10. Components of a big data pipeline are :
• The messaging system
• Message distribution support to various nodes for
further data processing.
• Data analysis system to derive decisions from data.
• Data storage system to store results and related
information.
• Data representation and reporting tools and alerts
system.
11. Important parameters that a big data pipeline
system must have -
• Compatible with big data
• Low latency
• Scalability
• Flexibility
• Economic
• A diversity that means it can handle various use cases.
12. In a Big Data pipeline system, the
two core processes are -
• The messaging system
• The data ingestion process
14. Batch Layer
Serving Layer
Incoming
data Queries
Real time Layer
Data Storage Layer
Batch
Engine
Real Time
Engine
Serving
Backend
Historical data Result data
18. • Review large amounts of data
• Spot trends
• Identify correlations and unexpected relationships
• Present the data to others
Big data visualisation techniques offer a fast
and effective way to :
19. Various Big Data Visualisation examples
include :
1. Linear
2. 2D/Planar/Geospatial
3. 3D/Volumetric
4. Temporal
5. Multidimensional
6. Tree/hierarchical
21. Big data privacy risks
1. Data breaches
2. Data brokerage
3. Data discrimination
22. Best practices for maintaining the
privacy of big data -
1. Employ real-time Monitoring
2. Implement homomorphic encryption
3. Avoid collecting too much data
4. Prevent internal threats