1. Big Data & Its Analysis 17-Feb-2017 Dr. M. Naci Akkøk, Chief Architect
Oracle Nordic

2. This Presentation … Lecture goal:
Overview “Big Data” technologies including Big Data Analytics (and AI)
Content:
Big Data Technologies
Big Data Analytics (generic)
Big Data Analytics and Artificial Intelligence (AI)
Cloud (is changing the whole picture…)
Q&A

3. What /why Big Data?
Big Data is NOT a single product or technology: Big Data is a set of needs addressed by several technologies.
IoT, social media, need to accumulate data and analyze them
“actionably” fuels Big Data.
A technology is best understood through an understanding of the demands that created it.
Dr. M. Naci Akkøk

4. What are the needs Big Data aims to address
What are the needs Big Data aims to address? Classical definition: “the V4 Challenge”
Volume: Large amounts
Velocity: High speed input
Variety: Many types of data sources, different database technologies, different structures/formats etc.
Value: Information value of acquired or stored data (large volumes of data, sparse information), analysis, reporting, discovery, prediction, learning

5. Data Lab and Data Management (incl
Data Lab and Data Management (incl. Data Quality) are key Components of any (healthy) Big Data Architecture
Data
Fast Data
Events
Actions
Streams
Apps
Packaged
Custom
Results
People
Data Services
Smart Things
Data Management
Reservoir
Factory
Warehouse
Business Analytics
Visualization
Reports
Data Lab
Data Science
Discovery
Data Sets
Oracle Confidential – Internal | Business Analytics Product Group

6. Typical (generic) Big Data “Solution”
End-User Applications ?
(Velocity, Variety) Acquisition &
Live Stream Analysis
(Volume, Variety)
Data Storage &
Archival (Reservoir)
(Value)
Stored or Archived
Data Analysis &
Discovery
Applications & Development Platform, SDK
Data & MW Integration, Security, Other MW Functions
Sensor-level development/test
(Centralized)
Cloud
SDK

8. Examples, References: A combination of needs & technologies
IOT + BDA + BDD + OAA examples with similar tools or use-cases!

9. Samples real-life examples and use-cases
HEALTH CARE
PUBLIC SECTOR
MANUFACTURING
COMMUNICATIONS
RETAIL
UTILITIES, ENERGY
All of the major Analysts, including McKinsey, have identified Big Data as a source for competitive advantage. Oracle´s Customers are already investing heavily in this area and we expect this increased investment to grow further in the near future.
NHS – UK Health Service invested in a Big Data solution to help identify and reduce fraud associated with drug prescriptions. The Health Service is funded by the UK Tax Payer and this solution has the potential to save £10s Millions.
Ministry of Education in Turkey decided 2 years ago to transform how they deliver educational services for 18M students across 42,000 Schools. The deal was worth $11M to Oracle and was a XLOB deal where CT, Systems, FMW and BI Sales teams were compensated. The deal also included 8 Engineered Systems including BDA, Exadata, Exalogic and Exalytics. MONE is predominantly a Microsoft account.
Airbus in France are utilising a Big Data solution to take sensor data from flight tests and to help reduce the time taken to complete testing and development of new aircraft. The solution is helping to reduce costs, provides the ability for Airbus to scale the amount of data it can handle and also speed up its time to value from shipping new aircraft faster.
Turkcell in Turkey use an Oracle Big Data solution for Customer Analytics and Real Time offers. They are delivering a service where 3rd parties can make offers to Turkcell customers based on their profile and their location in real time. This ‘mobile billboard’ service is generating new revenues for Turkcell and helping them find new ways to monetize data.
Procter & Gamble in the US are using a Big Data solution to examine consumer interaction data to better understand factors contributing to purchase decisions, and the subsequent rise or decline in market share. P&G integrated vast amounts of structured and unstructured data across research and development, supply chain, customer-facing operations, and customer interactions from traditional data sources and new online data sources which had not previously been collected and analyzed. The solution is further helping the company put the right product at the right price in front of the right shoppers at the right time, in stores and online
Reduce Prescription Fraud
Improve Student Outcomes
Accelerate Test Cycles to Reduce Backlog
Offering New Services based on Location Data
Better Predict Product Success
Meter User Data
Reservoir
Note that they are all solutions utilizing different mixtures of Volume, Velocity, Variety and Value challenges! IOT and big data worlds (often) overlap and fuel each other. IOT is becoming main-line. And with the advent of Internet of Nano-things (ION), D2D cross-communication is going to grow dramatically, requiring data management for faster and bigger data.
Be ready, be there!
Dr. M. Naci Akkøk – Lecture notes

10. [UC01] Replace road signs with GPS-driven head-up displays in the cars
[UC02] Just-in-time car-pooling, ”fetch-me-too” app.
[UC03] Sensor and GPS applied road (pilot, Trondheim)
[UC04] Roads, tunnels, other constructions and ground & materials monitoring with sensors
[UC05] Fraud detection (economy, projects etc.)
[UC06] Monitoring, analysis and prevention of accidents and almost-accidents
[UC07] Road capacity and characteristics for vehicles (typical in ITS)
[UC08] Analysis and discovery with correlations to other data (like weather data)
[UC09] Car-to-Car warning systems (Example: Experienced danger conveyed to cars behind)
[UC10] Improve manual road-controls using drones and sensors
[UC11] Software development kit (SDK) and data for service development (also for 3rd parties)
Use Cases, Innovations Intelligent Transportation Systems (ITS) and related challenges