Friday Sep 25, 2015

Oracle Advanced Analytics at Oracle Open World 2015

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 Highlights

Big Data Analytics with Oracle Advanced Analytics12c and Big Data SQL &
Fiserv Case Study: Fraud Detection in Online Payments [CON8743]

Tuesday, 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 Strategy

· Julia Minkowski, Risk Analytics Manager

Oracle 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.  
Conference Session

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.

Real 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

Customer Panel: Big Data and Data Warehousing [CON8741]

Wednesday, Oct 28, 4:15 p.m. | Moscone South—301

· Craig Fryar, Head of Wargaming Business Intelligence,

· 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.  Conference Session

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

Organizations 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.  Conference Session

Building Predictive Models for Identifying and Preventing Tax Fraud [CON3294]

Wednesday, 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

According 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.  Conference Session

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.

Sunday Jul 26, 2015

Big Data Analytics with Oracle Advanced Analytics: Making Big Data and Analytics Simple white paper

Big Data Analytics with Oracle Advanced Analytics:

Making Big Data and Analytics Simple

Oracle White Paper  |  July 2014 

Executive Summary:  Big Data Analytics with Oracle Advanced Analytics

(Click HERE to read entire Oracle white paper)   (Click HERE to watch YouTube video)

The era of “big data” and the “cloud” are driving companies to change.  Just to keep pace, they must learn new skills and implement new practices that leverage those new data sources and technologies.  Increasing customer expectations from sharing their digital exhaust with corporations in exchange for improved customer interactions and greater perceived value are pushing companies forward.  Big data and analytics offer the promise to satisfy these new requirements.  Cloud, competition, big data analytics and next-generation “predictive” applications are driving companies towards achieving new goals of delivering improved “actionable insights” and better outcomes.  Traditional BI & Analytics approaches don’t deliver these detailed predictive insights and simply can’t satisfy the emerging customer expectations in this new world order created by big data and the cloud.

Unfortunately, with big data, as the data grows and expands in the three V’s; velocity, volume and variety (data types), new problems emerge.  Data volumes grow and data becomes unmanageable and immovable.  Scalability, security, and information latency become new issues.  Dealing with unstructured data, sensor data and spatial data all introduce new data type complexities.  

Traditional advanced analytics has several information technology inherent weak points: data extracts and data movement, data duplication resulting in no single-source of truth, data security exposures, separate and many times, depending on the skills of the data analysts/scientists involved, multiple analytical tools (commercial and open source) and languages (SAS, R, SQL, Python, SPSS, etc.).  Problems become particularly egregious during a deployment phase when the worlds of data analysis and information management collide.   

Traditional data analysis typically starts with a representative sample or subset of the data that is exported to separate analytical servers and tools (SAS, R, Python, SPSS, etc.) that have been especially designed for statisticians and data scientists to analyze data.  The analytics they perform range from simple descriptive statistical analysis to advanced, predictive and prescriptive analytics.  If a data scientist builds a predictive model that is determined to be useful and valuable, then IT needs to be involved to figure out deployment and enterprise deployment and application integration issues become the next big challenge. The predictive model(s)—and all its associated data preparation and transformation steps—have to be somehow translated to SQL and recreated inside the database in order to apply the models and make predictions on the larger datasets maintained inside the data warehouse.  This model translation phase introduces tedious, time consuming and expensive manual coding steps from the original statistical language (SAS, R, and Python) into SQL.  DBAs and IT must somehow “productionize” these separate statistical models inside the database and/or data warehouse for distribution throughout the enterprise.  Some vendors will charge for specialized products and options for just for predictive model deployment.  This is where many advanced analytics projects fail.  Add Hadoop, sensor data, tweets, and expanding big data reservoirs and the entire “data to actionable insights” process becomes more challenging.  

Not with Oracle.  Oracle delivers a big data and analytics platform that eliminates the traditional extract, move, load, analyze, export, move load paradigm.  With Oracle Database 12c and the Oracle Advanced Analytics Option, big data management and big data analytics are designed into the data management platform from the beginning.  Oracle’s multiple decades of R&D investment in developing the industry’s leading data management platform, Oracle SQL, Big Data SQL, Oracle Exadata, Oracle Big Data Appliance and integration with open source R are seamlessly combined and integrated into a single platform—the Oracle Database.  

Oracle’s vision is a big data and analytic platform for the era of big data and cloud to:

  • Make big data and analytics simple (for any data size, on any computer infrastructure and any variety of data, in any combination) and

  • Make big data and analytics deployment simple (as a service, as a platform, as an application)

Oracle Advanced Analytics offers a wide library of powerful in-database algorithms and integration with open source R that together can solve a wide variety of business problems and can be accessed via SQL, R or GUI.  Oracle Advanced Analytics, an option to the Oracle Database Enterprise Edition 12c, extends the database into an enterprise-wide analytical platform for data-driven problems such as churn prediction, customer segmentation, fraud and anomaly detection, identifying cross-sell and up-sell opportunities, market basket analysis, and text mining and sentiment analysis.  Oracle Advanced Analytics empowers data analyst, data scientists and business analysts to more extract knowledge, discover new insights and make informed predictions—working directly with large data volumes in the Oracle Database.   

Data analysts/scientists have choice and flexibility in how they interact with Oracle Advanced Analytics.  Oracle Data Miner is an Oracle SQL Developer extension designed for data analysts that provides an easy to use “drag and drop” workflow GUI to the Oracle Advanced Analytics SQL data mining functions (Oracle Data Mining).  Oracle SQL Developer is a free integrated development environment that simplifies the development and management of Oracle Database in both traditional and Cloud deployments. When Oracle Data Miner users are satisfied with their analytical methodologies, they can share their workflows with other analysts and/or generate SQL scripts to hand to their DBAs to accelerate model deployment.  Oracle Data Miner also provides a PL/SQL API for workflow scheduling and automation.  

R programmers and data scientists can use the familiar open source R statistical programming language console, RStudio or any IDE to work directly with data inside the database and leverage Oracle Advanced Analytics’ R integration with the database (Oracle R Enterprise).  Oracle Advanced Analytics’ Oracle R Enterprise provides transparent SQL to R translation to equivalent SQL and Oracle Data Mining functions for in-database performance, parallelism, and scalability—this making R ready for the enterprise.  

Application developers, using the ODM SQL data mining functions and ORE R integration can build completely automated predictive analytic solutions that leverage the strengths of the database and the flexibly of R to integrate Oracle Advanced Analytics analytical solutions into BI dashboards and enterprise applications.

By integrating big data management and big data analytics into the same powerful Oracle Database 12c data management platform, Oracle eliminates data movement, reduces total cost of ownership and delivers the fastest way to deliver enterprise-wide predictive analytics solutions and applications.  

(Click HERE to read entire Oracle white paper)

Friday Jul 24, 2015

2015 BIWA SIG Virtual Conference - Two Days of "Live" Talks by Experts - FREE

2015 BIWA SIG Virtual Conference

July 30-31, 2015 9:00 a.m. - 1:00 p.m. CDT

Join us for two full days where you will hear about the latest Business Intelligence trends. 

Day One:

  • 9:00 a.m. - 10:00 a.m.: What’s new in Oracle EPM and BI Infrastructure - Eric Helmer, ADI Strategies

Hyperion EPM abd BI Fusion edition is a dramatic change under the covers. Corporations must consider more globalapproaches to infrastructure to maintain availability and performance while reducing footprint and cost. Technologies such as Exalytics, Oracle virtualization, cloud computing, software as a service, etc and open source operating systems (Linux) are more commonplace. Join Oracle Are Director Eric Helmer as he covers what’s new, what’s supported, and what options you have when implementing your EPM/BI project.

  • 10:00 a.m. - 11:00 a.m.Italian Ministry of Labor & Social Policy -- A Journey to Digital Government - Nicola Sandoli, ICONSULTING

The Italian Ministry of Labor and Social Policy (MLPS) is a branch of the Italian government responsible for all labormatters, including employment policies, promotions, worker protection, and social security. In its evolution towards a digital government, MLPS is streamlining and simplifying its administrative processes. MLPS has embarked on a data-driven journey to redefine business models and interactions with citizens – and optimize and transform government services. MLPS is focusing on four areas: - Information delivery: transitioning its data warehouse platform from reporting to centralizing and certifying data - Business Intelligence: monitoring activities, web publishing, and analyzing socio–political impact - Web analytics and semantic intelligence: interacting more efficiently with citizens - Job-hunting online guidance services: real time answers to young people looking for jobs MLPS is using a wide range of Oracle technologies to manage large amounts of diverse data, and apply advanced analytics, including - Oracle Exalytics for daily updates of 5TB of data - Oracle Spatial and Graph and MapViewer 11g for location intelligence capabilities - Oracle Business Intelligence for desktop and mobile reporting - Oracle Endeca Information Discovery for web analytics, data discovery, and data analysis using social and semantic intelligence - Oracle Real-Time Decisions - Oracle Service-Oriented Architecture Suite: central point for accessing and managing information made available through the Ministry web portal Cliclavoro Learn more about MLPS and its innovative platform that is delivering better information and services to their constituents.

  • 11:00 a.m. - 12:00 p.m.Exadata:  Elastic Configurations and IaaS – Private Cloud - Amit Kanda, Oracle

Customers are faced with challenges in their business, which include taking real time data driven decisions and  reducing costs.  Exadata’s extreme performance combined with Database In-Memory answer the real time data driven decisions. Elastic configurations and an updated subscription model (IaaS – Private Cloud) for Exadata  hardware and software accompanied the launch of Exadata X5–2.  This presentation will describe these updates and how customers can start small with Exadata and grow Exadata with their business – making it easier to reach business objectives.

  • 12:00 p.m. - 1:00 p.m.The State of Internet of Things (IoT) - Shyam Varan Nath, GE

The Internet of Things or IoT is poised to have a tremendous amount of impact around us. This session will look at  the industry landscape of IoT. The different flavors of IoT will be discussed with use cases from the consumer,  commercial and industrial sectors. Learn about the edge and cloud computing platforms to power the IoT solutions.  Finally, walk-thru of use-cases that show how machine/sensor data is being monetized through analytics. Such use  cases will span Aviation and other industries.

Day Two:

  • 9:00 a.m. - 10:00 a.m.: Big Data Analytics with Oracle Advanced Analytics 12c and Big Data SQL - Charlie Berger, Oracle

Oracle Advanced Analytics 12c, delivers parallelized in-database implementations of data mining algorithms andintegration 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 OAA models using SQL data mining functions and R. Oracle extends the Database to an analytical platform that mines more data and more data types, eliminates data movement and preserves security to automatically detect patterns and anticipate customer behavior and deliver actionable insights. Oracle Big Data SQL adds new big data sources and ORAAH provides algorithms that run on Hadoop. Come learn what’s new, best practices, and hear customer examples.

  • 10:00 a.m. - 11:00 a.m.: Graph Data Management and Analytics for Big DataBill Beauregard, Oracle & Zhe Wu, Oracle

The newest Oracle big data product, Oracle Big Data Spatial and Graph, offers a set of spatial analytic services, and a graph database with rich graph analytics that support big data workloads on Apache Hadoop and NoSQL technologies. Oracle is applying over a decade of expertise with spatial and graph analytic technologies to big data architectures. Graphs are an important data model for big data systems. Property graphs can be used for discovery, for instance, to discover underlying communities and influencers within a social graph, relationships and connections in cyber security networks, and to generate recommendations based on interests, profiles, and past behaviors. Oracle Big Data Spatial and Graph provides optimized storage, search and querying in Oracle NoSQL Database and Apache HBase for distributed property graphs. It offers 35 built-in, in-memory, parallel property graph analytic functions. We will discuss use cases, features, architecture, and show a demo. Learn how developers and data scientists can manage their most challenging graph data processing in a single enterprise-class Big Data platform.

  • 11:00 a.m. - 12:00 p.m.Why Oracle Database In-Memory?  Use Cases and Overview - Andy Rivenes, Oracle

Oracle recently announced the availability of the Oracle Database In-Memory option, a memory-optimized database technology that transparently adds real-time analytics to applications. Because the In-Memory option is 100% compatible with existing Oracle Database applications, it’s easy to integrate it into your environment and to begin reaping the benefits. But how do you get started with it? What do you need to know to take full advantage of this new functionality? This session will give an overview of what Oracle Database In-Memory is and then discuss some use cases to highlight how it can be used.

| Register Here |

Wednesday Apr 22, 2015

OpenWorld 2015 Call for Proposals Extended to Wed, May 6th, 11:59 p.m

OpenWorld 2015 Call for Proposals Extended to Wed, May 6th, 11:59 p.m Submit your Oracle Advanced Analytics stories now

If you’re an Oracle technology expert, conference attendees want to hear it straight from you. So don’t wait—proposals must be submitted by April 29.

Wanted: Outstanding Oracle Experts

The Oracle OpenWorld 2015 Call for Proposals is now open. Attendees at the conference are eager to hear from experts on Oracle business and technology. They’re looking for insights and improvements they can put to use in their own jobs: exciting innovations, strategies to modernize their business, different or easier ways to implement, unique use cases, lessons learned, the best of best practices.

If you’ve got something special to share with other Oracle users and technologists, they want to hear from you, and so do we. Submit your proposal now for this opportunity to present at Oracle OpenWorld, the most important Oracle technology and business conference of the year.

We recommend you take the time to review the General Information, Submission Information, Content Program Policies, and Tips and Guidelines pages before you begin. We look forward to your submissions.

Submit Your Proposal

By submitting a session for consideration, you authorize Oracle to promote, publish, display, and disseminate the content submitted to Oracle, including your name and likeness, for use associated with the Oracle OpenWorld and JavaOne San Francisco 2015 conferences. Press, analysts, bloggers and social media users may be in attendance at OpenWorld or JavaOne sessions.

General Information

  • Conference location: San Francisco, California, USA
  • Dates: Sunday, October 25 to Thursday, October 29, 2015
  • Website: Oracle OpenWorld

Key Dates for 2015

Deliverables Due Dates
Call for Proposals—Open Wednesday, March 25
Call for Proposals—Closed Wednesday, April 29, 11:59 p.m. PDT
Notifications for accepted and declined submissions sent Mid-June

Contact us

  • For questions regarding the Call for Proposals, send an e-mail to
  • For technical questions about the submission tool or issues with submitting your proposal, send an e-mail to
  • Oracle employee submitters should contact the appropriate Oracle track leads before submitting. To view a list of track leads, click here.

Wednesday Oct 08, 2014

2014 was a very good year for Oracle Advanced Analytics at Oracle Open World 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.  :-(

Big Data and Predictive Analytics: Fiserv Data Mining Case Study [CON8631]

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.

Developing Relevant Dining Visits with Oracle Advanced Analytics at Olive Garden [CON2898]

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.

Extending the Power of In-Database Analytics with Oracle Big Data Appliance [CON2452]

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.

Market Basket Analysis at Dunkin’ Brands [CON6545]

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.

Predictive Analytics with Oracle Data Mining [CON8596]

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 Is the Best Development Language for Big Data [CON7439]

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.

Advanced Predictive Analytics for Database Developers on Oracle [CON7977]

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.

What Are They Thinking? With Oracle Application Express and Oracle Data Miner [UGF2861]

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!


Wednesday Aug 06, 2014

New Book: Predictive Analytics Using Oracle Data Miner

Great New Book Now Available:  Predictive Analytics Using Oracle Data Miner, by Brendan Tierney, Oracle ACE Director

If you have an Oracle Database and want to leverage that data to discover new insights, make predictions and generate actionable insights, this book is a must read for you!  In Predictive Analytics Using Oracle Data Miner: Develop & Use Oracle Data Mining Models in Oracle Data Miner, SQL & PL/SQL, Brendan Tierney, Oracle ACE Director and data mining expert, guides the user through the basic concepts of data mining and offers step by step instructions for solving data-driven problems using SQL Developer’s Oracle Data Mining extension.  Brendan takes it full circle by showing the reader how to deploy advanced analytical methodologies and predictive models immediately into enterprise-wide production environments using the in-database SQL and PL/SQL functionality.  

Definitely a must read for any Oracle data professional!

See Predictive Analytics Using Oracle Data Miner, by Brendan Tierney on  

Tuesday May 06, 2014

Oracle Data Miner 4.0/SQLDEV 4.0 New Features - Watch Demo!

Oracle Data Miner 4.0 New Features 

Oracle Data Miner/SQLDEV 4.0 (for Oracle Database 11g and 12c)

  • New Graph node (box, scatter, bar, histograms)
  • SQL Query node + integration of R scripts
  • Automatic SQL script generation for deployment

Oracle Advanced Analytics 12c New SQL data mining algorithms/enhancements features exposed in Oracle Data Miner 4.0

  • Expectation Maximization Clustering algorithm
  • PCA & Singular Vector Decomposition algorithms
  • Decision Trees can also now mine unstructured data
  • Improved/automated Text Mining, Prediction Details and other algorithm improvements
  • SQL Predictive Queries—automatic build, apply within simple yet powerful SQL query

Tuesday Nov 12, 2013

Oracle Big Data Learning Library

Click on LEARN BY PRODUCT to view all learning resources.

Oracle Big Data Essentials

Attend this Oracle University Course!

Using Oracle NoSQL Database

Attend this Oracle University class!

Oracle and Big Data on OTN

See the latest resource on OTN.

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Friday Jun 08, 2012

New Oracle Advanced Analytics presentation

I recently updated my presentation on Oracle's new Advanced Analytics Option which bundles Oracle Data Mining with Oracle R Enterprise for maximum depth and breadth of data mining, statistics and advanced analytic functions from Oracle.  See New Oracle Advanced Analytics presentation.  

Tuesday May 29, 2012

Fraud and Anomaly Detection using Oracle Data Mining YouTube-like Video

I've created and recorded another YouTube-like presentation and "live" demos of Oracle Advanced Analytics Option, this time focusing on Fraud and Anomaly Detection using Oracle Data Mining.  [Note:  It is a large MP4 file that will open and play in place.  The sound quality is weak so you may need to turn up the volume.]

Data is your most valuable asset. It represents the entire history of your organization and its interactions with your customers.  Predictive analytics leverages data to discover patterns, relationships and to help you even make informed predictions.   Oracle Data Mining (ODM) automatically discovers relationships hidden in data.  Predictive models and insights discovered with ODM address business problems such as:  predicting customer behavior, detecting fraud, analyzing market baskets, profiling and loyalty.  Oracle Data Mining, part of the Oracle Advanced Analytics (OAA) Option to the Oracle Database EE, embeds 12 high performance data mining algorithms in the SQL kernel of the Oracle Database. This eliminates data movement, delivers scalability and maintains security. 

But, how do you find these very important needles or possibly fraudulent transactions and huge haystacks of data? Oracle Data Mining’s 1 Class Support Vector Machine algorithm is specifically designed to identify rare or anomalous records.  Oracle Data Mining's 1-Class SVM anomaly detection algorithm trains on what it believes to be considered “normal” records, build a descriptive and predictive model which can then be used to flags records that, on a multi-dimensional basis, appear to not fit in--or be different.  Combined with clustering techniques to sort transactions into more homogeneous sub-populations for more focused anomaly detection analysis and Oracle Business Intelligence, Enterprise Applications and/or real-time environments to "deploy" fraud detection, Oracle Data Mining delivers a powerful advanced analytical platform for solving important problems.  With OAA/ODM you can find suspicious expense report submissions, flag non-compliant tax submissions, fight fraud in healthcare claims and save huge amounts of money in fraudulent claims  and abuse.  

This presentation and several brief demos will show Oracle Data Mining's fraud and anomaly detection capabilities.  

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Thursday May 10, 2012

Oracle Data Mining Virtual Classes Scheduled

Two Oracle Data Mining Virtual Classes are now scheduled.  Register for a course in 2 easy steps.

Step 1: Select your Live Virtual Class options


Live Virtual Class
Course ID: D76362GC10
Course Title: Oracle Database 11g: Data Mining Techniques
Duration: 2 Days
Price: US$ 1,300 Dollars

Step 2: Select the date and location of your Live Virtual Class

Please select a location below then click on the Add to Cart button


Location  Duration Class Date Class Start Time Class End Time Course Materials Instruction Language Seats Audience Employees
Online 2 Days 09-Aug-2012 04:00 AM EDT 12:00 PM EDT English English Available Public Employees
Online 2 Days 18-Oct-2012 04:00 AM EDT 12:00 PM EDT English English Available Public Employees

100% Student Satisfaction: Oracle's 100% Student Satisfaction program applies to those publicly scheduled and publicly available Oracle University Instructor Led Training classes that are identified as part of the 100% Student Satisfaction program on the website at the time the class is purchased. Oracle will permit unsatisfied students to retake the class, subject to terms and conditions. Customers are not entitled to a refund. For more information and additional terms, conditions and restrictions that apply, click here

Wednesday Apr 04, 2012

Recorded YouTube-like presentation and "live" demos of Oracle Advanced Analytics/Oracle Data Mining

Ever want to just sit and watch a YouTube-like presentation and "live" demos of Oracle Advanced Analytics/Oracle Data Mining?  Then click here! (plays large MP4 file in a browser)

This 1+ hour long session focuses primarily on the Oracle Data Mining component of the Oracle Advanced Analytics Option and is tied to the Oracle SQL Developer Days virtual and onsite events.   I cover:

  • Big Data + Big Data Analytics
  • Competing on analytics & value proposition
  • What is data mining?
  • Typical use cases
  • Oracle Data Mining high performance in-database SQL based data mining functions
  • Exadata "smart scan" scoring
  • Oracle Data Miner GUI (an Extension that ships with SQL Developer)
  • Oracle Business Intelligence EE + Oracle Data Mining results/predictions in dashboards
  • Applications "powered by Oracle Data Mining for factory installed predictive analytics methodologies
  • Oracle R Enterprise

Please contact should you have any questions.  Hope you enjoy! 

Charlie Berger, Sr. Director of Product Management, Oracle Data Mining & Advanced Analytics, Oracle Corporation

Friday Mar 23, 2012

NEW 2-Day Instructor Led Course on Oracle Data Mining Now Available!

A NEW 2-Day Instructor Led Course on Oracle Data Mining has been developed for customers and anyone wanting to learn more about data mining, predictive analytics and knowledge discovery inside the Oracle Database.  To register interest in attending the class, click here and submit your preferred format.

Course Objectives:

  • Explain basic data mining concepts and describe the benefits of predictive analysis
  • Understand primary data mining tasks, and describe the key steps of a data mining process
  • Use the Oracle Data Miner to build,evaluate, and apply multiple data mining models
  • Use Oracle Data Mining's predictions and insights to address many kinds of business problems, including: Predict individual behavior, Predict values, Find co-occurring events
  • Learn how to deploy data mining results for real-time access by end-users

Five reasons why you should attend this 2 day Oracle Data Mining Oracle University course. With Oracle Data Mining, a component of the Oracle Advanced Analytics Option, you will learn to gain insight and foresight to:

  • Go beyond simple BI and dashboards about the past. This course will teach you about "data mining" and "predictive analytics", analytical techniques that can provide huge competitive advantage
  • Take advantage of your data and investment in Oracle technology
  • Leverage all the data in your data warehouse, customer data, service data, sales data, customer comments and other unstructured data, point of sale (POS) data, to build and deploy predictive models throughout the enterprise.
  • Learn how to explore and understand your data and find patterns and relationships that were previously hidden
  • Focus on solving strategic challenges to the business, for example, targeting "best customers" with the right offer, identifying product bundles, detecting anomalies and potential fraud, finding natural customer segments and gaining customer insight.

UDDATED for Oracle Database 12c & SQLDEV 4.0: Evaluating Oracle Data Mining Has Never Been Easier - Evaluation "Kit" Available

UPDATED (October 2015) for ORACLE DATABASE 12c & SQL DEVELOPER 4.1 (with ORACLE DATA MINER 4.1)  Extension

The Oracle Advanced Analytics Option turns the database into an enterprise-wide analytical platform that can quickly deliver enterprise-wide predictive analytics and actionable insights. Oracle Advanced Analytics empowers data and business analysts to extract knowledge, discover new insights and make predictions—working directly with large data volumes in the Oracle Database. Oracle Advanced Analytics, an Option of Oracle Database Enterprise Edition, offers a combination of powerful in-database algorithms and integration with open source R algorithms accessible via SQL and R languages and provides a range of GUI (Oracle Data Miner) and IDE (R client, RStudio, etc.) options targeting business users, data analysts, application developers and data scientists.

Now you can quickly and easily get set up to starting using Oracle Data Mining, the SQL API & GUI component of the Oracle Advanced Analytics Database Option for evaluation purposes. Just go to the Oracle Technology Network (OTN) and follow these simple steps.

Oracle Data Mining Evaluation "Kit" Instructions

Step 1: Download and Install the Oracle Database 12c

  • Anyone can download and install the Oracle Database for free for evaluation purposes. Read OTN web site for details.
  • Oracle Database 12c is the latest release and contains many new features.  See Oracle Advanced Analytics 12c Dcoumentation's New Features and this recent Oracle Data Mining Blog posting.  NOTE:  A major new feature of the 12c Oracle Database is multi-tenant and the ability to set up multiple Container databases.  However, to keep things simpler, UNCHECK the "create as Container database" option.  This makes your SQLDEV database connections simpler and then you can use the simpler case Oracle Data Miner tutorials.  If you create the Container database(s), your connection details get a bit more complicated.  
  • For  Oracle Database Release 11g, DB is the minimum, is better and naturally is best if you are a current customer and on active support.
  • Either 32-bit or 64-bit is fine. 4GB of RAM or more works fine for SQL Developer and the Oracle Data Miner GUI extension.
  • Downloading the database and then installing it should take just about an hour or so at most, depending on your network and computer.
  • For more instructions on setting up Oracle Data Mining see:
  • When you install the Oracle Database, the Oracle Data Mining Examples including sample data is available as part of the total Database installation.  See link.  

Step 2: Install SQL Developer 4.1 (the Oracle Data Miner GUI Extension installs automatically but additional post installation Set Up in required.  See Setting Up Oracle Data Miner )

Step 3: Follow the six (6) free step-by-step Oracle-by-Examples Tutorials:

That’s it!  Easy, fun and the fastest way to get started evaluating Oracle Advanced Analytics/Oracle Data Mining.  Enjoy!  


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Monday Sep 19, 2011

Building Predictive Analytical Applications using Oracle Data Mining recorded webcast

I did a Building Predictive Analytical Applications using Oracle Data Mining recorded webcast for IOUG earlier this week.  If this interests you, you can either watch the streaming presentation and demo hosted by the Independent Oracle User Group at in conjunction with the Oracle Business Intelligence, Wartehousing and Analytics Special Interest Group (BIWA SIG at or the download the 84 MB file by clicking on this link to the Building Predictive Analytical Applications using Oracle Data Mining.wmv file.   It included an overview of data mining, Oracle Data Mining, some demo slides, and then several example applications where we've factory-installed ODM predictive analytics methodologies into the Appls for self-learning and real-time deployment of ODM models. 

Example Predictive Analytics Applications (partial list)
  • Oracle Communications  & Retail Industry Models —factory installed data mining for specific industries
  • Oracle Spend Classification
  • Oracle Fusion Human Capital Management (HCM)  Predictive Workforce
  • Oracle Fusion Customer Relationship Management (CRM) Sales Prediction
  • Oracle Adaptive Access Manager real-time Security
  • Oracle Complex Event Processing integrated with ODM models
  • Predictive Incident Monitoring Service for Oracle Database customers

Pretty cool stuff if you or your customers are interested in analytics.  Here's the link to the ppt slides.    


Everything about Oracle Data Mining, a component of the Oracle Advanced Analytics Option - News, Technical Information, Opinions, Tips & Tricks. All in One Place


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