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  • September 25, 2015

Oracle Advanced Analytics at Oracle Open World 2015

Charlie Berger
Sr. Dir. Product Management, Machine Learning, AI and Cognitive Analytics

While there are a lot
of OOW talks that include the work “analytics” or “big data”, this is my short
list of sessions, training and demos that primarily focus on Oracle Advanced Analytics.
Hope to see you there!


Oracle Advanced Analytics at OOW'15

Big Data
Analytics with Oracle Advanced Analytics12c and Big Data SQL &

Fiserv Case Study: Fraud Detection in Online Payments [CON8743]

Oct 27, 5:15 p.m. | Moscone South—307

· Charles Berger, Sr. Director of Product
Management, Advanced Analytics and Data Mining, Oracle

· Miguel M Barrera, Director of Risk Analytics and

· Julia Minkowski, Risk Analytics Manager

Advanced Analytics 12c delivers parallelized in-database
implementations of data mining algorithms and integration with R. Data analysts
use Oracle Data Miner GUI and R to build and evaluate predictive models and
leverage R packages and graphs. Application developers deploy Oracle Advanced
Analytics models using SQL data mining functions and R. Oracle extends Oracle
Database to an analytical platform that mines more data and data types,
eliminates data movement, and preserves security to automatically detect
patterns, anticipate customer behavior, and deliver actionable insights. Oracle
Big Data SQL adds new big data sources and Oracle R Advanced Analytics for
Hadoop provides algorithms that run on Hadoop. 

Fiserv manage risk for $30B+ in transfers, servicing 2,500+ US financial
institutions, including 27 of the top 30 banks and prevents $200M in fraud
losses every year.  When dealing with potential fraud, reaction needs to
be fast.  Fiserv describes their use of Oracle Advanced Analytics for
fraud prevention in online payments and shares their best practices and results
from turning predictive models into actionable intelligence and next generation
strategies for risk mitigation.  

OAA Demo Pod (#3581—Big Data Predictive Analytics with Oracle Advanced Analytics, R, and Oracle Big Data SQL   Moscone South

The Oracle Advanced Analytics database option embeds powerful data mining algorithms in Oracle Database’s SQL kernel and adds integration with R for solving big data problems such as predicting customer behavior, anticipating churn, detecting fraud, and performing market basket analysis. Data analysts work directly with database data, using the Oracle Data Miner workflow GUI (SQL Developer 4.1 ext.), SQL, or R languages and can extend Oracle Advanced Analytics’ functionally with R graphics and CRAN packages. Oracle Big Data SQL enables Oracle Advanced Analytics models to run on Oracle Big Data Appliance. Oracle R Advanced Analytics for Hadoop provides a powerful R interface over Hadoop and Spark with parallel-distributed predictive algorithms. Learn more in this demo.

Business Value from Big Data and Advanced Analytics [UGF4519]

Sunday, Oct
25, 3:30 p.m. | Moscone South—301

· Antony Heljula, Technical Director, Peak
Indicators Limited

· Brendan Tierney, Principal Consultant, Oralytics

Attend this
session to hear real case studies where big data and advanced analytics have
delivered significant return on investment to a variety of Oracle customers.
These solutions can pay for themselves within one year. Customer case studies
include predicting which employees are likely to leave within the next 12
months, predicting which sales outlets are likely to suffer from out-of-stock
products, predicting sales based on the weather forecast, and predicting which
students are likely to withdraw early from their courses. A live demonstration
illustrates the high-level process for implementing predictive business
intelligence (BI) and its best practices.  
User Group
Forum Session

Panel: Big Data and Data Warehousing [CON8741]

Oct 28, 4:15 p.m. | Moscone South—301

· Craig Fryar, Head of Wargaming Business
Intelligence, Wargaming.net

· Manuel Martin Marquez, Senior Research Fellow and
Data Scientist, Cern Organisation Européenne Pour La Recherche Nucléaire

· Jake Ruttenburg, Senior Manager, Digital
Analytics, Starbucks

· Chris Wones, Chief Enterprise Architect, 8451

· Reiner Zimmermann, Senior Director, DW & Big
Data Global Leaders Program, Oracle

In this
session, hear how customers around the world are solving cutting-edge
analytical business problems using Oracle Data Warehouse and big data
technology. Understand the benefits of using these technologies together, and
how software and hardware combined can save money and increase productivity.
Learn how these customers are using Oracle Big Data Appliance, Oracle Exadata,
Oracle Exalytics, Oracle Database In-Memory 12c, or Oracle Analytics to
drive their business, make the right decisions, and find hidden information.
The conversation is wide-ranging, with customer panelists from a variety of
industries discussing business benefits, technical architectures,
implementation of best practices, and future directions.  

End-to-End Analytics Across
Big Data and Data Warehouse for Data Monetization [CON3296]

Monday, Oct
26, 4:00 p.m. | Moscone West—2022

· Satya Bhamidipati, Senior Principal Advanced
Analytics Market Dev, Business Analytics Product Group, Oracle

· Gokula Mishra, VP, Big Data & Advanced
Analytics, Oracle

have used data warehouses to manage structured and operational data, which
provides business analysts with the ability to analyze key internal data and
spot trends. However, the explosion of newer data sources (big data) not only
challenges the role of the traditional data warehouse in analyzing data from
these diverse sources but also exposes limitations posed by traditional
software and hardware platforms. This newer data can be combined with the data
in the data warehouse and analyzed without creating another data silo and
creating a hybrid data analytics structure. This presentation discusses the
data and analytics platform architecture that enables this data monetization
and presents various industry use cases.  

Predictive Models for Identifying and Preventing Tax Fraud [CON3294]

Oct 28, 9:00 a.m. | Park Central—Concordia

· Brian Bequette, Managing Partner, TPS

· Satya Bhamidipati, Senior Principal Advanced
Analytics Market Dev, Business Analytics Product Group, Oracle

to a TIGTA Audit Report issued in February 2013, in 2012 alone, the IRS
identified almost 642,000 incidents of identity theft affecting tax
administration, a 38 percent increase since 2010. And this number continues to
increase. Tax Processing Systems (TPS) consultants have focused on fraud
detection and developed innovative solutions and proprietary algorithms for
detecting fraud. In 2012, TPS formed a partnership with Oracle and has adapted
its cloud-based methodologies and algorithms for use on the Oracle technology
stack. Together, TPS and Oracle have created an end-to-end fraud detection
solution that is effective, efficient, and accurate. This presentation focuses
on the technology and the algorithms they have developed to detect fraud.  

Oracle University Pre-OOW Course
Sunday, Oct. 25th

Using Data Mining Techniques for
Predictive Analysis Course, Sunday October 25th

This session teaches students the
basic concepts of data mining and how to leverage the predictive analytical
power of data mining with Oracle Database by using Oracle Data Miner 12c.
Students will learn how to explore the data graphically, build and evaluate
multiple data models, apply data mining models to new data, and deploy data
mining's predications and insights throughout the enterprise. All this can be
performed on the data in Oracle Database on a real-time basis by using Oracle
Data Miner SQL APIs. As the data, models, and results remain in Oracle
Database, data movement is eliminated, security is maximized, and information
latency is minimized.

See Oracle University at Oracle OpenWorld and Make the Most of Your Oracle OpenWorld and JavaOne
Experience with Preconference Training by Oracle Experts

When: Sunday, October 25, 2015, 9
a.m.-4 p.m., with a one-hour lunch break
Where: Golden Gate University, 536 Mission Street, San Francisco,
CA 94105 (three blocks from Moscone Center)
Cost: US$850 for a full day of training (cost includes light
refreshments and a boxed lunch)

Instructor: Ashwin Agarwal… Read full bio

Target Audience: Data scientists, application
developers, and data analysts

Course Objectives:

  • Understand the
    basic concepts and describe the primary terminology of data mining
  • Understand the
    steps associated with a data mining process
  • Use Oracle
    Data Miner 12c to perform data mining
  • Understand the
    options for deploying data mining predictive results

Course Topics:

  • Understanding
    the Data Mining Concepts
  • Understanding
    the Benefits of Predictive Analysis
  • Understanding
    Data Mining Tasks
  • Key Steps of a
    Data Mining Process (Includes Demo)
  • Using Oracle
    Data Miner to Build, Evaluate, and Apply Multiple Data Mining Models
    Includes Demo)
  • Using Data
    Mining Predictions and Insights to Address Various Business Problems
    (Includes Demo)
  • Predicting
    Individual Behavior (Includes Demo)
  • Predicting
    Values (Includes Demo)
  • Finding
    Co-Occurring Events (Includes Demo)
  • Detecting
    Anomalies (Includes Demo)
  • Learning How to Deploy Data
    Mining Results for Real-Time Access by End Users

Prerequisites: A working knowledge of the SQL language and Oracle
Database design and administration

Also, on the Big Data + Analytics related products OTN pages, there is a
“Must See” Program Guide.
Clicking on
the .pdf link
you’ll see the full list.

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