The Big Data Guide
FAQs
Big data refers to incredibly large amounts of data (including both structured and unstructured data) that exceeds what traditional data processing software had historically been able to manage through the 1990s and early 2000s (e.g., terabytes vs zettabytes).
- Volume: This refers to the amount of data being collected.
- Velocity: This refers to the speed at which the data is ingested into the system, as well as the speed at which the data changes/updates over time.
- Variety: This refers to the various formats the data takes, as well as the different data sources ingested.
- Structured data: Structured data is usually composed of alphanumeric characters translated into a predefined format before being fed into a predetermined data model.
- Semi-structured data: Semi-structured data has some level of structure and organization but does not conform to the rigid data schema needed to align with traditional structured data requirements.
- Unstructured data: Unstructured data doesn't have consistent structure or schema and can be found in a variety of formats.
These formats can include everything from videos, images, and audio files to documents, web logs, sensor data, and binary data.
- Data sources
- Data collection and ingestion
- Data storage
- Data processing
- Data analytics
- Data visualization
- Data security and monitoring
- Parallel computing
- Elastic scalability
- Freedom of choice
- Interoperability
- Security
- Complexity
- Evolving technologies
- Specialized skill sets
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