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11.0 Big Data
11.1 Characteristics of Big Data
11.1.1 Volume, velocity, variety
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What does Big Data refer to?
Large and complex datasets
The three characteristics of Big Data are often referred to as the 3
Vs
Big Data can improve
operational
efficiency.
What does the term "Volume" in Big Data refer to?
The quantity of data
The characteristic "Velocity" in Big Data focuses on the
speed
at which data is generated and processed.
Order the following examples of high-velocity data sources from most continuous to least continuous:
1️⃣ IoT sensor data
2️⃣ Streaming services
3️⃣ Social media feeds
Match the type of data with its description:
Structured data ↔️ Organized data with predefined fields
Unstructured data ↔️ Data without a defined format
Semi-structured data ↔️ Data with some organizational properties
Integrating different data types is a key challenge of Big Data's "Variety"
characteristic
.
Which of the 3 Vs of Big Data describes the speed of data generation and processing?
Velocity
Big Data is used to improve decision-making, enhance customer experiences, and drive
innovation
.
"Volume" in Big Data refers to the accuracy of the data being processed.
False
What is an example of a data source that generates billions of daily posts?
Social media feeds
Analyzing large volumes of data requires advanced Big Data
technologies
.
Big Data is characterized by its enormous
volume
The volume of Big Data is often too large for
traditional databases
to handle.
How many customer transactions are processed daily in Big Data examples?
Millions
In Big Data, velocity refers to the speed at which data is generated, collected, and
processed
What type of data is generated by IoT sensors in Big Data examples?
Sensor data
Delivering insights with minimal
latency
is a key challenge in Big Data velocity.
What are three benefits of Big Data velocity?
Timely decision-making, customer engagement, efficiency
Real-time social media feeds allow businesses to respond quickly to
market changes
.
The variety of Big Data refers to the different types and formats of
data
that organizations manage.
Match the data type with its example in Big Data:
Structured ↔️ Customer transaction data
Unstructured ↔️ Text from emails
Semi-structured ↔️ Server logs
Overcoming challenges in data variety leads to
comprehensive
insights and better decision-making.
What are the 3 Vs of Big Data?
Volume, Velocity, Variety