Big Data

• What is the generic term for large datasets that are difficult to store and analyze?

  Big Data
• Why do big datasets require multiple servers?

  To store and provide access within a timescale
• What is a limitation of standard database software regarding big data?

  It can't handle high volumes of data
• In which sectors is big data commonly used?

  Retail, banking, government, mobile networks
• What are the three main characteristics of big data?

  Volume, velocity, variety
• What does latency refer to in the context of big data?

  Time delay between request and data receipt
• What type of data is defined using traditional database techniques?

  Structured data
• What is unstructured data?

  Data that cannot be defined in columns and rows
• Why is qualitative data harder to analyze than quantitative data?

  It is more likely to be unstructured
• How does machine learning assist in analyzing qualitative data?

  It automates the analysis process
• What is predictive analysis used for in the financial sector?

  To predict risk
• What are some issues associated with big data?

  Storage difficulties, unstructured data challenges
• What is required to handle big data effectively?

  Specialist software, massive storage, processing power
• Why is it difficult to keep track of big data?

  Data is constantly changing
• What issue arises from multiple users accessing big data simultaneously?

  Issues with concurrency