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AWS Initiate Berlin - Das Zeitalter von Big Data - So nutzen Sie Daten zum Entscheiden und Entdecken
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Ralph Winzinger, Solutions Architect, PS DACH
Berlin, 13.3.2018
Finding Meaning in the Noise:
Understanding Big Data with AWS Analytics
One tool to
rule them all
Big Data on AWS
Immediate Availability. Deploy instantly. No hardware to
procure, no infrastructure to maintain & scale
Trusted & Secure. Designed to meet the strictest
requirements. Continuously audited, including certifications
such as ISO 27001, FedRAMP, DoD CSM, and PCI DSS.
Broad & Deep Capabilities. Over 100 services and 100s
of features to support virtually any big data application &
workload
Hundreds of Partners & Solutions. Get help from a
consulting partner or choose from hundreds of tools and
applications across the entire data management stack.
The Modern Data Architecture
The Modern Data Architecture is Agile
Users Sources Models Applications Queries Processing
Value
Work
20%
80%
80%of what we consider
analytics is not analytics
80%of what we consider
analytics is not analytics
Data Acquisition
Indexing
Discovery
Storage
Security
Access
Governance
Automated and Reliable
Data Ingestion
Preservation of Original
Source Data
Lifecycle Management
and Cold Storage
Meta-Data Capture
Managing Governance,
Security & Privacy
Self-Service Discovery,
Search, Access
Manage Data Quality
Preparing for Analytics
Orchestration and
Job Scheduling
Capturing Data Change
Value
Work
80%
20%
80%is real value now and only
20% is preparation
Putting it all together
Building a Data Strategy on AWS
Kinesis Firehose
Athena
Query Service
GlueBatch
AWS IoT
Processing Data for
Analytics on Your
Data Lake
Broad Set of Analytics Capabilities
Batch
Processing
Data
Warehousing
Business
Reporting
Real-time
Processing
Predictive
Analytics
Processing & Analytics
T r a n s a c t i o n a l &
R D B M S
DynamoDB
NoSQL DB Relational
Database
Aurora
B I & D a t a
V i s u a l i z a t i o n
Kinesis Streams
& Firehose
B a t c h
EMR
Hadoop, Spark,
Presto
Redshift
Data Warehouse
Athena
Query Service
AWS Batch
Predictive
R e a l - t i m e
AWS Lambda
Apache Storm
on EMR
Apache Flink
on EMR
Spark Streaming
on EMR
Elasticsearch
Service
Kinesis Analytics,
Kinesis Streams
EastiCache DAX
FINRA Analyzes Billions of Transactions Daily
To respond to
rapidly changing
market dynamics,
FINRA, moved 75% of
its operations to
Amazon Web
Services, using AWS
to analyze 75B
records a day.
FINRA uses Amazon EMR and Amazon S3 to process up to 75 billion
trading events per day and securely store over 5 petabytes of data,
attaining savings of $10-20mm per year.
Fraud Detection
• AWS enables you to build sophisticated data strategies and related
analytics applications
• Retrospective, Real-time, Predictive
• You can build incrementally, adding use cases and increasing scale
as you go
• AWS provides a broad range of security and auditing features to
enable you to meet your security requirements
https://aws.amazon.com/big-data/
AWS Initiate Berlin - Das Zeitalter von Big Data - So nutzen Sie Daten zum Entscheiden und Entdecken
Thank you

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AWS Initiate Berlin - Das Zeitalter von Big Data - So nutzen Sie Daten zum Entscheiden und Entdecken

  • 2. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Ralph Winzinger, Solutions Architect, PS DACH Berlin, 13.3.2018 Finding Meaning in the Noise: Understanding Big Data with AWS Analytics
  • 3. One tool to rule them all
  • 4. Big Data on AWS Immediate Availability. Deploy instantly. No hardware to procure, no infrastructure to maintain & scale Trusted & Secure. Designed to meet the strictest requirements. Continuously audited, including certifications such as ISO 27001, FedRAMP, DoD CSM, and PCI DSS. Broad & Deep Capabilities. Over 100 services and 100s of features to support virtually any big data application & workload Hundreds of Partners & Solutions. Get help from a consulting partner or choose from hundreds of tools and applications across the entire data management stack.
  • 5. The Modern Data Architecture
  • 6. The Modern Data Architecture is Agile Users Sources Models Applications Queries Processing
  • 7. Value Work 20% 80% 80%of what we consider analytics is not analytics
  • 8. 80%of what we consider analytics is not analytics Data Acquisition Indexing Discovery Storage Security Access Governance
  • 19. Value Work 80% 20% 80%is real value now and only 20% is preparation
  • 20. Putting it all together
  • 21. Building a Data Strategy on AWS Kinesis Firehose Athena Query Service GlueBatch AWS IoT
  • 22. Processing Data for Analytics on Your Data Lake
  • 23. Broad Set of Analytics Capabilities Batch Processing Data Warehousing Business Reporting Real-time Processing Predictive Analytics
  • 24. Processing & Analytics T r a n s a c t i o n a l & R D B M S DynamoDB NoSQL DB Relational Database Aurora B I & D a t a V i s u a l i z a t i o n Kinesis Streams & Firehose B a t c h EMR Hadoop, Spark, Presto Redshift Data Warehouse Athena Query Service AWS Batch Predictive R e a l - t i m e AWS Lambda Apache Storm on EMR Apache Flink on EMR Spark Streaming on EMR Elasticsearch Service Kinesis Analytics, Kinesis Streams EastiCache DAX
  • 25. FINRA Analyzes Billions of Transactions Daily To respond to rapidly changing market dynamics, FINRA, moved 75% of its operations to Amazon Web Services, using AWS to analyze 75B records a day.
  • 26. FINRA uses Amazon EMR and Amazon S3 to process up to 75 billion trading events per day and securely store over 5 petabytes of data, attaining savings of $10-20mm per year. Fraud Detection
  • 27. • AWS enables you to build sophisticated data strategies and related analytics applications • Retrospective, Real-time, Predictive • You can build incrementally, adding use cases and increasing scale as you go • AWS provides a broad range of security and auditing features to enable you to meet your security requirements https://aws.amazon.com/big-data/