2014 was a very good year
for Oracle Advanced Analytics at Oracle Open World 2014. We had a number of
customer, partner and Oracle talks that focused on the Oracle Advanced Analytics Database Option. See
below with links to presentations. Check back later to OOW Sessions Content Catalog as not all presentations have been uploaded yet.
Moving data mining algorithms
to run as native data mining SQL functions eliminates data movement, automates
knowledge discovery, and accelerates the transformation of large-scale data to
actionable insights from days/weeks to minutes/hours. In this session, Fiserv,
a leading global provider of electronic commerce systems for the financial
services industry, shares best practices for turning in-database predictive
models into actionable policies and illustrates the use of Oracle Data Miner
for fraud prevention in online payments. Attendees will learn how businesses
that implement predictive analytics in their production processes significantly
improve profitability and maximize their ROI.
Olive Garden, traditionally
managing its 830 restaurants nationally, transitioned to a localized approach
with the help of predictive analytics. Using k-means clustering and logistic
classification algorithms, it divided its stores into five behavioral segments.
The analysis leveraged Oracle SQL Developer 4.0 and Oracle R Enterprise 1.3 to
evaluate 115 million transactions in just 5 percent the time required by the
company’s BI tool. While saving both time and money by making it possible to
develop the solution internally, this analysis has informed Olive Garden’s
latest remodel campaign and continues to uncover millions in profits by
optimizing pricing and menu assortment. This session illustrates how Oracle
Advanced Analytics solutions directly affect the bottom line.
A Perfect Storm: Oracle
Big Data Science for Enterprise R and SAS Users [CON8331]
With the advent of R and a
rich ecosystem of users and developers, a myriad of bloggers, and thousands of
packages with functionality ranging from social network analysis and spatial
data analysis to empirical finance and phylogenetics, use of R is on a steep
uptrend. With new R tools from Oracle, including Oracle R Enterprise, Oracle R
Distribution, and Oracle R Advanced Analytics for Hadoop, users can scale and
integrate R for their enterprise big data needs. Come to this session to learn
about Oracle’s R technologies and what data scientists from smart companies
around the world are doing with R.
The need for speed could not be greater—not speed of processing but time to market. The problem is driven by the long journey data takes before evolving into insight. Insight, however, is always relative to assumption. In fact, analytics is often seen as a battle between assumption and data. Assumptions can be classified into three types: related to distributions, ratios, and relations. In this session, you will see how the most-valuable business insights can come in the matter of hours, not months, when assumptions are challenged with data. This is made possible by the integration of Oracle Big Data Appliance, enabling transparent access to in-database analytics from the data warehouse and avoiding the traditional long journey of data to insight.
With almost 120 years of
franchising experience, Dunkin’ Brands owns two of the world’s most recognized,
beloved franchises: Dunkin’ Donuts and Baskin-Robbins. This session describes a
market basket analysis solution built from scratch on the Oracle Advanced
Analytics platform at Dunkin’ Brands. This solution enables Dunkin’ to look at
product affinity and a host of associated sales metrics with a view to
improving promotional effectiveness and cross-sell/up-sell to increase customer
loyalty. The presentation discusses the business value achieved and technical
challenges faced in scaling the solution to Dunkin’ Brands’ transaction
volumes, including engineered systems (Oracle Exadata) hardware and parallel
processing at the core of the implementation.
This session presents three
case studies related to predictive analytics with the Oracle Data Mining
feature of Oracle Advanced Analytics. Service contracts cancellation avoidance with
Oracle Data Mining is about predicting the contracts at risk of cancellation at
least nine months in advance. Predicting hardware opportunities that have a
high likelihood of being won means identifying such opportunities at least four
months in advance to provide visibility into suppliers of required materials.
Finally, predicting cloud customer churn involves identifying the customers
that are not as likely to renew subscriptions as others.
SQL has a long and storied
history. From the early 1980s till today, data processing has been dominated by
this language. It has changed and evolved greatly over time, gaining features
such as analytic windowing functions, model clauses, and row-pattern matching.
This session explores what's new in SQL and Oracle Database for exploiting big
data. You'll see how to use SQL to efficiently and effectively process data
that is not stored directly in Oracle Database.
applications use SQL queries to filter, aggregate, and summarize data. This is
called descriptive analytics. The next level is predictive analytics, where
hidden patterns are discovered to answer questions that give unique insights
that cannot be derived with descriptive analytics. Businesses are increasingly
using machine learning techniques to perform predictive analytics, which helps
them better understand past data, predict future trends, and enable better
decision-making. This session discusses how to use machine learning algorithms
such as regression, classification, and clustering to solve a few selected
business use cases.
Have you ever wanted to add
some data science to your Oracle Application Express applications? This session
shows you how you can combine predictive analytics from Oracle Data Miner into
your Oracle Application Express application to monitor sentiment analysis.
Using Oracle Data Miner features, you can build data mining models of your data
and apply them to your new data. The presentation uses Twitter feeds from conference
events to demonstrate how this data can be fed into your Oracle Application
Express application and how you can monitor sentiment with the native SQL and
PL/SQL functions of Oracle Data Miner. Oracle Application Express comes with
several graphical techniques, and the presentation uses them to create a
Experience with Big Data and Predictive Analytics [CON8148]
Delivering a high-quality
customer experience is essential for long-term profitability and customer
retention in the communications industry. Although service providers own a
wealth of customer data within their systems, the sheer volume and complexity
of the data structures inhibit their ability to extract the full value of the
information. To change this situation, service providers are increasingly
turning to a new generation of business intelligence tools. This session begins
by discussing the key market challenges for business analytics and continues by
exploring Oracle’s approach to meeting these challenges, including the use of
predictive analytics, big data, and social network analytics.
There are a few others where
Oracle Advanced Analytics is included e.g. Retail GBU, Big Data Strategy, etc.
but they are typically more broadly focused. If you search the Content
Catalog for “Advanced Analytics” etc. you can find other related
presentations that involve OAA.
Hope this helps. Enjoy!