Presented at the Artificial Intelligence for Knowledge Management (AI4KM), 2017, Melbourne, Australia
Artificial Intelligence, Semantic Data Lake, Social Analytics
3. Data Lake vs Data Warehouse/Mart
3
Usage:
• Fishing
• Boat Ride
• Storage and Supply Drinking Water
• Water Skiing
• Swimming
• Diving
• Snorkelling
• etc
Usage:
• Storage & Consume
Drinking Water
MULTIPLE USAGE SPECIFIC USAGE
Credit: Pradeep Manon (2017). Demystifying Data Lake ArchitectureArtificial Intelligence for Knowledge Management (AI4KM), 2017
4. Data Lake (Data Swamp) vs Semantic Data Lake
4
DATA LAKE
4
Enterprise Data
Sensor Web
Structured, Semi-Structured
& Unstructured
Unstructured (Structured) Structured & Semi-
Structured
Structured
Linked Open Data
CRAWLERS DATA HARVESTERS
WEB
KNOWLEDGE
HARVESTER
DATA
INGESTION ENGINE
Social Media
?DATA
SWAMP
SEMANTIC
DATA LAKE
HARMONIZATION
CLEANSING
FUSION
DEDUPLICATION
Artificial Intelligence for Knowledge Management (AI4KM), 2017
5. Big Data Challenge: Social Analytics
Sentiment Analytics Social Network Analytics
Anxiety Analytics Cluster Analytics
Personality Analytics Connector Analytics
Emotion Analytics Influencer Analytics
Concern Analytics Association Analytics
• Social Analytics is an umbrella term that includes a number of specialized analysis techniques, such
as social filtering, social network analysis, social channel analysis, sentiment analysis and social media
analytics.
• GCS Agile can perform the following big-data analytics:
•To-date, some of the areas this technology been applied to are listed below:
• Monitoring chatter in the Network of People
• Analysing chatter on Public Listed Companies
• Analysing personality, strengths and weakness of Individuals
• Analysing chatter among citizens on Public Services
• Analysing consumer chatter on specific Produce and Service
• Analysing public chatter on Crime in Specific Location.
• Analysing public chatter on specific Prominent People.
Artificial Intelligence for Knowledge Management (AI4KM), 2017