18 Questions
What is the primary advantage of using a relational database management system (RDBMS) like VoltDB?
Provides ACID guarantees for structured data
Which type of database is best suited for handling fast-moving data characterized by massive historical archives?
SQL databases like GenieDB
What is the key characteristic of NoSQL databases like CouchDB?
Schemeless and document-oriented
In the context of Big Data, what does the term 'Velocity' refer to?
Data useful in its temporal state
Which of the following is a characteristic feature of unstructured data?
Includes text, emails, pictures
What is the main advantage of using cloud storage for handling Big Data?
Enables scaling for large volumes of data
What is the purpose of the Insights stage in data analysis?
To extract meaningful insights like hidden patterns and market trends
Which of the following is NOT a commonly used method for conducting data analyses?
Structured Query Language (SQL)
What is the main function of a Relational Database Management System (RDBMS)?
Organizing and managing stored data in tables
What does ACID stand for in the context of Transaction Management in databases?
Atomicity, Consistency, Isolation, Durability
What can a Database Management System (DBMS) do?
Retrieve data and run queries
Which type of system solves problems when there are lots of transactions occurring concurrently?
Relational Database Management System (RDBMS)
What is the primary function of an analytics database?
Specialize in returning queries quickly
In the context of data lifecycle, which stage involves making formats and units consistent?
Data Preparation
What is the purpose of data imputation in the data preprocessing stage?
Filling in missing values
Which type of analytics deals with predicting future outcomes based on historical data?
Predictive analytics
What is the primary purpose of data visualization?
Summarize raw data into meaningful insights
Which task involves removing irrelevant or inaccurate data points from a dataset?
Removing suspicious data
Study Notes
- Data in Big Data are quantities, characters, or symbols processed by computers, containing value and knowledge that needs to be stored, managed, and analyzed to extract insights.
- Big Data is characterized by the 3Vs: Velocity (moves at high rates), Volume (massive historical archives), and Variety (from structured to unstructured data).
- Examples of sources for Big Data include online gaming, sensor data, financial trade, internet commerce, and mobile platforms.
- Different data management tools for Big Data include DBMS & Cloud for storing and scaling, New SQL for structured data, and NoSQL for unstructured data.
- The stages of working with data involve collecting data through research and making inferences to gain insights, with steps like data preparation, collection, analysis, visualization, and decision-making.
Test your knowledge of the fundamental concepts related to big data, including the definition of data, the characteristics of big data, and the importance of storing, managing, and analyzing data for extracting insights. Explore the challenges posed by the volume and complexity of big data.
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