Podcast
Questions and Answers
Which component carries the highest weight in the course assessment?
Which component carries the highest weight in the course assessment?
- Final exam (correct)
- Assignment
- Project
- Participation
What will happen if a student is caught cheating or plagiarizing?
What will happen if a student is caught cheating or plagiarizing?
- They will receive zero marks for that assessment. (correct)
- They will be expelled from the course.
- They will be given a warning.
- Their attendance will be affected.
How should a student communicate if they are unable to meet a deadline?
How should a student communicate if they are unable to meet a deadline?
- Talk to the professor after class.
- Submit the assignment late with an apology.
- Send an email before the deadline. (correct)
- Ask a classmate to inform the professor.
According to the course rules, what is permitted in class?
According to the course rules, what is permitted in class?
What defines Big Data according to the course content?
What defines Big Data according to the course content?
How many members are allowed in a project group?
How many members are allowed in a project group?
What aspects should a student focus on to earn their final grade?
What aspects should a student focus on to earn their final grade?
What characterizes structured data?
What characterizes structured data?
Which of the following types of data is considered unstructured?
Which of the following types of data is considered unstructured?
What are the 3 Vs of big data according to Laney?
What are the 3 Vs of big data according to Laney?
Which statement about analytics is true?
Which statement about analytics is true?
What does the term 'veracity' refer to in the context of big data?
What does the term 'veracity' refer to in the context of big data?
What is the primary focus of predictive analytics?
What is the primary focus of predictive analytics?
Which of the following is NOT a characteristic of big data?
Which of the following is NOT a characteristic of big data?
Which analytics type is best suited for answering the question, 'What has happened?'
Which analytics type is best suited for answering the question, 'What has happened?'
What is a primary goal of using analytics in big data?
What is a primary goal of using analytics in big data?
Which of the following formats is typically considered structured data?
Which of the following formats is typically considered structured data?
Which of the following best describes prescriptive analytics?
Which of the following best describes prescriptive analytics?
What role do data scientists typically focus on?
What role do data scientists typically focus on?
Which technology is considered the leader in the analytics market?
Which technology is considered the leader in the analytics market?
What is one of the key buzzwords associated with analytics?
What is one of the key buzzwords associated with analytics?
What is one characteristic that defines Big Data?
What is one characteristic that defines Big Data?
Business intelligence primarily involves which of the following?
Business intelligence primarily involves which of the following?
Which of the following is typically NOT a source of Big Data?
Which of the following is typically NOT a source of Big Data?
Which of the following represents a key component in data science?
Which of the following represents a key component in data science?
What is a major benefit of platforms like data lakes and Hadoop in relation to Big Data?
What is a major benefit of platforms like data lakes and Hadoop in relation to Big Data?
Which statement best describes the sampling size characteristic of Big Data?
Which statement best describes the sampling size characteristic of Big Data?
Why is it significant to handle Big Data in near-real time?
Why is it significant to handle Big Data in near-real time?
Which of the following statements about Big Data is correct?
Which of the following statements about Big Data is correct?
Which of the following challenges is associated with Big Data?
Which of the following challenges is associated with Big Data?
Which software product is known for its integrated platform providing end-to-end solutions in business intelligence?
Which software product is known for its integrated platform providing end-to-end solutions in business intelligence?
Which of the following programming languages is characterized as an interpreted, high-level, general-purpose language?
Which of the following programming languages is characterized as an interpreted, high-level, general-purpose language?
In which area is R primarily used?
In which area is R primarily used?
What is one of the main features of Hadoop?
What is one of the main features of Hadoop?
Which tool is widely recognized for creating interactive graphs and dashboards for business intelligence?
Which tool is widely recognized for creating interactive graphs and dashboards for business intelligence?
Which of the following is NOT an area that commonly uses Python?
Which of the following is NOT an area that commonly uses Python?
What distinguishes SAS's analytics solutions in the market?
What distinguishes SAS's analytics solutions in the market?
What key feature does R offer that enhances its functionality?
What key feature does R offer that enhances its functionality?
Flashcards
Big Data
Big Data
Data that is so large, complex, or fast that it's difficult to process using traditional methods.
Non-Traditional Sample Size
Non-Traditional Sample Size
Data sets so big that traditional methods, like statistical analysis tools, can't handle them effectively.
Data That Won't Fit in Main Memory
Data That Won't Fit in Main Memory
Data that doesn't fit into your computer's main memory, requiring specific tools for processing.
Velocity of Big Data
Velocity of Big Data
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Volume of Big Data
Volume of Big Data
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What is big data?
What is big data?
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Final exam weight
Final exam weight
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Assignment weight
Assignment weight
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Project weight
Project weight
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Academic honesty
Academic honesty
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Attendance requirement
Attendance requirement
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Communication with the instructor
Communication with the instructor
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Deadline communication
Deadline communication
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Structured data
Structured data
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Unstructured data
Unstructured data
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Big Data Analytics
Big Data Analytics
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Big Data: Volume
Big Data: Volume
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Big Data: Velocity
Big Data: Velocity
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Big Data: Variety
Big Data: Variety
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Big Data: Veracity
Big Data: Veracity
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Analytics
Analytics
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Predictive Analytics
Predictive Analytics
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Descriptive Analytics
Descriptive Analytics
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Prescriptive Analytics
Prescriptive Analytics
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Machine Learning
Machine Learning
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Data Mining
Data Mining
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Data Science
Data Science
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Business Intelligence
Business Intelligence
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SAS
SAS
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R
R
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Hadoop
Hadoop
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Python
Python
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Tableau
Tableau
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Data Analytics
Data Analytics
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Data Visualization
Data Visualization
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Study Notes
Class Rules
- Students can do anything except make noises (chatting, singing).
- Students can interrupt with questions.
- Attendance is required according to university policy.
- 80% attendance is necessary to sit the final exam.
Course Assessment
- The final exam is worth 50%.
- Assignments are worth 20% (individual).
- Projects are worth 30% (groups of 2-3 people). Project includes a report and presentation.
- Cheating and plagiarism result in zero marks.
- Course assessment is temporary; this can change.
What is Big Data?
- Big data is data that doesn't fit in main memory.
- Examples include web server access logs, the graph of the entire internet (Wikipedia), and daily satellite images over a year.
- It also includes data with a large number of observations and/or features.
- Non-traditional sample sizes (e.g., > 100 subjects) are difficult to analyze using traditional statistical tools (like Excel).
Big Data Characteristics
- Volume: Large quantities of data.
- Velocity: Data arriving quickly.
- Variety: Data comes in many formats (structured or unstructured).
- Veracity: Data quality (accuracy).
Big Data Tools
- Hadoop
- Apache Storm
- Spark
- Hive
- Tableau
- R
- Python
Analytics
- Analytics is the scientific process of transforming data into insights for better decision-making.
- Big data isn't valuable in itself; it's how you use it.
Types of Analytics
- Predictive analytics: Predicting future happenings based on past patterns.
- Descriptive analytics: Analyzing existing business practices for insights.
- Prescriptive analytics: Making decisions based on data for best outcomes.
Analytics Buzzwords
- Big data
- Machine learning
- Data science
- Data mining
- Business intelligence
Data Science
- Data science is a field encompassing multiple areas including data systems, business intelligence, machine learning, data science, and analytics.
- It emphasizes in-depth knowledge in one or two aspects of these areas.
- Specific teams may cover all these areas.
SAS
- SAS is the leading vendor in business intelligence.
- It offers a platform for end-to-end solutions and is the industry standard for clinical data analysis.
- Provides domain-specific analytics solutions across various industries.
R
- R is a widely used statistical computing language that is highly extensible.
Hadoop
- Hadoop is a popular big-data ecosystem.
- It can handle large computations across multiple machines.
Python
- Python is a high-level programming language very popular for diverse uses including Web Development, Game Development, and Machine Learning among others.
Tableau
- Tableau is a data visualization tool for business intelligence.
- Enables interactive charts and dashboards to gain insights.
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Description
This quiz covers the essential class rules and the fundamental concepts of Big Data. It highlights important assessment criteria and characteristics of Big Data, including its volume and the challenges it presents. Test your knowledge on key definitions and course policies!
