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.

Friday Aug 07, 2015

Oracle Advanced Analytics Oracle University (OU) Classes in Cambridge, MA. September 28-Oct. 1, 2015

Oracle University has rescheduled their 2 day back to back Oracle Advanced Analytics OU Classes in Cambridge, MA.   Please help spread the word. 

Oracle Advanced Analytics combo-course (ODM + ORE) training

This is great opportunity for big data analytics customers and partners to learn hands on about using Oracle Advanced Analytics.  Vlamis, authorized OU instructor(s), will be teaching the OAA/ODM & OAA/ORE courses again and have been a great and knowledgeable OAA training and implementation partner. The courses are also during the week of Predictive Analytics World in Boston (Oracle will be exhibiting and speaking) so perhaps a good time for customers to come to Boston, perhaps use some OU credits, learn some new skills and focus on Oracle’s predictive analytics. 

Anyone (customers and Oracle Employees) can register through us at or via their normal OU connections. They should be able to utilize OU training credits for either course.  Oracle Employees should register through the Employee Self Service from Self Service Applications

Please forward to any appropriate Oracle Advanced Analytics customers and partners.  Thanks!


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)

Wednesday Jul 15, 2015

Call for Abstracts at BIWA Summit'16 - The Oracle Big Data + Analytics User Conference

Please email with any questions regarding the submission process.

What Successes Can You Share?

We want to hear your story. Submit your proposal today for the Oracle BIWA Summit 2016.

Proposals will be accepted through Monday evening, November 2, 2015, at midnight, EST. Don’t wait, though—we’re accepting submissions on a rolling basis, so that selected sessions can be published early on our online agenda.

To submit your abstract, click here, select a track, fill out the form.

Please note:

  • Presentations must be noncommercial.
  • Sales promotions for products or services disguised as proposals will be eliminated. 
  • Speakers whose abstracts are accepted will be expected to submit (at a later date) a PowerPoint presentation slide set. 
  • Accompanying technical and use case papers are encouraged, but not required.

Speakers whose abstracts are accepted will be given a complimentary registration to the conference. (Any additional co-presenters must register for the event separately and provide appropriate registration fees. It is up to the co-presenters’ discretion which presenter to designate for the complimentary registration.) 

This Year’s Tracks

Proposals can be submitted for the following tracks: 

More About the Conference

The Oracle BIWA Summit 2016 is organized and managed by the Oracle BIWA SIG, the Oracle Spatial SIG, and the Oracle Northern California User Group. The event attracts top BI, data warehousing, analytics, Spatial, IoT and Big Data experts.

The three-day event includes keynotes from industry experts, educational sessions, hands-on labs, and networking events.

Hot topics include: 

  • Database, data warehouse and cloud, Big Data architecture
  • Deep dives and hands-on labs on existing Oracle BI, data warehouse, and analytics products
  • Updates on the latest Oracle products and technologies (e.g. Big Data Discovery, Oracle Visual Analyzer, Oracle Big Data SQL)
  • Novel and interesting use cases on everything – Spatial, Graph, Text, Data Mining, IoT, ETL, Security, Cloud
  • Working with Big Data (e.g., Hadoop, "Internet of Things,” SQL, R, Sentiment Analysis)
  • Oracle Business Intelligence (OBIEE), Oracle Big Data Discovery, Oracle Spatial, and Oracle Advanced Analytics—Better Together

Hope to see you at BIWA'16 in January, 2016!


Wednesday May 08, 2013

Oracle Advanced Analytics and Data Mining at the Movies on YouTube - Updated August 3, 2015

Updated August 3, 2015

Periodically, I've recorded a demonstration and/or presentation on Oracle Advanced Analytics and Data Mining and have posted them on YouTube.

Here are links to some of more recent YouTube postings--sort of an Oracle Advanced Analytics and Data Mining at the Movies experience.

  1. New Big Data Analyics using Oracle Advanced Analytics12c and Big Data SQL  - Watch on YouTube
  2. New - Oracle Academy Webcast:  Ask the Oracle Experts Big Data Analytics with Oracle Advanced Analytics - Watch YouTube
  3. Oracle Data Miner and Oracle R Enterprise Integration via SQL Query node - Watch Demo
  4. Oracle Data Miner 4.0 (SQL Developer 4.0 Extension) New Features - Watch Demo
  5. Oracle Business Intelligence Enterprise Edition (OBIEE) SampleAppls Demo featuring integration with Oracle Advanced Analytics/Data Mining
  6. Oracle Big Data Analytics Demo mining remote sensor data from HVACs for better customer service 
  7. In-Database Data Mining for Retail Market Basket Analysis Using Oracle Advanced Analytics
  8. In-Database Data Mining Using Oracle Advanced Analytics for Classification using Insurance Use Case
  9. Fraud and Anomaly Detection using Oracle Advanced Analytics Part 1 Concepts
  10. Fraud and Anomaly Detection using Oracle Advanced Analytics Part 2 Demo
  11. Overview Presentation and Demonstration of Oracle Advanced Analytics Database Option

So.... grab your popcorn and a comfortable chair.  Hope you enjoy!


Oracle Advanced Analytics at the Movies

Wednesday Feb 08, 2012

Oracle Announces Availability of Oracle Advanced Analytics for Big Data

Oracle Announces Availability of Oracle Advanced Analytics for Big Data

Oracle Integrates R Statistical Programming Language into Oracle Database 11g

REDWOOD SHORES, Calif. - February 8, 2012

News Facts

  • Oracle today announced the availability of     Oracle Advanced Analytics, a new option for Oracle Database 11g that bundles Oracle R Enterprise together with Oracle Data Mining.
  • Oracle R Enterprise delivers enterprise class performance for users of the R statistical programming language, increasing the scale of data that can be analyzed by orders of magnitude using Oracle Database 11g.
  • R has attracted over two million users since its introduction in 1995, and Oracle R Enterprise dramatically advances capability for R users. Their existing R development skills, tools, and scripts can now also run transparently, and scale against data stored in Oracle Database 11g.
  • Customer testing of Oracle R Enterprise for Big Data analytics on Oracle Exadata has shown up to 100x increase in performance in comparison to their current environment.
  • Oracle Data Mining, now part of Oracle Advanced Analytics, helps enable customers to easily build and deploy predictive analytic applications that help deliver new insights into business performance. Oracle Advanced Analytics, in conjunction with Oracle Big Data Appliance, Oracle Exadata Database Machine and Oracle Exalytics In-Memory Machine, delivers the industry’s most integrated and comprehensive platform for Big Data analytics.

Comprehensive In-Database Platform for Advanced Analytics

  • Oracle Advanced Analytics brings analytic algorithms to data stored in Oracle Database 11g and Oracle Exadata as opposed to the traditional approach of extracting data to laptops or specialized servers.
  • With Oracle Advanced Analytics, customers have a comprehensive platform for real-time analytic applications that deliver insight into key business subjects such as churn prediction, product recommendations, and fraud alerting.
  • By providing direct and controlled access to data stored in Oracle Database 11g, customers can accelerate data analyst productivity while maintaining data security throughout the enterprise.
  • Powered by decades of Oracle Database innovation, Oracle R Enterprise helps enable analysts to run a variety of sophisticated numerical techniques on billion row data sets in a matter of seconds making iterative, speed of thought, and high-quality numerical analysis on Big Data practical.
  • Oracle R Enterprise drastically reduces the time to deploy models by eliminating the need to translate the models to other languages before they can be deployed in production.
  • Oracle R Enterprise integrates the extensive set of Oracle Database data mining algorithms, analytics, and access to Oracle OLAP cubes into the R language for transparent use by R users.
  • Oracle Data Mining provides an extensive set of in-database data mining algorithms that solve a wide range of business problems. These predictive models can be deployed in Oracle Database 11g and use Oracle Exadata Smart Scan to rapidly score huge volumes of data.
  • The tight integration between R, Oracle Database 11g, and Hadoop enables R users to write one R script that can run in three different environments: a laptop running open source R, Hadoop running with Oracle Big Data Connectors, and Oracle Database 11g.
  • Oracle provides single vendor support for the entire Big Data platform spanning the hardware stack, operating system, open source R, Oracle R Enterprise and Oracle Database 11g. To enable easy enterprise-wide Big Data analysis, results from Oracle Advanced Analytics can be viewed from Oracle Business Intelligence Foundation Suite and Oracle Exalytics In-Memory Machine.

Supporting Quotes

  • “Oracle is committed to meeting the challenges of Big Data analytics. By building upon the analytical depth of Oracle SQL, Oracle Data Mining and the R environment, Oracle is delivering a scalable and secure Big Data platform to help our customers solve the toughest analytics problems,” said Andrew Mendelsohn, senior vice president, Oracle Server Technologies.
  • “We work with leading edge customers who rely on us to deliver better BI from their Oracle Databases. The new Oracle R Enterprise functionality allows us to perform deep analytics on Big Data stored in Oracle Databases. By leveraging R and its library of open source contributed CRAN packages combined with the power and scalability of Oracle Database 11g, we can now do that,” said Mark Rittman, co-founder, Rittman Mead.

Supporting Resources

About Oracle

Oracle engineers hardware and software to work together in the cloud and in your data center. For more information about Oracle (NASDAQ: ORCL), visit


Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners.

Contact Info

Eloy Ontiveros

Joan Levy
Blanc & Otus for Oracle


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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