Tuesday Nov 12, 2013
Wednesday Sep 04, 2013
Oracle Data Miner (Extension of SQL Developer 4.0) Integrate Oracle R Enterprise Mining Algorithms into workflow using the SQL Query node
By chberger on Sep 04, 2013
I posted a new white paper authored by Denny Wong, Principal Member of Technical Staff, User Interfaces and Components, Oracle Data Mining Technologies. You can access the white paper here and the companion files here. Here is an excerpt:
Oracle Data Miner (Extension of SQL Developer 4.0)
Integrate Oracle R Enterprise Mining Algorithms into workflow using the SQL Query node
Oracle R Enterprise (ORE), a component of the Oracle Advanced Analytics Option, makes the open source R statistical programming language and environment ready for the enterprise and big data. Designed for problems involving large amounts of data, Oracle R Enterprise integrates R with the Oracle Database. R users can develop, refine and deploy R scripts that leverage the parallelism and scalability of the database to perform predictive analytics and data analysis.
Oracle Data Miner (ODMr) offers a comprehensive set of in-database algorithms for performing a variety of mining tasks, such as classification, regression, anomaly detection, feature extraction, clustering, and market basket analysis. One of the important capabilities of the new SQL Query node in Data Miner 4.0 is a simplified interface for integrating R scripts registered with the database. This provides the support necessary for R Developers to provide useful mining scripts for use by data analysts. This synergy provides many additional benefits as noted below.
· R developers can further extend ODMr mining capabilities by incorporating the extensive R mining algorithms from the open source CRAN packages or leveraging any user developed custom R algorithms via SQL interfaces provided by ORE.
· Since this SQL Query node can be part of a workflow process, R scripts can leverage functionalities provided by other workflow nodes which can simplify the overall effort of integrating R capabilities within the database.
· R mining capabilities can be included in the workflow deployment scripts produced by the new sql script generation feature. So the ability of deploy R functionality within the context of an Data Miner workflow is easily accomplished.
· Data and processing are secured and controlled by the Oracle Database. This alleviates a lot of risk that are incurred by other providers, when users have to export data out of the database in order to perform advanced analytics.
Oracle Advanced Analytics saves analysts, developers, database administrators and management the headache of trying to integrate R and database analytics. Instead, users can quickly gain the benefit of new R analytics and spend their time and effort on developing business solutions instead of building homegrown analytical platforms.
Monday Jul 15, 2013
Oracle Data Miner GUI, part of SQL Developer 4.0 Early Adopter 1 is now available for download on OTN
By chberger on Jul 15, 2013
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
· 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
Wednesday May 08, 2013
By chberger on May 08, 2013
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.
- New - Oracle Business Intelligence Enterprise Edition (OBIEE) SampleAppls Demo featuring integration with Oracle Advanced Analytics/Data Mining
- New - Oracle Big Data Analytics Demo mining remote sensor data from HVACs for better customer service
- In-Database Data Mining for Retail Market Basket Analysis Using Oracle Advanced Analytics
- In-Database Data Mining Using Oracle Advanced Analytics for Classification using Insurance Use Case
- Fraud and Anomaly Detection using Oracle Advanced Anlaytics Part 1 Concepts
- Fraud and Anomaly Detection using Oracle Advanced Analytics Part 2 Demo
- Overview Presentation and Demonstration of Oracle Advanced Analytics Database Option
So.... grab your popcorn and a comfortable chair. Hope you enjoy!
Wednesday Mar 13, 2013
Tuesday Jan 01, 2013
By chberger on Jan 01, 2013
Turkcell İletişim Hizmetleri A.S. Successfully Combats Communications Fraud with Advanced In-Database Analytics
[Original link available on oracle.com http://www.oracle.com/us/corporate/customers/customersearch/turkcell-1-exadata-ss-1887967.html]
- Oracle Customer: Turkcell İletişim Hizmetleri A.Ş.
- Location: Istanbul, Turkey
- Industry: Communications
- Employees: 3,583
- Annual Revenue: Over $5 Billion
Turkcell İletişim Hizmetleri A.Ş. is a leading provider of mobile communications in Turkey with more than 34 million subscribers. Established in 1994, Turkcell created the first global system for a mobile communications (GSM) network in Turkey. It was the first Turkish company listed on the New York Stock Exchange.
Communications fraud, or the use of telecommunications products or services without intention to pay, is a major issue for the organization. The practice is fostered by prepaid card usage, which is growing rapidly. Anonymous network-branded prepaid cards are a tempting vehicle for money launderers, particularly since these cards can be used as cash vehicles—for example, to withdraw cash at ATMs. It is estimated that prepaid card fraud represents an average loss of US$5 per US$10,000 in transactions. For a communications company with billions of transactions, this could result in millions of dollars lost through fraud every year.
Consequently, Turkcell wanted to combat communications fraud and money laundering by introducing advanced analytical solutions to monitor key parameters of prepaid card usage and issue alerts or block fraudulent activity. This type of fraud prevention would require extremely fast analysis of the company’s one petabyte of uncompressed customer data to identify patterns and relationships, build predictive models, and apply those models to even larger data volumes to make accurate fraud predictions.
To achieve this, Turkcell deployed Oracle Exadata Database Machine X2-2 HC Full Rack, so that data analysts can build predictive antifraud models inside the Oracle Database and deploy them into Oracle Exadata for scoring, using Oracle Data Mining, a component of Oracle Advanced Analytics, leveraging Oracle Database11g technology. This enabled the company to create predictive antifraud models faster than with any other machine, as models can be built using search and query language (SQL) inside the database, and Oracle Exadata can access raw data without summarized tables, thereby achieving extremely fast analyses.
A word from Turkcell İletişim Hizmetleri A.Ş.
“Turkcell manages 100 terabytes of compressed data—or one petabyte of uncompressed raw data—on Oracle Exadata. With Oracle Data Mining, a component of the Oracle Advanced Analytics Option, we can analyze large volumes of customer data and call-data records easier and faster than with any other tool and rapidly detect and combat fraudulent phone use.” – Hasan Tonguç Yılmaz, Manager, Turkcell İletişim Hizmetleri A.Ş.
- Combat communications fraud and money laundering by introducing advanced analytical solutions to monitor prepaid card usage and alert or block suspicious activity
- Monitor numerous parameters for up to 10 billion daily call-data records and value-added service logs, including the number of accounts and cards per customer, number of card loads per day, number of account loads over time, and number of account loads on a subscriber identity module card at the same location
- Enable extremely fast sifting through huge data volumes to identify patterns and relationships, build predictive antifraud models, and apply those models to even larger data volumes to make accurate fraud predictions
- Detect fraud patterns as soon as possible and enable quick response to minimize the negative financial impact
Oracle Product and Services
- Used Oracle Exadata Database Machine X2-2 HC Full Rack to create predictive antifraud models more quickly than with previous solutions by accessing raw data without summarized tables and providing unmatched query speed, which optimizes and shortens the project design phases for creating predictive antifraud models
- Leveraged SQL for the preparation and transformation of one petabyte of uncompressed raw communications data, using Oracle Data Mining, a feature of Oracle Advanced Analytics to increase the performance of predictive antifraud models
- Deployed Oracle Data Mining models on Oracle Exadata to identify actionable information in less time than traditional methods—which would require moving large volumes of customer data to a third-party analytics software—and achieve an average gain of four hours and more, taking into consideration the absence of any system crash (as occurred in the previous environment) during data import
- Achieved extreme data analysis speed with in-database analytics performed inside Oracle Exadata, through a row-wise information search—including day, time, and duration of calls, as well as number of credit recharges on the same day or at the same location—and query language functions that enabled analysts to detect fraud patterns almost immediately
- Implemented a future-proof solution that could support rapidly growing data volumes that tend to double each year with Oracle Exadata’s massively scalable data warehouse performance
“We selected Oracle because in-database mining to support antifraud efforts will be a major focus for Turkcell in the future. With Oracle Exadata Database Machine and the analytics capabilities of Oracle Advanced Analytics, we can complete antifraud analysis for large amounts of call-data records in just a few hours. Further, we can scale the solution as needed to support rapid communications data growth,” said Hasan Tonguç Yılmaz, datawarehouse/data mining developer, Turkcell Teknoloji Araştırma ve Geliştirme A.Ş.
Oracle Partner: Turkcell Teknoloji Araştırma ve Geliştirme A.Ş.
All development and test processes were performed by Turkcell Teknoloji. The company also made significant contributions to the configuration of numerous technical analyses which are carried out regularly by Turkcell İletişim Hizmetleri's antifraud specialists.
- Turkcell İletişim Hizmetleri Uses Engineered System to Analyze 10 Billion Daily, Call-Data Records and Service Logs and to Generate 100,000 Monthly Reports
- Turkcell Deploys Oracle Data Integrator to Drive Efficiency
- Turkcell Accelerates Reporting Tenfold, Saves on Storage and Energy Costs with Consolidated Oracle Exadata Platform
- Turkcell Superonline Transforms Its Order Management and Service Fulfillment with Oracle Communications Solutions
- Technologist of the Year
- Turkcell is an Exemplary Oracle Cross Stack Customer
- Turkcell Gets Three 10X Improvements with Oracle
- Oracle Exadata Changes the Rules of the Game for Turkcell
- Customers Discuss Benefits of Oracle Exadata
- Turkcell Technology Uses Oracle Complex Event Processing for Extreme Scale Mobile Networks
- Turkcell Technology Research & Development Inc. Achieves Substantial Savings with Fault Prevention
- Turkcell iletisim Hizmetleri A.S. Processes Mobile Network Data of 33 Million Subscribers in Real Time
- Kcell Boosts Business Intelligence with Data Warehouse Solution
- Turkcell Gets the Benefits of Oracle Exadata
- Turkcell Eliminates Manual Updates with Oracle IDM
Tuesday May 29, 2012
By chberger on May 29, 2012
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.
Thursday May 10, 2012
By chberger on May 10, 2012
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 NEW
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|
|2 Days||09-Aug-2012||04:00 AM EDT||12:00 PM EDT||English||English||Available||Public|
|2 Days||18-Oct-2012||04:00 AM EDT||12:00 PM EDT||English||English||Available||Public|
Wednesday Apr 04, 2012
By chberger on Apr 04, 2012
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 firstname.lastname@example.org 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
By chberger on Mar 23, 2012
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.
- 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
By chberger on Mar 23, 2012
UPDATED (March 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
- 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.
- For Oracle Database Release 11g, 18.104.22.168.0 DB is the minimum, 22.214.171.124 is better and naturally 126.96.36.199 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 )
- 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!
Note: There are also four (4) additional Oracle Data Miner 3.2 Tutorials that are similar that may be helpful to review.
- Setting Up Oracle Data Miner 11g Release 2 This tutorial covers the process of setting up Oracle Data Miner 11g Release 2 for use within Oracle SQL Developer 3.0.
- Using Oracle Data Miner 11g Release 2 This tutorial covers the use of Oracle Data Miner to perform data mining against Oracle Database 11g Release 2. In this lesson, you examine and solve a data mining business problem by using the Oracle Data Miner graphical user interface (GUI).
- Star Schema Mining Using Oracle Data Miner This tutorial covers the use of Oracle Data Miner to perform star schema mining against Oracle Database 11g Release 2.
- Text Mining Using Oracle Data Miner This tutorial covers the use of Oracle Data Miner to perform text mining against Oracle Database 11g Release 2.
Wednesday Feb 08, 2012
Thursday Jul 14, 2011
Oracle Fusion Human Capital Management Application uses Oracle Data Mining for Workforce Predictive Analytics
By chberger on Jul 14, 2011
Oracle's new Fusion Human Capital Management (HCM) Application now embeds predictive analytic models automatically generated by Oracle Data Mining to enrich dashboards and manager's portals with predictions about the likelihood that an employee with voluntarily leave the organization and a prediction about the employee's likely future performance. Armed with this new information that is based on historical patterns and relationships found by Oracle Data Mining, enterprises can more proactively manage their valuable employee assets and better compete. The integrated Oracle Fusion HCM Application requires the Oracle Data Mining Option to the Oracle Database. With custom predictive models generated using the customer's own data, Oracle Fusion HCM enables managers to better understand the employees, understand the key factors for each individual and even perform "What if?" analysis to see the likely impact on an employee by adjusting a critical HR factor e.g. bonus, vacation time, amount of travel, etc.
Excerpting from the Oracle Fusion HCM website and collateral: "Every day organizations struggle to answer essential questions about their workforce. How much money are we losing by not having the right talent in place and how is that impacting current projects? What skills will we need in the next 5 years that we don’t have today? How will business be impacted by impending retirements and are we prepared? Fragmented systems and bolt-on analytics are only some of the barriers that HR faces today. The consequences include missed opportunities, lost productivity, attrition, and uncontrolled operational costs. To address these challenges, Oracle Fusion Human Capital Management (HCM)puts information at your fingertips, helps you predict future trends, and enables you to turn insight into action. You will eliminate unnecessary costs, increase workforce productivity and retention, and gain a strategic advantage over your competition. Oracle Fusion HCM has been designed from the ground up so that you can work naturally and intuitively with analytics woven right into the fabric of your business processes."
This exceprt from the Solution Brief http://www.oracle.com/us/products/applications/fusion/fusion-hcm-know-your-people-356192.pdf describes the Predictive Analytics features and benefits: "Every day organizations struggle to answer essential questions about their workforce. How much money are we losing by not having the right talent in place and how is that impacting current projects? What skills will we need in the next 5 years that we don’t have today? How will business be impacted by impending retirements and are we prepared? Fragmented systems and bolt-on analytics are only some of the barriers that HR faces today. The consequences include missed opportunities, lost productivity, attrition, and uncontrolled operational costs. To address these challenges, Oracle Fusion Human Capital Management (HCM) puts information at your fingertips, helps you predict future trends, and enables you to turn insight into action. You will eliminate unnecessary costs, increase workforce productivity and retention, and gain a strategic advantage over your competition. Oracle Fusion HCM has been designed from the ground up so that you can work naturally and intuitively with analytics woven right into the fabric of your business processes." ....
"Predictive Analysis Imagine if you could look ahead and be prepared for upcoming workforce trends. Most organizations do not have the analytic capability to do predictive human capital analysis, yet the worker information needed to make educated forecasts already exists today. Aging populations, shifting demographics, rising and falling economies, and multi-generational issues can have a significant impact on workforce decisions – for employees, managers and HR professionals. Not being able to accurately predict how all the moving parts fit together, and where you really have potential problems, can make or break an organization. Oracle Fusion HCM gives you the ability to finally see into the future, analyzing worker performance potential, risk of attrition, and enabling what-if analysis on ways to improve your workforce. Additionally, modeling capabilities provide you with extra power to bring together information from sources unthinkable in the past. For example, imagine understanding which recruiting agencies are providing the highest-quality recruits by comparing first year performance ratings with sources of hire. Being able to see potential problems before they occur and take immediate action will increase morale, save money, and boost your competitive edge. Result: You are able to look ahead and be prepared for upcoming workforce trends."
There is a great demo of Oracle Fusion HCM Workforce Predictive Analytics that highlights the Oracle Data Mining. This is one of the latest examples of Applications "powered by Oracle Data Mining".
When you change your paradigm and move the algorithms to the data rather than the traditional approach of extracting the data and moving it to the algorithms for analysis, it CHANGES EVERYTHING. Keep watching for additional Applications powered by Oracle's in-database advanced analytics.
Thursday Dec 09, 2010
Monday Mar 08, 2010
Everything about Oracle Data Mining, a component of the Oracle Advanced Analytics Option - News, Technical Information, Opinions, Tips & Tricks. All in One Place
- Deploy Data Miner Apply Node SQL as RESTful Web Service for Real-Time Scoring
- How to generate training and test dataset using SQL Query node in Data Miner
- dunnhumby Accelerates Complex Segmentation Queries from Weeks to Minutes—Gains Competitive Advantage
- How to generate Scatterplot Matrices using R script in Data Miner
- How to export data from the Explore Node using Data Miner and SQL Developer
- Oracle BIWA Summit 2014 January 14-16, 2014 at Oracle HQ in Redwood Shores, CA
- Come See and Test Drive Oracle Advanced Analytics at the BIWA Summit'14, Jan 14-16, 2014
- Oracle Big Data Learning Library
- Oracle Data Miner (Extension of SQL Developer 4.0) Integrate Oracle R Enterprise Mining Algorithms into workflow using the SQL Query node
- Oracle Data Miner GUI, part of SQL Developer 4.0 Early Adopter 1 is now available for download on OTN