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Questions and Answers
What does 'Velocity' refer to in the context of big data?
What is the main focus of analytics in the context of big data?
What is a characteristic of big data related to its 'Volume'?
What does 'Variety' refer to in the context of big data?
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What is the primary focus of descriptive analytics?
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Which type of analytics is used for diagnosing the reasons as to why certain events happened?
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What is the main purpose of predictive analytics?
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Which type of analytics involves analyzing past data to present it in a summarized form?
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What is the main focus of prescriptive analytics?
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Which type of data is involved in big data analytics?
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What techniques are used in big data analytics?
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When are specialized tools and frameworks required for big data analysis?
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What are the three main characteristics of big data mentioned in the text?
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Which type of analytics involves analyzing historical data to search for patterns indicating fraud?
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In which phase of the big data analytics life-cycle is the data stored in specialized storage solutions designed to scale?
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What can wearable electronic devices allow in the healthcare example mentioned in the text?
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Study Notes
Velocity in Big Data
- Refers to the speed at which data is generated, processed, and analyzed.
- Real-time data streaming is crucial for timely decision-making.
Analytics Focus in Big Data
- Main focus is on extracting meaningful insights to guide decisions.
- Aims to derive value from data through various analytical techniques.
Volume in Big Data
- Characteristic denotes the immense quantity of data generated daily.
- Data sources include social media, sensors, transactions, and more, leading to terabytes to petabytes of data.
Variety in Big Data
- Refers to the diverse types of data, including structured, semi-structured, and unstructured formats.
- Examples include text, images, videos, and sensor data.
Descriptive Analytics
- Primary focus is on summarizing past data to understand trends and patterns.
- Helps businesses understand what happened in historical data.
Diagnostic Analytics
- Utilized for identifying reasons behind specific past events or outcomes.
- Involves analyzing data to uncover cause-and-effect relationships.
Predictive Analytics
- Aims to forecast future events based on historical data patterns.
- Utilizes statistical models and machine learning techniques for predictions.
Summarization in Analytics
- Descriptive analytics presents past data in a summarized format.
- Helps in grasping key trends without delving into raw data.
Prescriptive Analytics
- Focuses on recommending actions based on data insights.
- Involves decision-making processes to optimize outcomes.
Types of Data in Big Data Analytics
- Involves various forms such as structured databases, unstructured documents, and streaming data from IoT devices.
- Data types enhance insights through comprehensive analysis.
Techniques in Big Data Analytics
- Includes machine learning, data mining, statistical analysis, and natural language processing.
- Techniques enable extraction of actionable insights from massive datasets.
Specialized Tools for Big Data
- Required when traditional data processing software is insufficient for handling large volumes and velocities of data.
- Tools and frameworks facilitate scalability, storage, and processing capabilities.
Characteristics of Big Data
- Three main characteristics: Volume, Velocity, and Variety.
- These characteristics define the complexity and scale of data processing needs.
Fraud Detection Analytics
- Involves analyzing historical data to spot patterns indicating fraudulent activity.
- Uses advanced algorithms to identify anomalies and suspicious behavior.
Data Storage in Big Data Analytics Life-Cycle
- During the storage phase, data is housed in specialized solutions that can scale to handle growing volumes.
- Ensures efficiency and effectiveness in data management.
Wearable Electronic Devices in Healthcare
- Allow for continuous monitoring of patients' health metrics.
- Enable real-time data collection, aiding timely interventions and personalized care.
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Description
Test your knowledge about prescriptive analytics and big data, including prediction models, outcomes, and advanced analytic techniques used against large and diverse data sets.
