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BIG DATA & ORACLE
TECHNOLOGIES
KIEV
OCT 2013
PRACTIC CONSULTING
Alliance of Professional IT & Management Consultants
HTTP://PRACTIC-CONSULTING.COM
Agenda
• ABOUT BIG DATAWHAT
• INDUSTRY EXAMPLES OF BIG DATAWHEN
• ORACLE NO SQL
• ORACLE R
• ORACLE ENDECA
HOW
WHAT IS BIG DATA?
PART I
What Is Big Data?
Big Data – is data that becomes large
enough that it cannot be processed
using conventional methods
Big Data – is the new generation
of data warehousing and
business analysis systems
010101101010100101010101010101010010101010100101010101001010101010010101010101010100101
010100101010101010101001010101010010101010101010010101001010101001010101001010101001010
101010101001010101010100101010100101010100101010100101010101001010101001010101001010101
010010101010100101010010101001010101001010101001010100101010010101010010101010010101010
010101010010101001010101010101010101010101010010101010010101010010101010010101010010101
010010101010010101010010101010010101010010101010010101010010100101010100101010100101010
A Wider Variety of Data
Internet
Data
 Clickstream
 Social media
 Social media stream
 Web site logs
Research
Data
 Experiments
 Observations
 Surveys
 Marketplace data
Healthcare
Data
 Treatment data
 Telehealth
 National Electronic Health Records
 Procedures
Image
Data
 Image
 Video
 Satellite image
 Surveillance
Device
Data
 RF Devices
 Sensors
 EDI
 Telemetry
Why Is Big Data Important?
Big Data - Just another buzzword
or powerful business & science enabler?
SQL
Analytics
• Count
• Mean
• OLAP
Descriptive
Analytics
• Univariate
distribution
• Central
tendency
• Dispersion
Data Mining
• Association
rules
• Clustering
• Feature
extraction
Predictive
Analytics
• Classification
• Regression
• Forecasting
• Spatial
• Machine
Learning
• Text
Analytics
Simulation
• Monte Carlo
• Agent-based
modeling
• Discrete
event
modeling
Optimizatio
n
• Linear
Optimization
• Non-Linear
Optimization
Business Intelligence Advanced Analytics
INDUSTRY EXAMPLES
OF BIG DATA
PART II
Marketing & Sales + Big Data
TO DELIVER AN ANSWER
100 milliseconds
COUNT OF ADS
100,000 per SECOND
http://www.dataxu.com/
ADVERTISING
PLATFORM
Clickstream, Behavior
Retail + Big Data
CAPTURE
1,000 tweets per SECONDS
INCREASE OF DATA
+10 TB per DAY
http://www.walmart.com/
WAL-MART ONLINE
MARKETING
Social Media
Health Care + Big Data
INCREASE OF DATA EACH MONTH
+10 TB
PATIENTS INVOLVED
10,000
https://cghub.ucsc.edu/index.html/
CANCER GENOMICS
HUB
DNA and RNA data
Science + Big Data
SEVEN TELESCOPES CAPTURE
2 MB per SECOND
IN NEXT 10-15 YEARS ALL
TELESCOPES WILL RECEIVE
30 TB per SECOND
http://www.skatelescope.org/
THE CATALOG OF
UNIVERSE
Data from Telescope
ORACLE TECHNOLOGIES
PART III
Oracle NoSQL
Hadoop Distributed File
System (HDFS)
Oracle NoSQL Database
File System Database
Parallel scanning Indexed storage
No inherent structure Simple data structure
High volume writes
High volume random reads
and writes
Batch Oriented Real-Time
Big Data Storage Choices
Oracle NoSQL
• RDBMS
– High value, high density,
complex data
– Complex data relationships
– Schema-centric
– Designed to scale up & out
– Lots of general purpose
features/functionality
 High overhead ($ per
operation)
• NoSQL architectures
– Low value, low density, simple
data
– Very simple relationships
– Schema-free, unstructured or
semi-structured data
– Distributed storage and
processing
– Stripped down, special
purpose data store
 Lower overhead ($ per
operation)
Oracle NoSQL
Simple Data Model
Small, distributed footprint
Highly scalable, available
Transparent load
balancing
Integrates with Oracle
Stack
Application
Storage Nodes
Datacenter B
Storage Nodes
Datacenter A
NoSQL Database
Driver
Application
NoSQL Database
Driver
A Distributed, Scalable Key-Value Database
Oracle NoSQL
Key-value pairs
• Simple data model – key-value pair (major+minor-key paradigm)
• Simple operations – read/insert/update/delete, RMW support
• Scope of transaction – records within a major key, single API call
• Unordered scan of all data (non-transactional)
userid
addresssubscriptions
email idphone #expiration date
Major key:
Sub key:
Value:
Strings
Byte Array 
Oracle NoSQL
On Line Display Advertising
Oracle NoSQL
Getting Started with Oracle NoSQL DB
1. Download from OTN:
www.oracle.com/technetwork/products/nosqldb/
downloads/index.html
2. Review Quick Start & Getting Started
Guide
3. Review Programmatic API Guide
4. Start writing Java code
What is R?
• R is an Open Source language and
environment for statistical computing
and graphics
http://www.R-project.org/
• Started in 1994 as an Alternative to
SAS, SPSS & Other proprietary
Statistical Environments
• The R environment
– R is an integrated suite of software facilities for data
manipulation, calculation and graphical display
• Around 2 million R users worldwide
– Widely taught in Universities
– Many Corporate Analysts know and use R
• Thousands of open sources R
packages to enhance productivity such
as:
– Bioinformatics
– Spatial Statistics
– Financial Market Analysis
Why statisticians/data analysts use
R?
R environment is ..
• Powerful
• Extensible
• Graphical
• Extensive statistics
• OOTB functionality with
many ‘knobs’ but
smart defaults
• Ease of installation and use
• Free
Limitations of R
• R is a client and server bundled together as 1 executable
– Single user tool, like Excel
– Single-threaded
– Cannot leverage multi-CPU capacity without use of special
packages and coding
• R requires data to be loaded into memory first
– Loading data may not be a limitation given RAM available on
laptops/desktops
– R’s call by value semantics means that as data flows into functions,
for each function invocation, a complete copy of the data is made
– As a result you can quickly run into memory limits
Oracle R Connector for Hadoop
• Provides transparent access to Hadoop Cluster, which
consists of MapReduce and HDFS-resident data
• R users not required to learn new language or interface to
work with Hadoop
• R users can execute jobs on a Hadoop cluster without
requiring knowledge of Hadoop internals, Hadoop CLI, or
IT infrastructure
• Ability to leverage open source contributed R packages to
work on HDFS-resident data
Oracle R Enterprise
• Provides familiar R environment to operate on database-
resident data
• Overloads base R functions for scalable execution in
Oracle Database
– Automatically generates SQL from R and submits query to
database
– Leverages table parallelism where applicable
• Enables embedded execution of R scripts at Oracle
Database server
– Provides database-controlled data-parallel execution framework
– Enables leveraging CRAN open source R packages
• Enables integration of structured results and graphics with
OBIEE dashboards and BI Publisher documents
Oracle R Links
• Blog: https://blogs.oracle.com/R/
• Forum: https://forums.oracle.com/forums/forum.jspa?forumID=1397
• Oracle R Distribution:
http://www.oracle.com/technetwork/indexes/downloads/r-distribution-1532464.html
• ROracle:
http://cran.r-project.org/web/packages/ROracle
• Oracle R Enterprise:
http://www.oracle.com/technetwork/database/options/advanced-analytics/r-enterprise
• Oracle R Connector for Hadoop:
http://www.oracle.com/us/products/database/big-data-connectors/overview
Other Oracle Big Data Products
Oracle Endeca Information Discovery
http://www.oracle.com/us/solutions/business-analytics/business-
intelligence/endeca/overview/index.html
Oracle Data Integrator Application Adapter for Hadoop
http://www.oracle.com/us/products/middleware/data-
integration/hadoop/overview/index.html
Oracle Loader for Hadoop
http://www.oracle.com/technetwork/bdc/hadoop-loader/learnmore/index.html
The End
The best way to predict the future is to
create it!
- Peter F. Drucker

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ORACLE BIG DATA & ANALYTICS TECHNOLOGIES FOR KIEV EVENT

  • 1. BIG DATA & ORACLE TECHNOLOGIES KIEV OCT 2013 PRACTIC CONSULTING Alliance of Professional IT & Management Consultants HTTP://PRACTIC-CONSULTING.COM
  • 2. Agenda • ABOUT BIG DATAWHAT • INDUSTRY EXAMPLES OF BIG DATAWHEN • ORACLE NO SQL • ORACLE R • ORACLE ENDECA HOW
  • 3. WHAT IS BIG DATA? PART I
  • 4. What Is Big Data? Big Data – is data that becomes large enough that it cannot be processed using conventional methods Big Data – is the new generation of data warehousing and business analysis systems 010101101010100101010101010101010010101010100101010101001010101010010101010101010100101 010100101010101010101001010101010010101010101010010101001010101001010101001010101001010 101010101001010101010100101010100101010100101010100101010101001010101001010101001010101 010010101010100101010010101001010101001010101001010100101010010101010010101010010101010 010101010010101001010101010101010101010101010010101010010101010010101010010101010010101 010010101010010101010010101010010101010010101010010101010010100101010100101010100101010
  • 5. A Wider Variety of Data Internet Data  Clickstream  Social media  Social media stream  Web site logs Research Data  Experiments  Observations  Surveys  Marketplace data Healthcare Data  Treatment data  Telehealth  National Electronic Health Records  Procedures Image Data  Image  Video  Satellite image  Surveillance Device Data  RF Devices  Sensors  EDI  Telemetry
  • 6. Why Is Big Data Important? Big Data - Just another buzzword or powerful business & science enabler? SQL Analytics • Count • Mean • OLAP Descriptive Analytics • Univariate distribution • Central tendency • Dispersion Data Mining • Association rules • Clustering • Feature extraction Predictive Analytics • Classification • Regression • Forecasting • Spatial • Machine Learning • Text Analytics Simulation • Monte Carlo • Agent-based modeling • Discrete event modeling Optimizatio n • Linear Optimization • Non-Linear Optimization Business Intelligence Advanced Analytics
  • 8. Marketing & Sales + Big Data TO DELIVER AN ANSWER 100 milliseconds COUNT OF ADS 100,000 per SECOND http://www.dataxu.com/ ADVERTISING PLATFORM Clickstream, Behavior
  • 9. Retail + Big Data CAPTURE 1,000 tweets per SECONDS INCREASE OF DATA +10 TB per DAY http://www.walmart.com/ WAL-MART ONLINE MARKETING Social Media
  • 10. Health Care + Big Data INCREASE OF DATA EACH MONTH +10 TB PATIENTS INVOLVED 10,000 https://cghub.ucsc.edu/index.html/ CANCER GENOMICS HUB DNA and RNA data
  • 11. Science + Big Data SEVEN TELESCOPES CAPTURE 2 MB per SECOND IN NEXT 10-15 YEARS ALL TELESCOPES WILL RECEIVE 30 TB per SECOND http://www.skatelescope.org/ THE CATALOG OF UNIVERSE Data from Telescope
  • 13. Oracle NoSQL Hadoop Distributed File System (HDFS) Oracle NoSQL Database File System Database Parallel scanning Indexed storage No inherent structure Simple data structure High volume writes High volume random reads and writes Batch Oriented Real-Time Big Data Storage Choices
  • 14. Oracle NoSQL • RDBMS – High value, high density, complex data – Complex data relationships – Schema-centric – Designed to scale up & out – Lots of general purpose features/functionality  High overhead ($ per operation) • NoSQL architectures – Low value, low density, simple data – Very simple relationships – Schema-free, unstructured or semi-structured data – Distributed storage and processing – Stripped down, special purpose data store  Lower overhead ($ per operation)
  • 15. Oracle NoSQL Simple Data Model Small, distributed footprint Highly scalable, available Transparent load balancing Integrates with Oracle Stack Application Storage Nodes Datacenter B Storage Nodes Datacenter A NoSQL Database Driver Application NoSQL Database Driver A Distributed, Scalable Key-Value Database
  • 16. Oracle NoSQL Key-value pairs • Simple data model – key-value pair (major+minor-key paradigm) • Simple operations – read/insert/update/delete, RMW support • Scope of transaction – records within a major key, single API call • Unordered scan of all data (non-transactional) userid addresssubscriptions email idphone #expiration date Major key: Sub key: Value: Strings Byte Array 
  • 17. Oracle NoSQL On Line Display Advertising
  • 18. Oracle NoSQL Getting Started with Oracle NoSQL DB 1. Download from OTN: www.oracle.com/technetwork/products/nosqldb/ downloads/index.html 2. Review Quick Start & Getting Started Guide 3. Review Programmatic API Guide 4. Start writing Java code
  • 19. What is R? • R is an Open Source language and environment for statistical computing and graphics http://www.R-project.org/ • Started in 1994 as an Alternative to SAS, SPSS & Other proprietary Statistical Environments • The R environment – R is an integrated suite of software facilities for data manipulation, calculation and graphical display • Around 2 million R users worldwide – Widely taught in Universities – Many Corporate Analysts know and use R • Thousands of open sources R packages to enhance productivity such as: – Bioinformatics – Spatial Statistics – Financial Market Analysis
  • 20. Why statisticians/data analysts use R? R environment is .. • Powerful • Extensible • Graphical • Extensive statistics • OOTB functionality with many ‘knobs’ but smart defaults • Ease of installation and use • Free
  • 21. Limitations of R • R is a client and server bundled together as 1 executable – Single user tool, like Excel – Single-threaded – Cannot leverage multi-CPU capacity without use of special packages and coding • R requires data to be loaded into memory first – Loading data may not be a limitation given RAM available on laptops/desktops – R’s call by value semantics means that as data flows into functions, for each function invocation, a complete copy of the data is made – As a result you can quickly run into memory limits
  • 22. Oracle R Connector for Hadoop • Provides transparent access to Hadoop Cluster, which consists of MapReduce and HDFS-resident data • R users not required to learn new language or interface to work with Hadoop • R users can execute jobs on a Hadoop cluster without requiring knowledge of Hadoop internals, Hadoop CLI, or IT infrastructure • Ability to leverage open source contributed R packages to work on HDFS-resident data
  • 23. Oracle R Enterprise • Provides familiar R environment to operate on database- resident data • Overloads base R functions for scalable execution in Oracle Database – Automatically generates SQL from R and submits query to database – Leverages table parallelism where applicable • Enables embedded execution of R scripts at Oracle Database server – Provides database-controlled data-parallel execution framework – Enables leveraging CRAN open source R packages • Enables integration of structured results and graphics with OBIEE dashboards and BI Publisher documents
  • 24. Oracle R Links • Blog: https://blogs.oracle.com/R/ • Forum: https://forums.oracle.com/forums/forum.jspa?forumID=1397 • Oracle R Distribution: http://www.oracle.com/technetwork/indexes/downloads/r-distribution-1532464.html • ROracle: http://cran.r-project.org/web/packages/ROracle • Oracle R Enterprise: http://www.oracle.com/technetwork/database/options/advanced-analytics/r-enterprise • Oracle R Connector for Hadoop: http://www.oracle.com/us/products/database/big-data-connectors/overview
  • 25. Other Oracle Big Data Products Oracle Endeca Information Discovery http://www.oracle.com/us/solutions/business-analytics/business- intelligence/endeca/overview/index.html Oracle Data Integrator Application Adapter for Hadoop http://www.oracle.com/us/products/middleware/data- integration/hadoop/overview/index.html Oracle Loader for Hadoop http://www.oracle.com/technetwork/bdc/hadoop-loader/learnmore/index.html
  • 26. The End The best way to predict the future is to create it! - Peter F. Drucker

Notas do Editor

  1. http://www.slideshare.net/cloudera/20100806-cloudera-10-hadoopable-problems-webinar-4931616
  2. http://www.youtube.com/watch?v=sANatTx87r4