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Questions and Answers
What percentage of data in organizations is estimated to be unstructured?
What percentage of data in organizations is estimated to be unstructured?
Which company is said to store, access, and analyze more than 30 Petabytes of user-generated data?
Which company is said to store, access, and analyze more than 30 Petabytes of user-generated data?
What is one major benefit of Big Data application in the telecom sector?
What is one major benefit of Big Data application in the telecom sector?
In the context of retail, what does Amazon's recommendation engine primarily rely on?
In the context of retail, what does Amazon's recommendation engine primarily rely on?
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How can effective use of data and sensors help in traffic management in densely populated cities?
How can effective use of data and sensors help in traffic management in densely populated cities?
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What is one way big data can improve the healthcare sector?
What is one way big data can improve the healthcare sector?
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What challenge is associated with analyzing big data in manufacturing?
What challenge is associated with analyzing big data in manufacturing?
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What is one benefit Google gains from extracting information from user searches?
What is one benefit Google gains from extracting information from user searches?
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What was a significant development in 2005 that contributed to the handling of big data?
What was a significant development in 2005 that contributed to the handling of big data?
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Which of the following accurately describes a feature of big data?
Which of the following accurately describes a feature of big data?
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How has the Internet of Things (IoT) impacted big data?
How has the Internet of Things (IoT) impacted big data?
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What does the concept of 'elastic scalability' in cloud computing refer to?
What does the concept of 'elastic scalability' in cloud computing refer to?
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Which statement is true about the evolution of big data?
Which statement is true about the evolution of big data?
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Which of the following practices is part of big data processing?
Which of the following practices is part of big data processing?
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What characteristic of big data makes it challenging to process using conventional techniques?
What characteristic of big data makes it challenging to process using conventional techniques?
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Which of the following best defines big data?
Which of the following best defines big data?
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What is a significant consequence of a business not adapting to customer expectations?
What is a significant consequence of a business not adapting to customer expectations?
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Which of the following is NOT a major source of Big Data?
Which of the following is NOT a major source of Big Data?
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How does big data analytics affect marketing campaigns?
How does big data analytics affect marketing campaigns?
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What is one of the challenges associated with Big Data?
What is one of the challenges associated with Big Data?
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Why has the data growth rate increased rapidly in recent years?
Why has the data growth rate increased rapidly in recent years?
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Which term describes datasets that are large and complex, making them difficult to store and process?
Which term describes datasets that are large and complex, making them difficult to store and process?
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What role does observing customer behavior play in business?
What role does observing customer behavior play in business?
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What is the predicted amount of data volumes by the year 2020?
What is the predicted amount of data volumes by the year 2020?
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What does the 'composition' of data refer to?
What does the 'composition' of data refer to?
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Which characteristic of Big Data describes the 'amount of data' generated?
Which characteristic of Big Data describes the 'amount of data' generated?
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How is 'velocity' defined in the context of Big Data?
How is 'velocity' defined in the context of Big Data?
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What type of data is indicated to be included in the 'variety' aspect of Big Data?
What type of data is indicated to be included in the 'variety' aspect of Big Data?
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What does the 'condition' of data evaluate?
What does the 'condition' of data evaluate?
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Which of the following statements about Big Data is true regarding future data generation?
Which of the following statements about Big Data is true regarding future data generation?
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Which aspect of data does 'context' refer to?
Which aspect of data does 'context' refer to?
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Which challenge does the 'variety' of Big Data create?
Which challenge does the 'variety' of Big Data create?
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What is one of the main challenges faced when combining unstructured and inconsistent data in data lakes or warehouses?
What is one of the main challenges faced when combining unstructured and inconsistent data in data lakes or warehouses?
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Which statement accurately contrasts traditional Business Intelligence (BI) with big data?
Which statement accurately contrasts traditional Business Intelligence (BI) with big data?
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What is a major security concern associated with big data?
What is a major security concern associated with big data?
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In what environment is data typically analyzed in both real-time and offline modes?
In what environment is data typically analyzed in both real-time and offline modes?
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What is a characteristic feature of a Data Warehouse (DW)?
What is a characteristic feature of a Data Warehouse (DW)?
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How does data processing change between traditional BI and big data environments?
How does data processing change between traditional BI and big data environments?
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What type of data does a Data Warehouse primarily manage?
What type of data does a Data Warehouse primarily manage?
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Which statement accurately describes a feature of big data tools?
Which statement accurately describes a feature of big data tools?
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What does it mean for a data warehouse to be subject-oriented?
What does it mean for a data warehouse to be subject-oriented?
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Which attribute refers to the consistent formatting of data from different sources within a data warehouse?
Which attribute refers to the consistent formatting of data from different sources within a data warehouse?
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Why is data in a data warehouse considered nonvolatile?
Why is data in a data warehouse considered nonvolatile?
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What does the term time variant describe in the context of a data warehouse?
What does the term time variant describe in the context of a data warehouse?
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Which of the following best describes the utilization of a data warehouse?
Which of the following best describes the utilization of a data warehouse?
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What kind of data relationships do data warehouses typically focus on?
What kind of data relationships do data warehouses typically focus on?
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How do data warehouses handle historical data compared to online transaction processing systems?
How do data warehouses handle historical data compared to online transaction processing systems?
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Which of the following statements is true about data warehouse structures?
Which of the following statements is true about data warehouse structures?
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Study Notes
Unit 1: Introduction to Big Data
- Big data is a collection of large and complex datasets.
- Its origins date back to the 1960s and 70s.
- Big data is characterized by its volume, velocity, variety, and veracity.
- Key sources of big data include social media, e-commerce sites, weather stations, telecommunication companies, and the stock market.
- The volume of big data is growing exponentially.
- Big data is difficult to store and process using traditional methods due to its large volume & variety.
- Specialized tools and frameworks are needed to handle big data.
- Big data has many applications across various industries, such as healthcare, telecom, retail, and manufacturing.
- Big data analytics provides organizations with insights and helps make better business decisions.
Big Data Characteristics
- Volume: The massive amount of data generated daily, growing at a rapid pace. Data size has increased significantly from 2005 on.
- Velocity: The speed at which data is generated and processed, often in real-time. This real-time nature is critical for many applications.
- Variety: The different formats and types of data that can be processed (structured, semi-structured, and unstructured). This includes structured data like logs and semi-structured like JSON documents, versus unstructured like images, audio, and video.
- Veracity: The accuracy, completeness, and trustworthiness of the data, critical for ensuring data quality. Inaccurate data leads to poor decisions.
Types of Big Data
- Structured: Data that conforms to a predefined schema, organized in tables like a relational database management system (RDBMS)
- Semi-structured: Data that has some organizational structure but no fixed format, like JSON and XML. Data often has tags that identify specific parts of the information
- Unstructured: Data with no predefined format or organization, like images, audio, videos, sensor data
Big Data Challenges
- Data Synchronization: Integrating diverse and disparate datasets. Different sources may not use the same format, terminology or units of measurement, leading to problems and inconsistencies when combined
- Data Professionals: A shortage of professionals with the skills to work efficiently with big data. The needed skills are multidisciplinary.
- Meaningful Insights: Extracting actionable insights from the huge amount of data.
- Data Storage and Quality: Effectively storing and managing big data of various types.
- Data Security and Privacy: Ensuring data is protected and used responsibly.
- Data accessibility: The sheer volume of data can challenge the ability to access and utilize data for decision-making.
Data Warehousing
- A subject-oriented, integrated, non-volatile, and time-variant data repository.
- Designed specifically for analysis, not transaction processing.
- Data is stored in the data warehouse to support decision-making.
- Common attributes of typical data warehouses: data stored is historical to focus on what already happened; data access is often read intensive; relatively few large tables store the data; data is integrated into a useful format; data is non-volatile, which means not changing, once input.
Data Warehouse Goals
- Support reporting and analysis by storing historical data.
- Provide a foundation for better decision making.
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Description
This quiz covers the fundamentals of Big Data, including its characteristics such as volume, velocity, variety, and veracity. It also explores the historical context, sources, and applications across various industries, emphasizing the challenges and solutions in handling large datasets.
