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 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 https://www.oracle.com/openworld/call-for-proposals.html 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 speaker-services_ww@oracle.com.
  • For technical questions about the submission tool or issues with submitting your proposal, send an e-mail to OpenWorldContent@gpj.com.
  • Oracle employee submitters should contact the appropriate Oracle track leads before submitting. To view a list of track leads, click here.

Thursday Nov 20, 2014

ORACLE BI, DW, ANALYTICS, BIG DATA AND SPATIAL USER COMMUNITY - BIWA Summit'15 www.biwasummit.org

Please share with your Oracle BI, DW, Analytics, big Data and Spatial User coMMUNITY.   THANKS.  CB

BIWA Summit’15 Jan 27-29, 2015 Early Bird Registration Ends Friday. 

Registration is now LIVE. Register by November 21st (tomorrow) to receive the early bird pricing of $249 and save $50.

Please direct your colleagues to REGISTER NOW and participate to take advantage of the Early Bird registration ($249.00 USD).  EARLY BIRD SPECIAL ENDS TOMORROW (Friday, Nov. 21).  Here’s some information about the event below and some pics and talks from last year to give some feel for the opportunity.   

BIWA Summits have been organized and managed by the Oracle BI, DW and Analytics SIG user community of IOUG (Independent Oracle User Group) and attract the top Oracle BI, DW and Advanced Analytics and Big Data experts. The 2.5-day BIWA Summit'15 event joins forces with the Oracle Spatial SIG and involves Keynotes by Industry experts, Educational sessions, Hands-on Labs and networking events. We have a great line up so far w/ Tom Kyte Senior Technical Architect in Oracles Server Technology, Doug Cutting (Chief Architect, Cloudera), Oracle BI Senior Management, Neil Mendelson, VP of Product Management Big Data and Advanced Analytics, Matt Bradley, SVP, Oracle Product Development, EPM Applications, other features speakers, and many customers/tech experts (see web site and search % Sessions). Our BIWA Summit offers a broad, multi-track user driven conference that has built up a growing reputation over the years. We emphasize technical content and networking with like minded customers, users, developers, product managers (Database, Big Data Appliance, Oracle Advanced Analytics, Spatial, OBIEE, Endeca, Big Data Discovery, In-Memory, SQL Patterns, etc.), etc. who all share an interest in “novel and interesting use cases” of Oracle BI, DW, Advanced Analytics and Spatial technologies, applications and solutions. We’re off to a great start this year with a great agenda and hope to pack the HQ CC this Jan 27-29, 2015 with 300+ attendees.

Please forward and share with your Oracle BI, DW, Analytics, Big Data and Spatial colleagues.   

Thank you!  Hope to see you at BIWA Summit'15

Charlie

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

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.  

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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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 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!

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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Tuesday Jan 01, 2013

Turkcell Combats Pre-Paid Calling Card Fraud Using In-Database Oracle Advanced Analytics

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]

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.

Challenges

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

Solutions

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

Why Oracle

“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.

Partner

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.

Resources

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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.  

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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Wednesday Feb 10, 2010

Funny YouTube video that features Oracle Data Mining

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