Wednesday May 08, 2013

Oracle Advanced Analytics and Data Mining at the Movies on YouTube

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.

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

Charlie 

Oracle Advanced Analytics at the Movies

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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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Tuesday Aug 09, 2011

SAIL-WORLD article - America's Cup: Oracle Data Mining supports crew and BMW ORACLE Racing

Originally printed at http://www.sail-world.com/UK/Americas-Cup:-Oracle-Data-Mining-supports-crew-and-BMW-ORACLE-Racing/68834

America's Cup: Oracle Data Mining supports crew and BMW ORACLE Racing


  <script language="freezescript"> </script>
'USA-17 on her way to winning the 33rd America’s Cup, use of Oracle’s datamining technology and Oracle Database 11g and Oracle Application Express'    BMW Oracle Racing © Photo Gilles Martin-Raget    Click Here to view large photo

BMW ORACLE Racing won the 33rd America’s Cup yacht race in February 2010, beating the Swiss team, Alinghi, decisively in the first two races of the best-of-three contest.

BMW ORACLE Racing’s victory in the America’s Cup challenge was a lesson in sailing skill, as one of the world’s most experienced crews reached speeds as fast as 30 knots. But if you listen to the crew in their postrace interviews, you’ll notice that what they talk about is technology.

The wrist PDA displays worn by five of the USA-17 crew - where they could read actual and predictive data fed back from the onboard systems -  .. .   Click Here to view large photo

'The story of this race is in the technology,' says Ian Burns, design coordinator for BMW ORACLE Racing.

From the drag-resistant materials encasing its hulls to its unprecedented 223-foot wing sail, the BMW ORACLE Racing’s trimaran, named USA, is a one-of-a-kind technological juggernaut. No less impressive are the electronics used to guide the vessel and fine-tune its performance.

Each crewmember is equipped with a PDA on his wrist that has customized data for his job: what the load balance is on a particular rope, for example, or the current aerodynamic performance of the wing sail. The helmsman’s sunglasses display graphical and numeric data to help him fine-tune the boat’s direction while he keeps two hands on the wheel and visually scans the sea, the boat, the crew, the sails, and the wing.

The America’s Cup is a challenge-based competition in which the winning yacht club hosts the next event and, within certain guidelines, makes the rules. For the 33rd America’s Cup, the competing teams could not agree on a set of rules, so the event defaulted to an unrestricted format for boat design and cost.

'All we knew were the length of the boat and the course configuration,' says Burns. The boats were allowed a maximum length of 90 feet, and the course would be 20 miles out windward and 20 miles back. 'Within those parameters,' says Burns, 'you could build as fast a thing as you can think of.'

Learning by Data

The no-holds-barred rules for this race created what Burns calls an 'open playground' for boat designers. The innovative and costly vessels that resulted were one-of-a-kind creations with unpredictable sailing characteristics that would require a steep learning curve and lots of data.

33rd America’s Cup - BMW ORACLE Racing - Training in Valencia - collecting data via 250 sensors, managing it and analysing it were handled on the yacht, on the tender and ashore in Valencia and in the Austin Data Centre, USA. -  BMW Oracle Racing © Photo Gilles Martin-Raget   Click Here to view large photo

'One of the problems we faced at the outset was that we needed really high accuracy in our data because we didn’t have two boats,' says Burns. 'Generally, most teams have two boats, and they sail them side by side. Change one thing on one boat, and it’s fairly easy to see the effect of a change with your own eyes.'

With only one boat, BMW ORACLE Racing’s performance analysis had to be done numerically by comparing data sets. To get the information needed, says Burns, the team had to increase the amount of data collected by nearly 40 times what they had done in the past.

The USA holds 250 sensors to collect raw data: pressure sensors on the wing; angle sensors on the adjustable trailing edge of the wing sail to monitor the effectiveness of each adjustment, allowing the crew to ascertain the amount of lift it’s generating; and fiber-optic strain sensors on the mast and wing to allow maximum thrust without overbending them.

33rd America’s Cup - BMW ORACLE Racing - Day 1 - The difference between the wingsail and softsail is evident - even though the softsail has more area -  BMW Oracle Racing: Guilain Grenier   Click Here to view large photo


But collecting data was only the beginning. BMW ORACLE Racing also had to manage that data, analyze it, and present useful results. The team turned to Oracle Data Mining in Oracle Database 11g.

Peter Stengard, a principal software engineer for Oracle Data Mining and an amateur sailor, became the liaison between the database technology team and BMW ORACLE Racing. 'Ian Burns contacted us and explained that they were interested in better understanding the performance-driving parameters of their new boat,' says Stengard. 'They were measuring an incredible number of parameters across the trimaran, collected 10 times per second, so there were vast amounts of data available for analysis. An hour of sailing generates 90 million data points.'

After each day of sailing the boat, Burns and his team would meet to review and share raw data with crewmembers or boat-building vendors using a Web application built with Oracle Application Express. 'Someone in the meeting would say, 'Wouldn’t it be great if we could look at some new combination of numbers?’ and we could quickly build an Oracle Application Express application and share the information during the same meeting,' says Burns. Later, the data would be streamed to Oracle’s Austin Data Center, where Stengard and his team would go to work on deeper analysis.

BMW Oracle USA-17 powers thru Alinghi - America’s Cup 2010 Race 1 -  BMW Oracle Racing © Photo Gilles Martin-Raget   Click Here to view large photo


Because BMW ORACLE Racing was already collecting its data in an Oracle database, Stengard and his team didn’t have to do any extract, transform, and load (ETL) processes or data conversion. 'We could just start tackling the analytics problem right away,' says Stengard. 'We used Oracle Data Mining, which is in Oracle Database. It gives us many advanced data mining algorithms to work with, so we have freedom in how we approach any specific task.'

Using the algorithms in Oracle Data Mining, Stengard could help Burns and his team learn new things about how their boat was working in its environment. 'We would look, for example, at mast rotations—which rotation works best for certain wind conditions,' says Stengard. 'There were often complex relationships within the data that could be used to model the effect on the target—in this case something called velocity made good, or VMG. Finding these relationships is what the racing team was interested in.'

BMW Oracle Racing Technology team -  Richard Gladwell   Click Here to view large photo

Stengard and his team could also look at data over time and with an attribute selection algorithm to determine which sensors provided the most-useful information for their analysis. 'We could identify sensors that didn’t seem to be providing the predictive power they were looking for so they could change the sensor location or add sensors to another part of the boat,' Stengard says.

Burns agrees that without the data mining, they couldn’t have made the boat run as fast. 'The design of the boat was important, but once you’ve got it designed, the whole race is down to how the guys can use it,' he says. 'With Oracle database technology, we could compare our performance from the first day of sailing to the very last day of sailing, with incremental improvements the whole way through. With data mining we could check data against the things we saw, and we could find things that weren’t otherwise easily observable and findable.'

BMW Oracle Racing made 4000 data measurements 10 times a second -  BMW Oracle Racing: Guilain Grenier   Click Here to view large photo

Flying by Data

The greatest challenge of this America’s Cup, according to Burns, was managing the wing sail, which had been built on an unprecedented scale. 'It is truly a massive piece of architecture,' Burns says. 'It’s 20 stories high; it barely fits under the Golden Gate Bridge. It’s an amazing thing to see.'

The wing sail is made of an aeronautical fabric stretched over a carbon fiber frame, giving it the three-dimensional shape of a regular airplane wing. Like an airplane wing, it has a fixed leading edge and an adjustable trailing edge, which allows the crew to change the shape of the sail during the course of a race.

Oracle wing under maintenance - standing 70 metres high it is the longest wing ever build for a plane or yacht -  Jean Philippe Jobé   Click Here to view large photo


Next Steps

'The crew of the USA was the best group of sailors in the world, but they were used to working with sails,' says Burns, 'Then we put them under a wing. Our chief designer, Mike Drummond, told them an airline pilot doesn’t look out the window when he’s flying the plane; he looks at his instruments, and you guys have to do the same thing.'

A second ship, known as the performance tender, accompanied the USA on the water. The tender served in part as a floating datacenter and was connected to the USA by wireless LAN.

USA-17 about to round the windward mark, Race 1, 33rd America’s Cup. Under performing senors on the boat were moved to provide better information. -  Richard Gladwell  


'The USA generates almost 4,000 variables 10 times a second,' says Burns. 'Sometimes the analysis requires a very complicated combination of 10, 20, or 30 variables fitted through a time-based algorithm to give us predictions on what will happen in the next few seconds, or minutes, or even hours in terms of weather analysis.'

Like the deeper analysis that Stengard does back at the Austin Data Center, this real-time data management and near-real-time data analysis was done in Oracle Database 11g. 'We could download the data to servers on the tender ship, do some quick analysis, and feed it right back to the USA,' says Burns.

'We started to do better when the guys began using the instruments,' Burns says. 'Then we started to make small adjustments against the predictions and started to get improvements, and every day we were making gains.'

Those gains were incremental and data driven, and they accumulated over years—until the USA could sail at three times the wind speed. Ian Burns is still amazed by the spectacle.

'It’s an awesome thing to watch,' he says. 'Even with all we have learned, I don’t think we have met the performance limits of that beautiful wing.'

USA-17 pursues Alinghi 5 - Race 1, 33rd America’s Cup, Valencia. Her crew flew her off the instruments 'a pilot doesn’t fly a plane by looking out the window'. -  BMW Oracle Racing: Guilain Grenier   Click Here to view large photo

Read more about Oracle Data Mining

Hear a podcast interview with Ian Burns

Download Oracle Database 11g Release 2

Story republished from: www.oracle.com/technology/oramag/oracle/10-may/o30racing.html

by Jeff Erickson Share   11:41 PM Sat 24 Apr 2010 GMT


Thursday Jul 14, 2011

Oracle Fusion Human Capital Management Application uses Oracle Data Mining for Workforce Predictive Analytics

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".

 

Employee grid

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.

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