Download Oracle Advanced Analytics

Big Data és
Oracle Machine Learning,
az analitikus felhőben
Nagyobb, jobb, gyorsabb, több!
Fekete Zoltán
Platform, principal sales consultant
[email protected]
Copyright © 2017 Oracle and/or its affiliates. All rights reserved. |
Safe Harbor Statement
The following is intended to outline our general product direction. It is intended for
information purposes only, and may not be incorporated into any contract. It is not a
commitment to deliver any material, code, or functionality, and should not be relied upon
in making purchasing decisions. The development, release, and timing of any features or
functionality described for Oracle’s products remains at the sole discretion of Oracle.
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Mi irányítunk?
Sokszor halljuk, hallgass a megérzéseidre!
Nos, ez egyre komplexebb.
• „Légy szabad! Még mindig a szemed meg a füled
akarod használni. Ne számítgass, használd a tudat
alatti ösztöneidet.”
• „Bízz az Erőben, Luke!”
• „Csak az ösztöneidben bízz, Luke!”
– Egy új remény, Csillagok háborúja, George Lucas
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Mi irányítunk még mindig? Kinek a döntése?
https://www.scientificamerican.com/article/will-democracy-survive-big-data-and-artificial-intelligence/
• „Often the recommendations we are offered fit so well that the
resulting decisions feel as if they were our own, even though
they are actually not our decisions. In fact, we are being
remotely controlled ever more successfully in this manner. The
more is known about us, the less likely our choices are to be free
and not predetermined by others.”
• „The trend goes from programming computers z
to programming people.”
• „Search algorithms and recommendation systems
can be influenced.”
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Szingularitás 2047-re?
https://www.inverse.com/article/28386-singularity-2047
• „One of the chips in our shoes in the next 30 years will be
smarter than our brain. We will be less than our shoes. And we
are stepping on them.”
• „I think this super intelligence is going to be our partner. If we
misuse it, it’s a risk. If we use it in good spirits it will be our
partner for a better life.””
– Masayoshi Son, Softbank Robotics CEO
• Ray Kurzweil, Google, director of Engineering, futurológus:
singularity to occur around 2045, 2050-re egy számítógép olyan
intelligens lehet, mint az emberi agyak kombinációja
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Gartner's 2016 Hype Cycle for Emerging Technologies
http://www.gartner.com/newsroom/id/3412017
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
A teljes kép – Oracle Big Data + relációs megoldás
DATA RESERVOIR
DATA WAREHOUSE
Cloudera Hadoop
Oracle Big Data
Connectors
Oracle Big Data SQL
Oracle NoSQL
Oracle R Distribution, ORAA4H
Oracle Data
Integrator
Oracle Big Data Spatial and
Graph
Oracle
Database
Oracle
Database
Oracle Industry
In-Memory,
Multitenant
Models
Oracle Industry Models
Oracle Advanced Analytics
Oracle Advanced
Oracle Spatial
& Graph
Analytics
Oracle Spatial & Graph
Big Data Appliance
Apache
Flume
Oracle
GoldenGate
Oracle Data
Integrator
SOURCES
Oracle Event
Processing
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Exadata
Oracle
GoldenGate
Oracle Event
Processing
Oracle Database In-Memory Goals
Real Time Analytics
100x
Accelerate Mixed
Workload OLTP
No Changes to
Applications
Trivial to Implement
2x
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
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Az analitikus lekérdezések gyorsítása
Data Scans
Joins
In-Memory Aggregation
STATE = CA
CPU
Vector Register
SALES
HASH JOIN
CA
CA
CA
CA
• Speed of memory
• Scan and Filter only
the needed Columns
• Vector Instructions
Table A
Table B
•Convert Star Joins into 10X
Faster Column Scans
•Search large table for values
that match small table
•Create In-Memory
Report Outline that is
Populated during Fast Scan
•Runs Reports Instantly
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Adat architektúra: Big Data
Üzleti adat
•
•
•
•
Adat
folyamok
Szociális
háló/log
adat
Végrehajtás
Innováció
Enterprise
adatok
További
források
Alk./adat
szolgáltatás
API-k
Gyors adatok
Adat platform
Lake
Data Factory
Analitika
Warehouse
Adat laboratórium
Telematics
Industry Services
Internet of Things
Sentiment
BI/jelentés
Model First &
Analytics
dashboard
• Reporting-oriented
• Often enterprise wide
in scope, cross LoB
• “you know the
questions to ask”
Adat
felfedezés
Data First
Analytics
• Data Exploration
• Highly visual and/or
interactive
• “you don’t know the
questions to ask”
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Oracle Confidential
Minden felhasználó típushoz és tudáshoz
Üzleti adat
Adat
folyamok
Adatfolyam, gyors adat
Apache
Szociális
háló/log
adat
Enterprise
adatok
Végrehajtás
Innováció
További
források
Oracle
NoSQL
Adat platform
Apache
Oracle Database
& Big Data SQL
Reservoir
Factory & Governance
Warehouse
Oracle
Data Integration
Kutató laboratórium
Oracle
R
R elemző
SQL
Developer
Oracle
Big Data
Discovery
Adat
szolgáltatás
API-k
Oracle
CAF & OEP
•
•
•
•
Telematics
Industry Services
Internet of Things
Sentiment
Analitika
Reports
Model First&
Analytics
Dashboards
Oracle
Business
Intelligence
• Reporting-oriented
• Often enterprise wide
in scope, cross LoB
• “you know the
questions to ask”
Oracle
Big Data
Discovery
Data First
Discovery
Analytics
Adattudós
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
• Data Exploration
• Highly visual and/or
interactive
• “you don’t know the
questions to ask”
Oracle Confidential
Vég-felh.
Elemző
1
Big Data Appliance – fő tervezési/mérnöki szempontok
Működtetési / install egyszerűség, HA
Nagy teljesítmény, minden adatot, BD SQL
Nyílt analitikai platform
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
1
Big Data Appliance X6-2
azonnal bevethető teljes környezet
6 szervertől tetszőlegesen bővíthető
Sun Oracle X6-2L Servers, szerverenként:
• 2 * 22 Core, 256 GB - 768 GB mem. , 96 TB Disk
Telepített szoftver (BDA 4.7,2016. dec.):
• Oracle Linux, UEK 4 on OL 6
• Oracle Big Data SQL 3.1*
• Cloudera Distribution of Apache Hadoop CDH 5.9.0 – EDH Edition
• Cloudera Manager 5.9.0
• Oracle R Distribution
• Oracle NoSQL Database CE 4.2.9
– JDK 8u111, MySQL 5.6.34
* Oracle Big Data SQL is separately licensed
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
1
Oracle Cloud Platform for Big Data
COLLECT
MANAGE
EXPERIMENT
DataFlow ML CS
Big Data Preparation CS
IoT CS
GoldenGate CS
Event Hub CS
Data Integration CS
Big Data CS
NoSQL Database CS
Big Data CS CE
Big Data SQL CS
NoSQL Database CS
Exadata CS
Big Data Discovery CS
Stream Analytics CS*
R on Hadoop*
Spatial and Graph*
ANALYZE
& ACT
Data Visualization CS
Business Intelligence CS
Spatial and Graph*
Advanced Analytics*
R on Hadoop*
* Bundled with other Cloud Services
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
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1
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1
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1
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
1
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1
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
2
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
2
Oracle Management Cloud
egyesített intelligens platform, együttműködő szolgáltatások
Application
Performance Monitoring
Monitor real and synthetic users
and application performance
Infrastructure
Monitoring
Monitor database and cross-tier
infrastructure performance
Security Monitoring and
Analytics
Orchestration
New in 2017
New in 2017
Execute automated remediation
and other tasks at cloud scale
Detect, investigate, and remediate
full range of security threats
Configuration &
Compliance
IT
Analytics
New in 2017
Log
Analytics
Analyze business and IT data using
pre-built apps and explorers
Manage configuration and change
against industry and own standards
Aggregate, index, and explore the
entire enterprise log estate
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
2
Management Cloud - Machine Learning támogatással
heterogén forrásokkal
END USER
EXPERIENCE
APPLICATION
MIDDLE TIER
DATA TIER
VIRTUALIZATION
TIER
INFRASTRUCTURE
TIER
VM
VM
CONTAINER
CONTAINER
01100100 01100001 01110100 01100001 0110010001100001 01110100 0100 01100001
01100100 01100001 01110100 01100001 0110010001100001 01011 01110100
110000101100100
01100001 01110100 110000101100100 01100001 01110100 01100001
Global Threat Feeds
CASB
0110010001100001
01110100
110000101100100
0100111
01100001
01110100
ANOMALY DETECTION
Identity
✔
110000101100100 01100001 01110100 01100001 011010 0110010001100001 01110100
Real Users
01100001
0110010001100001 01110100 01001 01100001 0110010001100001 01110100
Synthetic Users
01100001
0110010001100001 01001 01110100 01100001 0110010001100001 01110100
App metrics
CLUSTERING
01100001
01100001 0110010001100001
Transactions 0100101001 001 0110010001100001 01110100 ✔
01110100
010011 01100001 0110010001100001 01110100 01100001 01100100 01100001
Server metrics
01001
01110100 01100001 0110010001100001 01110100 01100001 01100100 0100 01100001
Diagnostics
Logs
01110100
01100001 0110010001100001 01110100 01000100
110000101100100
✔ 0100CORRELATION
01100001
Host metrics 01110100 110000101100100 01100001 01110100 01100001 0110010001100001
VM metrics 110000101100100 01100001 010001 01110100 110000101100100 01100001
01110100
Container metrics
01110100 01100001 01000100 010011 0110010001100001 01110100 01100001
PREDICTION
✔
CMDB/Compliance
0110010001100001
01110100
01000 01110100 110000101100100 01100001 01110100
Unified Platform
Tickets
01100001
01000100 010011 0110010001100001 01110100 01100001 0110010001100001
Alerts
01110100
010011
Security Events
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
2
“Oracle is also working to integrate
cutting-edge technologies such as
machine learning into business
applications across industries.”
– Mark Hurd, CEO Oracle
2017. március 21., Oracle Industry Connect
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Confidential – Oracle
2
„Prediktív” enterprise alkalmazások
Oracle Advanced Analytics az Oracle alkalmazásokban, példák
• Oracle HCM Fusion
– Employee turnover and performance
prediction and “What if?” analysis
• Oracle CRM Fusion
– Prediction of sales opportunities,
what to sell, amount, timing, etc.
• Oracle Industry Data Models
– Communications Data Model churn
prediction, segmentation, profiling, etc.
– Retail Data Model loyalty and market
basket analysis
– Airline Data Model analysis frequent
flyers, loyalty, etc.
– Utilities Data Model customer churn,
cross-sell, loyalty, etc.
• Oracle Retail Insights Cloud Services
– Market Basket Analysis Insights
– Customer Insights & Clustering
• Oracle Customer Support
– Predictive Incident Monitoring (PIM)
• Oracle Spend Classification
– Real-time and batch flagging of
noncompliance and anomalies
in expense submissions
• Oracle FinServ Analytic Applications
– Customer Insight, Enterprise Risk Management,
Enterprise Performance, Financial Crime
and Compliance
• Oracle Adaptive Access Manager
– Real-time security and fraud analytics
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
What is Machine Learning, Data Mining & Predictive
Analytics?
Automatically sifting through large amounts of data to
create models that find previously hidden patterns,
discover valuable new insights and make predictions
•Identify most important factor (Attribute Importance)
•Predict customer behavior (Classification)
•Predict or estimate a value (Regression)
•Find profiles of targeted people or items (Decision Trees)
•Segment a population (Clustering)
•Find fraudulent or “rare events” (Anomaly Detection)
•Determine co-occurring items in a “baskets” (Associations)
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
A1 A2 A3 A4 A5 A6 A7
Oracle’s Advanced Analytics and Machine Learning Platform
Multiple interfaces across platforms — SQL, R, GUI, Dashboards, Apps
Information Producers
Users
R programmers
R Client
Platform
Data & Business Analysts
Business Analysts/Mgrs Domain End Users (HCM, CRM)
SQLDEV/
Oracle Data Miner
OBIEE/DV
Applications
Big Data SQL
Hadoop
HQL
Information Consumers
ORAAH
Parallel,
distributed
algorithms
Oracle Database Enterprise Edition
Oracle Advanced Analytics - Database Option
SQL Data Mining, ML & Analytic Functions + R Integration
for Scalable, Distributed, Parallel in-DB ML Execution
Oracle Cloud
Copyright © 2017, Oracle and/or its affiliates. All rights reserved. |
Oracle Database 12c
UK National Health Service
Combating Healthcare Fraud
Objectives
 Use new insight to help identify cost savings and meet goals
 Identify and prevent healthcare fraud and benefit eligibility
errors to save costs
 Leverage existing data to transform business and productivity
 “Oracle Advanced Analytics’ data mining capabilities and Oracle
Exalytics’ performance really impressed us. The overall solution is
very fast, and our investment very quickly provided value. We can
now do so much more with our data, resulting in significant
savings for the NHS as a whole”
– Nina Monckton, Head of Information Services,
NHS Business Services Authority
Solution
 Identified up to GBP100 million (US$156 million) potentially
Update: £300M confirmed fraud
£400+M additional potential identified
saved through benefit fraud and error reduction
 Used anomaly detection to uncover fraudulent activity where
some dentists split a single course of treatment into multiple
parts and presented claims for multiple treatments
Looking to Cloud now….
 Analyzed billions of records at one time to measure longerterm patient journeys and to analyze drug prescribing patterns
Oracle Exadata Database
to improve patient care
Machine
Oracle Advanced
Analytics
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Oracle Exalytics In-Memory
Machine
Oracle Endeca Information
Discovery
Oracle Business Intelligence EE
Oracle Advanced Analytics DB Option
In-Database Machine Learning Algorithms*—SQL &
Classification
• Decision Tree
• Logistic Regression (GLM)
• Naïve Bayes
• Support Vector Machine (SVM)
• Random Forest
Regression
• Multiple Regression (GLM)
• Support Vector Machine (SVM)
• Stepwise Linear Regression
• Linear Model
• Generalized Linear Model
• Multi-Layer Neural Networks
Anomaly Detection
• 1-Class Support Vector Machine
Advanced Analytics
& GUI Access
Clustering
Predictive Queries
• Hierarchical k-Means
• Orthogonal Partitioning Clustering
• Expectation-Maximization
Attribute Importance
• Minimum Description Length
• Unsupervised pair-wise KL div.
A1 A2 A3 A4 A5
A6 A7
Market Basket Analysis
• Apriori – Association Rules
Text Mining
• All OAA/ODM SQL ML support
• Explicit Semantic Analysis
• Clustering
• Regression
• Anomaly Detection
• Feature Extraction
Feature Extraction & Creation
• Nonnegative Matrix Factorization
• Principal Component Analysis
• Singular Value Decomposition
Time Series
• Single & Double Exp. Smoothing
Open Source R Algorithms
• Ability to run any R package
(9,000+)via Embedded R mode
+ Ability to Mine Unstructured, Structured & Transactional data
+ Partitioned Models
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Oracle R Advanced Analytics for Hadoop
AA Algorithms in a Hadoop Cluster: Map-Reduce and Spark (2.7)
Classification
GLM ORAAH
Logistic Regression ORAAH
Regression
MLP Neural Networks ORAAH
Ridge Regression
Decision Trees
Support Vector Machines
Gaussian Mixture Models
Clustering
K-Means
K-Means
Non-negative Matrix
Factorization
LASSO
Random Forests
Support Vector Machines
Feature Extraction
Collaborative Filtering
(LMF)
Attribute Importance
Random Forest
Linear Regression
Basic Statistics
Principal Components Analysis
Principal Components Analysis
Correlation/Covariance
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
LASSO
30
Oracle’s Advanced Analytics
Prediktív analitika, „kódot az adatokhoz”
Key Features
 Párhuzamos, skálázható, R integr.
 In-Database + Hadoop
 Elemzők, adattudósok, fejlesztők
 D&D workflow, R és SQL API
Data Miner GUI
 Adat menedzsment kiterjesztése
fejlett prediktív platformmá
 SQL generálás gombnyomásra,
azonnali beépítés alkalmazásba
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Advanced Analytics
You Can Think of Oracle Advanced Analytics Like This…
Traditional SQL
SQL Statistical Functions - SQL &
– “Human-driven” queries
– Domain expertise
– Any “rules” must be defined and
managed
SQL Queries
– SELECT
– DISTINCT
– Automated knowledge discovery, model
building and deployment
– Domain expertise to assemble the “right”
data to mine/analyze
+
Statistical SQL “Verbs”
– MEAN, STDEV
– MEDIAN
– AGGREGATE
– SUMMARY
– WHERE
– CORRELATE
– AND OR
– FIT
– GROUP BY
– COMPARE
– ORDER BY
– ANOVA
– RANK
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
FREE!
You Can Think of Oracle’s Advanced Analytics Like This…
Traditional SQL
Oracle Advanced Analytics - SQL &
– “Human-driven” queries
– Domain expertise
– Any “rules” must be defined and
managed
SQL Queries
– SELECT
– DISTINCT
– Automated knowledge discovery, model
building and deployment
– Domain expertise to assemble the “right”
data to mine/analyze
+
Analytical SQL “Verbs”
– PREDICT
– DETECT
– AGGREGATE
– CLUSTER
– WHERE
– CLASSIFY
– AND OR
– REGRESS
– GROUP BY
– PROFILE
– ORDER BY
– IDENTIFY FACTORS
– RANK
– ASSOCIATE
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Advanced Analytics
Masszívan párhuzamos SQL: DB, Hadoop és NoSQL
Big Data SQL + Advanced Analytics
Oracle Big Data Appliance
Oracle Database 12c
Data Analysts
SQL / R
JSON
Structured and Unstructured Data Reservoir
• JSON data
• HDFS / Hive
• NoSQL
• Spatial and Graph data
• Image and Video data
• Social Media
Store business-critical data in Oracle
• Customer data
• Transactional data
• Unstructured documents, comments
• Spatial and Graph data
• Image and Video data
• Social Media
Data analyzed via SQL / R / GUI
• R Clients
• SQL Clients
• Oracle Data Miner
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Oracle Advanced Analytics
Real-Time Scoring, Predictions and Recommendations
• On-the-fly, single record apply with new data (e.g. from call center)
Select prediction_probability(CLAS_DT_1_64, 'Yes'
USING 7800 as bank_funds, 125 as checking_amount, 20 as
credit_balance, 55 as age, 'Married' as marital_status,
250 as MONEY_MONTLY_OVERDRAWN, 1 as house_ownership)
from dual;
Social Media
Call Center
Likelihood to respond:
Get AdviceBranch
Office
R
Mobile
Web
Email
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
R: Transparency via function overloading
Advanced Analytics
Invoke in-database aggregation function
> aggdata <- aggregate(ONTIME_S$DEST,
+
by = list(ONTIME_S$DEST),
+
FUN = length)
Oracle Advanced Analytics
ORE Client Packages
Transparency Layer
> class(aggdata)
[1] "ore.frame"
attr(,"package")
[1] "OREbase"
> head(aggdata)
Group.1
x
1 ABE
237
2 ABI
34
3 ABQ
1357
4 ABY
10
5 ACK
3
6 ACT
33
Oracle SQL
select DEST, count(*)
from ONTIME_S
group by DEST
Oracle Database
In-db
Stats
ONTIME_S
Database Server
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
ORAAH: Machine Learning in Spark against HDFS data
Invoke ORAAH custom parallel distributed GLM Model using Spark Caching
Oracle Distribution of R version 3.1.1 (--) -- "Sock it to Me"
> Connects to Spark
> spark.connect("yarn-client",memory="24g")
> # Attaches the HDFS file for use within R
> ont1bi <- hdfs.attach("/user/oracle/ontime_1bi")
Oracle R Advanced Analytics
for Hadoop Client Packages
YARN: Apache
Spark Job
1
Spark-Based Machine
Learning algorithms
module
> # Formula definition: Cancelled flights (0 or 1) based on other attributes
> form_oraah_glm2 <- CANCELLED ~ DISTANCE + ORIGIN + DEST + F(YEAR) + F(MONTH) +
+ F(DAYOFMONTH) + F(DAYOFWEEK)
5
> system.time(m_spark_glm <- orch.glm2(formula=form_oraah_glm2, ont1bi))
ORCH GLM: processed 6 factor variables, 25.806 sec
ORCH GLM: created model matrix, 100128 partitions, 32.871 sec
ORCH GLM: iter 1, deviance 1.38433414089348300E+09, elapsed time 9.582 sec
ORCH GLM: iter 2, deviance 3.39315388583931150E+08, elapsed time 9.213 sec
ORCH GLM: iter 3, deviance 2.06855738812683250E+08, elapsed time 9.218 sec
ORCH GLM: iter 4, deviance 1.75868100359263200E+08, elapsed time 9.104 sec
ORCH GLM: iter 5, deviance 1.70023181759611580E+08, elapsed time 9.132 sec
ORCH GLM: iter 6, deviance 1.69476890425481350E+08, elapsed time 9.124 sec
ORCH GLM: iter 7, deviance 1.69467586045954760E+08, elapsed time 9.077 sec
ORCH GLM: iter 8, deviance 1.69467574351380850E+08, elapsed time 9.164 sec
user system elapsed
84.107 5.606 143.591
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
2
4
Custom Spark Java Algorithm
Custom
Spark Java
Algorithm
distributed
in-Memory
Computation
distributed in-Memory Computation
3
/user/oracle/ontime_s
Big Data Analytics using w Graph
Oracle Advanced Analytics/Machine Learning with Enhanced Graph & Spatial Data Sources
• Add new engineered
features
Transactional network
relationships data
– Percentage time spent in
zones
– Amount time/encounters
with persons of interest
• Better predictions
using available dataTransactional
– At risk customers
– Government approval
processes
– Medical claims
– IoT predictive analytics
geo-location data
summarized to %
time spent in
areas or number
of “hits” near a
location
Better data and “engineered
features”; better predictive
models and predictive insights
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
What is a “notebook”
• Web-based –
accessible by browser
• Enables interactive
data analytics
• Produces appealing
data-driven and
collaborative documents
• Integrates formatted notes
with your code
Copyright © 2017, Oracle and/or its affiliates. All rights reserved. |
Mesterséges intelligencia, AI – szervezetileg?
https://www.wsj.com/articles/how-artificial-intelligence-will-change-everything-1488856320?mod=e2fb
• „ a chief AI officer or a VP—to sort this out for them. Recruiting AI talent is
so difficult that having a centralized AI function would be the best way to
have consistent hiring and promotion and management standards for an AI
team. This team can then work cross-functionally ...”
– Andrew Ng, chief scientist, Baidu
• „I believe in the power of small, interdisciplinary teams that have support
high up in the corporation... It’s very important to match the speed of the
technology with the nimbleness of the teams. And having a centralized AI
guru at the top,... is unlikely to be as fast and effective as having a
decentralized organization with powerful teams, with real talent.”
– Neil Jacobstein, Singularity University
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Getting started: OAA Links and Resources
Oracle Advanced Analytics Overview:
 OAA presentation— Big Data Analytics with Oracle Advanced Analytics …or just watch Watch YouTube video
presentation and demo(s)
 Big Data Analytics with Oracle Advanced Analytics: Making Big Data and Analytics Simple white paper on OTN
 Oracle Internal OAA Product Management Wiki and Workspace
 Oracle Advanced Analytics Customer Successes
YouTube recorded OAA Presentations and Demos:
 Oracle Advanced Analytics and Data Mining at the YouTube Movies (6 + OAA “live” Demos on ODM’r 4.0 New
Features, Retail, Fraud, Loyalty, Overview, etc.)
Getting Started:






Link to OAA/Oracle Data Miner Workflow GUI Online (free) Tutorial Series on OTN
Link to OAA/Oracle R Enterprise (free) Tutorial Series on OTN
Link to Free Oracle Advanced Analytics "Test Drives" on Oracle Cloud via Vlamis Partner
Link to Getting Started w/ ODM blog entry
Link to New OAA/Oracle Data Mining 2-Day Instructor Led Oracle University course.
Oracle Data Mining Sample Code Examples
Additional Resources:





Oracle Advanced Analytics Option on OTN page
OAA/Oracle Data Mining on OTN page, ODM Documentation & ODM Blog
OAA/Oracle R Enterprise page on OTN page, ORE Documentation & ORE Blog
Oracle SQL based Basic Statistical functions on OTN
Oracle R Advanced Analytics for Hadoop (ORAAH) on OTN
 Business Intelligence, Warehousing & Analytics—BIWA Summit’17, Jan 31, Feb 1 & 2,
2017 at Oracle HQ Conference Center (w/ links to customer presentations)
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
Copyright © 2016, Oracle and/or its affiliates. All rights reserved. |
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