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!

cb

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 Amazon.com  



Sunday May 18, 2014

Oracle Data Miner and Oracle R Enterprise Integration - Watch Demo

Oracle Data Miner and Oracle R Enterprise Integration - Watch Demo

Oracle Advanced Analytics (Database EE) Option turns the database into an enterprise-wide analytical platform that can quickly deliver enterprise-wide predictive analytics and actionable insights.  Oracle Advanced Analytics is comprised of both the Oracle Data Mining SQL data mining functions, Oracle Data Miner, an extension to SQL Developer that exposes the data mining SQL functions for data analysts, and Oracle R Enterprise which integrates the R statistical programming language with SQL.  15 powerful in-database SQL data mining functions, the SQL Developer/Oracle Data Miner workflow GUI and the ability to integrate open source R within an analytical methodology, makes the Oracle Database + Oracle Advanced Analytics Option the ideal platform for building and deploying enterprise-wide predictive analytics applications/solutions.  

In Oracle Data Miner 4.0 we added a new SQL Query node to allow users to insert arbitrary SQL scripts within an ODMr analytical workflow. Additionally, the SQL Query node allows users to leverage registered R scripts to extend Oracle Data Miner's analytical capabilities.  For applications that are mostly OAA/Oracle Data Mining SQL data mining functions based but require additional analytical techniques found in the R community, this is an ideal method for integrating the power of in-database SQL analytical and data mining functions with the flexibility of open source R.  For applications that are built entirely using the R statistical programming language, it may be more practical to stay within the R console or RStudio environments, but for SQL-centric in-database predictive methodologies, this integration is just what might satisfy your needs.

Watch this Oracle Data Miner and Oracle R Enteprise Integration YouTube to see the demo. 

There is an excellent related Oracle Data Miner:  Integrate Oracle R Enterprise Algorithms into workflow using the SQL Query node (pdf, companion files) white paper on this topic that includes examples on the Oracle Technology Network in the Oracle Data Mining pages.  

Monday Jul 15, 2013

Oracle Data Miner GUI, part of SQL Developer 4.0 Early Adopter 1 is now available for download on OTN

The NEW Oracle Data Miner GUI, part of SQL Developer 4.0 Early Adopter 1 is now available for download on OTN.  See link to SQL Developer 4.0 EA1.   


The Oracle Data Miner 4.0 New Features are applicable to Oracle Database 11g Release 2 and Oracle Database Release 12c:  See Oracle Data Miner Extension to SQL Developer 4.0 Release Notes for EA1 for additional information  

· Workflow SQL Script Deployment

o Generates SQL scripts to support full deployment of workflow contents

· SQL Query Node

o Integrate SQL queries to transform data or provide a new data source

o Supports the running of R Language Scripts and viewing of R generated data and graphics


· Graph Node

o Generate Line, Scatter, Bar, Histogram and Box Plots



· Model Build Node Improvements

o Node level data usage specification applied to underlying models

o Node level text specifications to govern text transformations

o Displays heuristic rules responsible for excluding predictor columns

o Ability to control the amount of Classification and Regression test results generated

· View Data

o Ability to drill in to view custom objects and nested tables

These new Oracle Data Miner GUI capabilities expose Oracle Database 12c and Oracle Advanced Analytics/Data Mining Release 1 features:

· Predictive Query Nodes

o Predictive results without the need to build models using Analytical Queries

o Refined predictions based on data partitions

· Clustering Node New Algorithm

o Added Expectation Maximization algorithm

· Feature Extraction Node New Algorithms

o Added Singular Value Decomposition and Principal Component Analysis algorithms

· Text Mining Enhancements

o Text transformations integrated as part of Model's Automatic Data Preparation

o Ability to import Build Text node specifications into a Model Build node

· Prediction Result Explanations

o Scoring details that explain predictive result

· Generalized Linear Model New Algorithm Settings

o New algorithm settings provide feature selection and generation

See OAA on OTN pages http://www.oracle.com/technetwork/database/options/advanced-analytics/index.html for more information on Oracle Advanced Analytics.

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Wednesday May 08, 2013

Oracle Advanced Analytics and Data Mining at the Movies on YouTube - Updated June 15, 2015

Updated June 15, 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 - Oracle Academy Webcast:  Ask the Oracle Experts Big Data Analytics with Oracle Advanced Analytics - Watch YouTube
  2. Oracle Data Miner and Oracle R Enterprise Integration via SQL Query node - Watch Demo
  3. Oracle Data Miner 4.0 (SQL Developer 4.0 Extension) New Features - Watch Demo
  4. Oracle Business Intelligence Enterprise Edition (OBIEE) SampleAppls Demo featuring integration with Oracle Advanced Analytics/Data Mining
  5. Oracle Big Data Analytics Demo mining remote sensor data from HVACs for better customer service 
  6. In-Database Data Mining for Retail Market Basket Analysis Using Oracle Advanced Analytics
  7. In-Database Data Mining Using Oracle Advanced Analytics for Classification using Insurance Use Case
  8. Fraud and Anomaly Detection using Oracle Advanced Analytics Part 1 Concepts
  9. Fraud and Anomaly Detection using Oracle Advanced Analytics Part 2 Demo
  10. Overview Presentation and Demonstration of Oracle Advanced Analytics Database Option

 

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

Charlie 

Oracle Advanced Analytics at the Movies

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Thursday Mar 21, 2013

Recorded Webcast: Best Practices using Oracle Advanced Analytics with Oracle Exadata

Best Practices using Oracle Advanced Analytics with Oracle Exadata

 On Demand
Launch Presentation


Join us to learn how Oracle Advanced Analytics extends the Oracle database into a comprehensive advanced analytics platform through two major components, Oracle R Enterprise and Oracle Data Mining. Using these tools with Oracle Exadata Database Machine will allow organizations to perform at their peak and find real business value within their data.

You need to visit this Oracle Exadata Webcast Main page first and submit your registration information.  Then you’ll receive an email so you can view the Webcast.  This is external so you can share with anyone can download the presentation as well.  FYI.  Charlie

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Friday Mar 23, 2012

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

UPDATED (July 2014) for ORACLE DATABASE 12c & SQL DEVELOPER 4.0 (with ORACLE DATA MINER 4.0)  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 http://www.oracle.com/technetwork/database/enterprise-edition/downloads/index.html 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, 11.2.0.1.0 DB is the minimum, 11.2.0.2 is better and naturally 11.2.0.3 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: http://www.oracle.com/technetwork/database/options/odm/dataminerworkflow-168677.html
  • 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 4.0 (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:

  • Setting Up Oracle Data Miner 4.0   This tutorial covers the process of setting up Oracle Data Miner for use within Oracle SQL Developer 4.0.
  • Using Oracle Data Miner 4.0 This tutorial covers the use of Oracle Data Miner 4.0 to perform data mining against Oracle Database 12c. In this lesson, you examine and solve a data mining business problem by using the Oracle Data Miner graphical user interface (GUI). The Oracle Data Miner GUI is included as an extension of Oracle SQL Developer, version 4.0.
  • Using Feature Selection and Generation with GLM This tutorial covers the use of Oracle Data Miner 4.0 to leverage enhancements to the Oracle implementation of Generalized Liner Models (GLM) for Oracle Database 12c. These enhancements include support for Feature Selection and Generation.
  • Text Mining with an EM Clustering Model This tutorial covers the use of Oracle Data Miner 4.0 to leverage new text mining enhancements while applying a clustering model. In this lesson, you learn how to use the Expectation Maximization (EM) algorithm in a clustering model.
  • Using Predictive Queries With Oracle Data Miner 4.0 This tutorial covers the use of Predictive Queries against mining data by using Oracle Data Miner 4.0.
  • Using the SQL Query Node in a Data Miner Workflow This tutorial covers the use of the new SQL Query Node in an Oracle Data Miner 4.0 workflow.

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

Charlie

Note: There are also four (4) additional Oracle Data Miner 3.2 Tutorials that are similar that may be helpful to review.

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Thursday Jan 07, 2010

Welcome to Oracle Data Mining!

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