By Charlie Berger-Oracle on Oct 08, 2014
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. :-(
- Julia Minkowski - Risk Manager, Fiserv, Inc.
- Miguel Barrera - Director, Risk Analytics, fiserv
- Charles Berger - Senior Director, Product Management, Data Mining and Advanced Analytics, Oracle
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]
- Marcos Arancibia Coddou - Product Manager, Oracle Advanced Analytics, Oracle
- Mark Hornick - Director, Advanced Analytics, Oracle
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.
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.
- Pirama Arumuga nainar - Senior Software Engineer, Oracle
- Ekine Akuiyibo - Software Engineer, Oracle
- Debabrata Sarkar - Senior Engineering Manager, Oracle
Traditional 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.
- Roel Hartman - Director, Logica
- Brendan Tierney - Consultant, DIT & Oralytics.com (Author, Predictive Analytics using Oracle Data Miner book)
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 sentiment dashboard.
Transforming Customer 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!