Jupyter Notebook as an IDE
What should you do to set a heading in a Jupyter Notebook cell?
Add a heading like ‘# Section 1’ before the first cell and change the cell type to Markdown.
p.31
Boolean Logic in Data Analysis
What does the '&' operator do when combining conditional tests?
The output is True only if all conditions are met.
p.3
Importance of Data Analytics
In which industries will data analytics skills be important in the future?
Financial services, consumer goods, travel and transportation, and industrial products.
p.20
Python Programming for Data Analytics
What programming language did Python succeed?
The ABC programming language.
p.31
Boolean Logic in Data Analysis
What is the result of combining multiple conditions with '&'?
True only if all conditions are satisfied.
p.31
Boolean Logic in Data Analysis
What is the result of combining multiple conditions with '|'?
True if at least one condition is satisfied.
p.6
Data Representation Techniques
What type of services are provided by cloud-based platforms?
Storage and computing services.
p.17
Data Representation Techniques
How are locations indicated in spatial data on a web page?
By horizontal (X) and vertical (Y) positions.
p.1
Definition of Data Analytics
What is Data Analytics?
The process of examining data sets to draw conclusions about the information they contain.
p.12
Data Representation Techniques
Which forms of Data Representation will be focused on in this course?
Item Set, Vector/Matrix, Sequence, Time Series, Spatial/Spatiotemporal, Graph/Network, Stream.
p.15
Definition of Data Analytics
What additional element makes data spatiotemporal?
Inclusion of a given time point in the measurement.
p.22
Jupyter Notebook as an IDE
How does Jupyter Notebook differ from traditional programming workflows?
It encourages an execute-explore workflow instead of the typical edit-compile-run workflow.
p.3
Importance of Data Analytics
Why are the skills learned in data analytics considered a competitive necessity?
Because we live in an era of AI and big data, and these skills are essential across various industries.
What happens to the code after the '#' symbol?
It is treated as comments and will not be executed by the computer.
p.31
Boolean Logic in Data Analysis
What does the '|' operator do when combining conditional tests?
The output is True as long as one condition is met.
p.21
Jupyter Notebook as an IDE
How is Jupyter Notebook similar to a traditional notebook?
You can write sentences in it, just like using a pen in any notebook.
What does x[8] represent in a string?
The ninth character of the string.
p.4
Data Analytics vs. Data Science
What analogy is used to describe the work of a data scientist?
Chemistry is not about testing tubes, highlighting that data science is more than just data manipulation.
p.17
Data Representation Techniques
What is an example of spatial data related to user behavior on a web page?
Average time that users’ eyes are fixed at locations on a Web page.
p.30
Boolean Logic in Data Analysis
What happens when you compare two values in Python?
The expression is evaluated, and Python returns a Boolean answer.
p.8
Characteristics of Big Data
What is a quote related to data storage mentioned in the text?
“History can be too long to be stored.” - K. L. Chan
p.22
Jupyter Notebook as an IDE
What type of workflow does Jupyter Notebook encourage?
An execute-explore workflow.
p.23
Python Programming for Data Analytics
What is the primary design goal of Python?
To be an easily readable language.
p.11
Data Representation Techniques
What is the relationship between real data and analytics?
There is a big gap between real data and analytics.
p.13
Data Representation Techniques
Provide an example of attributes for products.
Kimono= 5; Shoe= 4; Piano= 3.
p.20
Python Programming for Data Analytics
What institution was Guido van Rossum associated with when he invented Python?
Centrum Wiskunde & Informatica (CWI) in the Netherlands.
p.21
Jupyter Notebook as an IDE
What programming languages can be used in Jupyter Notebook?
Languages like R, Python, C++, etc.
How can we access specific characters in a string?
By using indexing, such as x[0], x[4], x[5], x[8].
p.13
Data Representation Techniques
What is the significance of emojis in the context provided?
They are used as visual representations in data, such as on Twitter.
p.33
Group Project: Brand Perception Survey
What is the objective of the Brand Perception Survey?
To understand customers' perceptions, attitudes, and behaviors related to a particular brand through a questionnaire and provide recommendations based on data analysis.
p.27
Python Programming for Data Analytics
Are variable names in Python restricted to just one character?
No, you can use any words as the name.
p.19
Python Programming for Data Analytics
What is the primary focus of the 'Quick Start with Python' course?
To provide an introduction to Python programming.
What is a string in data analytics?
A collection of alphabets, words, or other characters.
How can you add explanations to results in Markdown?
By writing text without including the '#' at the beginning.
p.15
Definition of Data Analytics
What defines spatial data?
Measurement of a numerical property at a given location.
p.3
Importance of Data Analytics
What can data analytics inform decisions about?
Anything from new product development to hiring choices.
p.1
Characteristics of Big Data
What are some characteristics of Big Data?
Volume, velocity, variety, veracity, and value.
p.23
Python Programming for Data Analytics
How can you add more cells in a Python environment?
By clicking the ‘ + ’ button.
p.7
Characteristics of Big Data
What is the significance of volume in data analytics?
It refers to the vast amounts of data generated every second/minute/hour/day in our digitized world.
p.24
Python Programming for Data Analytics
What is the primary focus of the 'Quick Start with Python' course?
To introduce the basics of Python programming.
p.30
Boolean Logic in Data Analysis
What do Booleans represent in data analytics?
One of two values: True or False.
p.15
Definition of Data Analytics
What is an example of spatiotemporal data?
Spread of a disease with time measurements.
What is an example of adding an explanation in Markdown?
'1+2 equals 3!' can be added under the result 3.
p.13
Data Representation Techniques
What is an attribute in the context of vector data?
A numerical property of the object.
Give an example of a string.
K. L. Chan AEF HKBU Ifadd ∵.
p.11
Data Representation Techniques
What role does data representation play in data analytics?
Data representation bridges the gap between real data and analytics.
p.27
Python Programming for Data Analytics
What is the purpose of variables in data analysis?
To store values throughout the data analysis process.
What does x[0] represent in a string?
The first character of the string.
What does x[4] represent in a string?
The fifth character of the string.
p.27
Python Programming for Data Analytics
How can you recall the value of a variable in Python?
By simply typing the variable name in the script.
p.4
Data Analytics vs. Data Science
What is data analytics?
The process of collecting, cleansing, transforming, modeling, and communicating data to extract valuable insights for decision making.
p.10
Characteristics of Big Data
What does it mean for data to be heterogeneous?
Data consists of various types, such as tables, images, text, and more.
p.16
Data Representation Techniques
What are the components of 3D spatial data?
Longitude, latitude, and altitude.
p.1
Data Representation Techniques
What are common Data Representation Techniques?
Charts, graphs, and tables used to visualize data.
p.25
Jupyter Notebook as an IDE
What is the importance of using Markdown in Jupyter Notebook?
It helps in organizing and structuring the code for better readability.
What does x[5] represent in a string?
The sixth character of the string.
p.10
Characteristics of Big Data
What is a challenge related to integrating heterogeneous data?
It is difficult to integrate data from various sources and formats.
p.13
Data Representation Techniques
What does the notation 'Vectrx' represent?
It represents a vector data structure.
p.10
Characteristics of Big Data
What types of data are mentioned as examples of heterogeneity?
Image data, text data, network data, geographic maps, and computer-generated simulations.
p.10
Characteristics of Big Data
What is a difficulty associated with creating common storage for heterogeneous data?
It is challenging to establish a unified storage solution.
p.4
Data Analytics vs. Data Science
What does data science encompass?
A set of fundamental principles, such as algorithms, that guide the extraction of knowledge from data.
p.7
Characteristics of Big Data
How many gigabytes are in one zettabyte?
1 Zettabyte = 1000 trillion GB.
p.10
Characteristics of Big Data
What challenges arise from ingesting heterogeneous data in real time?
It becomes harder to ingest due to the complexity and variety of data.
p.7
Characteristics of Big Data
What potential benefits can big data provide to businesses?
Business insights and profits.
p.21
Jupyter Notebook as an IDE
Why will Jupyter Notebook be used in this course?
It supports the Python language and provides an interactive environment.
p.7
Characteristics of Big Data
What are some challenges associated with big data?
Storage cost and processing cost.
