Big Data is growing rapidly in terms of volume, variety, and velocity. The cloud is well-suited to handle Big Data challenges by providing elastic and scalable infrastructure, which optimizes resources and reduces costs compared to traditional IT. In the cloud, users can collect, store, analyze and share large amounts of data without upfront investment, and scale easily as needs change. Real-world examples show how companies in industries like banking, retail, and advertising are using the cloud's Big Data services to gain insights from large datasets.
10. Traditional analytics required a
fixed data model,
based on pre-known questions
Big Data promotes data exploration and
experimentation which leads to innovation
12. Lower costs,
faster throughput
Collection & Computation Collaboration
Generation
storage & analytics & sharing
Increased pressure on traditional IT and tools
13. Require tools designed for data
collection and computation at
any volume, velocity or format.
14. Software
• Designed for distribution
• Easy programming models
• Flexible language choice
• Platform for abstraction and ecosystem
• Good example: Hadoop
15. Infrastructure
• Designed for distribution
• Easy programming models
• Flexible language choice
• Platform for abstraction and ecosystem
• Good example: Cloud computing
23. “Over the next decade, the number of files or containers that
encapsulate the information in the digital universe will grow by
75x.
While the pool of IT staff available to manage them will grow
only slightly. At 1.5x”
- 2011 IDC Digital Universe Study
25. Cloud computing
30% 70%
The Old Managing All of the
IT World Using Big Data
“Undifferentiated Heavy Lifting”
26. Cloud computing
30% 70%
The Old Managing All of the
IT World Using Big Data
“Undifferentiated Heavy Lifting”
Cloud-Based Configuring
Infrastructure Analyzing and Using Big Data
Cloud Assets
70% 30%
42. Simple Storage Service
1 Trillion
1000,000
750,000
500,000
250,000
0,000
750k+ peak transactions per second
43. Global Accessibility
Region
US-WEST (N. California) EU-WEST (Ireland)
GOV CLOUD ASIA PAC (Tokyo)
US-EAST (Virginia)
US-WEST (Oregon)
ASIA PAC
(Singapore)
SOUTH AMERICA (Sao Paulo)
44. Amazon DynamoDB
Managed NoSQL database service
Unlimited size
Unlimited scale
Flexible key/value store
Consistent, low latencies (single digit milliseconds, SSD)
Robust, durable data storage
Integrated analytics with Elastic MapReduce
45. Amazon Elastic MapReduce
On-demand, managed analytics platform
Powered by Hadoop
Integrated with Spot instances to lower costs
Vibrant ecosystem of tools
Elastic clusters
Flexible programming model (Java, Python, Ruby etc)
47. Big Data Verticals
Social
Media/Advertisi Financial
Oil & Gas Retail Life Sciences Security Network/Gamin
ng Services
g
User
Anti-virus
Targeted Monte Carlo Demographics
Recommend
Advertising Simulations
Seismic Genome Fraud
Usage analysis
Analysis Analysis Detection
Image and
Transactions
Video Risk Analysis
Processing Analysis Image In-game
Recognition metrics
49. Bank – Monte Carlo Simulations
“The AWS platform was a good fit for its
unlimited and flexible computational power to
23 Hours to our risk-simulation process requirements.
With AWS, we now have the power to decide
20 Minutes how fast we want to obtain simulation
results, and, more importantly, we have the
ability to run simulations not possible before
due to the large amount of infrastructure
required.” – Castillo, Director, Bankinter