Interesting announcement from PiCloud

An interesting announcement from PiCloud who is a cloud computing startup, but focused on python (as the name suggests). They basically have created a cloud library (or in R lingo – a package) that enables you to call cloud power sitting from the desktop interface itself. This announcement is for multiple IP addresses. Real parallel processing or just a quick trick in technical jargon- you decide!

  1. Prepare
  2. Run
  3. Monitor
Prepare

s1 cores are comparable in performance to c1 cores with one extra trick up their sleeve: each job running in parallel will have a different IP.

Why is this important?
Using unique IPs is necessary to minimize the automated throttling most sites will impose when seeing fast, repeated access from a single IP.

How do I use it?
If you’re already using our c1 cores, all you’ll need to do is set the _type keyword.

cloud.call(func, _type=’s1′)

How much?
$0.04/core/hour

Why don’t other cores have individual IPs?
For other core types, such as c2, multiple cores may be running on a single machine that is assigned only a single IP address. When using s1 cores, you’re guaranteed that each core sits on a different machine.

 

http://www.picloud.com/

Denial of Service Attacks against Hospitals and Emergency Rooms

One of the most frightening possibilities of cyber warfare is to use remotely deployed , or timed intrusion malware to disturb, distort, deny health care services.

Computer Virus Shuts Down Georgia Hospital

A doctor in an Emergency Room depends on critical information that may save lives if it is electronic and comes on time. However this electronic information can be distorted (which is more severe than deleting it)

The electronic system of a Hospital can also be overwhelmed. If there can be built Stuxnet worms on   nuclear centrifuge systems (like those by Siemens), then the widespread availability of health care systems means these can be reverse engineered for particularly vicious cyber worms.

An example of prime area for targeting is Veterans Administration for veterans of armed forces, but also cyber attacks against electronic health records.

Consider the following data points-

http://threatpost.com/en_us/blogs/dhs-warns-about-threat-mobile-devices-healthcare-051612

May 16, 2012, 9:03AM

DHS’s National Cybersecurity and Communications Integration Center (NCCIC) issued the unclassfied bulletin, “Attack Surface: Healthcare and Public Health Sector” on May 4. In it, DHS warns of a wide range of security risks, including that could expose patient data to malicious attackers, or make hospital networks and first responders subject to disruptive cyber attack

http://publicintelligence.net/nccic-medical-device-cyberattacks/

National Cybersecurity and Communications Integration Center Bulletin

The Healthcare and Public Health (HPH) sector is a multi-trillion dollar industry employing over 13 million personnel, including approximately five million first-responders with at least some emergency medical training, three million registered nurses, and more than 800,000 physicians.

(U) A significant portion of products used in patient care and management including diagnosis and treatment are Medical Devices (MD). These MDs are designed to monitor changes to a patient’s health and may be implanted or external. The Food and Drug Administration (FDA) regulates devices from design to sale and some aspects of the relationship between manufacturers and the MDs after sale. However, the FDA cannot regulate MD use or users, which includes how they are linked to or configured within networks. Typically, modern MDs are not designed to be accessed remotely; instead they are intended to be networked at their point of use. However, the flexibility and scalability of wireless networking makes wireless access a convenient option for organizations deploying MDs within their facilities. This robust sector has led the way with medical based technology options for both patient care and data handling.

(U) The expanded use of wireless technology on the enterprise network of medical facilities and the wireless utilization of MDs opens up both new opportunities and new vulnerabilities to patients and medical facilities. Since wireless MDs are now connected to Medical information technology (IT) networks, IT networks are now remotely accessible through the MD. This may be a desirable development, but the communications security of MDs to protect against theft of medical information and malicious intrusion is now becoming a major concern. In addition, many HPH organizations are leveraging mobile technologies to enhance operations. The storage capacity, fast computing speeds, ease of use, and portability render mobile devices an optimal solution.

(U) This Bulletin highlights how the portability and remote connectivity of MDs introduce additional risk into Medical IT networks and failure to implement a robust security program will impact the organization’s ability to protect patients and their medical information from intentional and unintentional loss or damage.

(U) According to Health and Human Services (HHS), a major concern to the Healthcare and Public Health (HPH) Sector is exploitation of potential vulnerabilities of medical devices on Medical IT networks (public, private and domestic). These vulnerabilities may result in possible risks to patient safety and theft or loss of medical information due to the inadequate incorporation of IT products, patient management products and medical devices onto Medical IT Networks. Misconfigured networks or poor security practices may increase the risk of compromised medical devices. HHS states there are four factors which further complicate security resilience within a medical organization.

1. (U) There are legacy medical devices deployed prior to enactment of the Medical Device Law in 1976, that are still in use today.

2. (U) Many newer devices have undergone rigorous FDA testing procedures and come equipped with design features which facilitate their safe incorporation onto Medical IT networks. However, these secure design features may not be implemented during the deployment phase due to complexity of the technology or the lack of knowledge about the capabilities. Because the technology is so new, there may not be an authoritative understanding of how to properly secure it, leaving open the possibilities for exploitation through zero-day vulnerabilities or insecure deployment configurations. In addition, new or robust features, such as custom applications, may also mean an increased amount of third party code development which may create vulnerabilities, if not evaluated properly. Prior to enactment of the law, the FDA required minimal testing before placing on the market. It is challenging to localize and mitigate threats within this group of legacy equipment.

3. (U) In an era of budgetary restraints, healthcare facilities frequently prioritize more traditional programs and operational considerations over network security.

4. (U) Because these medical devices may contain sensitive or privacy information, system owners may be reluctant to allow manufactures access for upgrades or updates. Failure to install updates lays a foundation for increasingly ineffective threat mitigation as time passes.

(U) Implantable Medical Devices (IMD): Some medical computing devices are designed to be implanted within the body to collect, store, analyze and then act on large amounts of information. These IMDs have incorporated network communications capabilities to increase their usefulness. Legacy implanted medical devices still in use today were manufactured when security was not yet a priority. Some of these devices have older proprietary operating systems that are not vulnerable to common malware and so are not supported by newer antivirus software. However, many are vulnerable to cyber attacks by a malicious actor who can take advantage of routine software update capabilities to gain access and, thereafter, manipulate the implant.

(U) During an August 2011 Black Hat conference, a security researcher demonstrated how an outside actor can shut off or alter the settings of an insulin pump without the user’s knowledge. The demonstration was given to show the audience that the pump’s cyber vulnerabilities could lead to severe consequences. The researcher that provided the demonstration is a diabetic and personally aware of the implications of this activity. The researcher also found that a malicious actor can eavesdrop on a continuous glucose monitor’s (CGM) transmission by using an oscilloscope, but device settings could not be reprogrammed. The researcher acknowledged that he was not able to completely assume remote control or modify the programming of the CGM, but he was able to disrupt and jam the device.

http://www.healthreformwatch.com/category/electronic-medical-records/

February 7, 2012

Since the data breach notification regulations by HHS went into effect in September 2009, 385 incidents affecting 500 or more individuals have been reported to HHS, according to its website.

http://www.darkdaily.com/cyber-attacks-against-internet-enabled-medical-devices-are-new-threat-to-clinical-pathology-laboratories-215#axzz1yPzItOFc

February 16 2011

One high-profile healthcare system that regularly experiences such attacks is the Veterans Administration (VA). For two years, the VA has been fighting a cyber battle against illegal and unwanted intrusions into their medical devices

 

http://www.mobiledia.com/news/120863.html

 DEC 16, 2011
Malware in a Georgia hospital’s computer system forced it to turn away patients, highlighting the problems and vulnerabilities of computerized systems.

The computer infection started to cause problems at the Gwinnett Medical Center last Wednesday and continued to spread, until the hospital was forced to send all non-emergency admissions to other hospitals.

More doctors and nurses than ever are using mobile devices in healthcare, and hospitals are making patient records computerized for easier, convenient access over piles of paperwork.

http://www.doctorsofusc.com/uscdocs/locations/lac-usc-medical-center

As one of the busiest public hospitals in the western United States, LAC+USC Medical Center records nearly 39,000 inpatient discharges, 150,000 emergency department visits, and 1 million ambulatory care visits each year.

http://www.healthreformwatch.com/category/electronic-medical-records/

If one jumbo jet crashed in the US each day for a week, we’d expect the FAA to shut down the industry until the problem was figured out. But in our health care system, roughly 250 people die each day due to preventable error

http://www.pcworld.com/article/142926/are_healthcare_organizations_under_cyberattack.html

Feb 28, 2008

“There is definitely an uptick in attacks,” says Dr. John Halamka, CIO at both Beth Israel Deaconess Medical Center and Harvard Medical School in the Boston area. “Privacy is the foundation of everything we do. We don’t want to be the TJX of healthcare.” TJX is the Framingham, Mass-based retailer which last year disclosed a massive data breach involving customer records.

Dr. Halamka, who this week announced a project in electronic health records as an online service to the 300 doctors in the Beth Israel Deaconess Physicians Organization,

Interview Markus Schmidberger ,Cloudnumbers.com

Here is an interview with Markus Schmidberger, Senior Community Manager for cloudnumbers.com. Cloudnumbers.com is the exciting new cloud startup for scientific computing. It basically enables transition to a R and other platforms in the cloud and makes it very easy and secure from the traditional desktop/server model of operation.

Ajay- Describe the startup story for setting up Cloudnumbers.com

Markus- In 2010 the company founders Erik Muttersbach (TU München), Markus Fensterer (TU München) and Moritz v. Petersdorff-Campen (WHU Vallendar) started with the development of the cloud computing environment. Continue reading “Interview Markus Schmidberger ,Cloudnumbers.com”

Cloud Computing using Python

I liked the new features in PiCloud , which is a cloud computing way to use Python. Python is increasingly popular as a computational language, and the cloud is the way where HW is headed to atleast as of 2011-12

http://www.picloud.com/

The new features allows you to publish your own functions as urls.

 By publishing your Python functions to URLs. Why would you want to publish a function?

  • To call your Python functions from a programming language other than Python.
  • To use PiCloud from Google AppEngine, which does not support our native client library.
  • To easily setup a scalable RPC system.

Here’s a peek at the interface:

You publish a Python function

cloud.rest.publish(your_func, ‘myfunction’)

We give you a URL Back

https://api.picloud.com/r/2/myfunction/

You make an HTTP request using your method of choice to the URL

curl -k -u ‘key:secret_key’ https://api.picloud.com/r/2/myfunction/

It certainly is an interesting development and I am wondering how other languages can adopt this paradigm as well.
For R, as of now http://www.cloudnumbers.com/ seems to be the only player in the cloud.
It would be exciting to see more players in the cloud statistical analytical space.

 

Interview Dan Steinberg Founder Salford Systems

Here is an interview with Dan Steinberg, Founder and President of Salford Systems (http://www.salford-systems.com/ )

Ajay- Describe your journey from academia to technology entrepreneurship. What are the key milestones or turning points that you remember.

 Dan- When I was in graduate school studying econometrics at Harvard,  a number of distinguished professors at Harvard (and MIT) were actively involved in substantial real world activities.  Professors that I interacted with, or studied with, or whose software I used became involved in the creation of such companies as Sun Microsystems, Data Resources, Inc. or were heavily involved in business consulting through their own companies or other influential consultants.  Some not involved in private sector consulting took on substantial roles in government such as membership on the President’s Council of Economic Advisors. The atmosphere was one that encouraged free movement between academia and the private sector so the idea of forming a consulting and software company was quite natural and did not seem in any way inconsistent with being devoted to the advancement of science.

 Ajay- What are the latest products by Salford Systems? Any future product plans or modification to work on Big Data analytics, mobile computing and cloud computing.

 Dan- Our central set of data mining technologies are CART, MARS, TreeNet, RandomForests, and PRIM, and we have always maintained feature rich logistic regression and linear regression modules. In our latest release scheduled for January 2012 we will be including a new data mining approach to linear and logistic regression allowing for the rapid processing of massive numbers of predictors (e.g., one million columns), with powerful predictor selection and coefficient shrinkage. The new methods allow not only classic techniques such as ridge and lasso regression, but also sub-lasso model sizes. Clear tradeoff diagrams between model complexity (number of predictors) and predictive accuracy allow the modeler to select an ideal balance suitable for their requirements.

The new version of our data mining suite, Salford Predictive Modeler (SPM), also includes two important extensions to the boosted tree technology at the heart of TreeNet.  The first, Importance Sampled learning Ensembles (ISLE), is used for the compression of TreeNet tree ensembles. Starting with, say, a 1,000 tree ensemble, the ISLE compression might well reduce this down to 200 reweighted trees. Such compression will be valuable when models need to be executed in real time. The compression rate is always under the modeler’s control, meaning that if a deployed model may only contain, say, 30 trees, then the compression will deliver an optimal 30-tree weighted ensemble. Needless to say, compression of tree ensembles should be expected to be lossy and how much accuracy is lost when extreme compression is desired will vary from case to case. Prior to ISLE, practitioners have simply truncated the ensemble to the maximum allowable size.  The new methodology will substantially outperform truncation.

The second major advance is RULEFIT, a rule extraction engine that starts with a TreeNet model and decomposes it into the most interesting and predictive rules. RULEFIT is also a tree ensemble post-processor and offers the possibility of improving on the original TreeNet predictive performance. One can think of the rule extraction as an alternative way to explain and interpret an otherwise complex multi-tree model. The rules extracted are similar conceptually to the terminal nodes of a CART tree but the various rules will not refer to mutually exclusive regions of the data.

 Ajay- You have led teams that have won multiple data mining competitions. What are some of your favorite techniques or approaches to a data mining problem.

 Dan- We only enter competitions involving problems for which our technology is suitable, generally, classification and regression. In these areas, we are  partial to TreeNet because it is such a capable and robust learning machine. However, we always find great value in analyzing many aspects of a data set with CART, especially when we require a compact and easy to understand story about the data. CART is exceptionally well suited to the discovery of errors in data, often revealing errors created by the competition organizers themselves. More than once, our reports of data problems have been responsible for the competition organizer’s decision to issue a corrected version of the data and we have been the only group to discover the problem.

In general, tackling a data mining competition is no different than tackling any analytical challenge. You must start with a solid conceptual grasp of the problem and the actual objectives, and the nature and limitations of the data. Following that comes feature extraction, the selection of a modeling strategy (or strategies), and then extensive experimentation to learn what works best.

 Ajay- I know you have created your own software. But are there other software that you use or liked to use?

 Dan- For analytics we frequently test open source software to make sure that our tools will in fact deliver the superior performance we advertise. In general, if a problem clearly requires technology other than that offered by Salford, we advise clients to seek other consultants expert in that other technology.

 Ajay- Your software is installed at 3500 sites including 400 universities as per http://www.salford-systems.com/company/aboutus/index.html What is the key to managing and keeping so many customers happy?

 Dan- First, we have taken great pains to make our software reliable and we make every effort  to avoid problems related to bugs.  Our testing procedures are extensive and we have experts dedicated to stress-testing software . Second, our interface is designed to be natural, intuitive, and easy to use, so the challenges to the new user are minimized. Also, clear documentation, help files, and training videos round out how we allow the user to look after themselves. Should a client need to contact us we try to achieve 24-hour turn around on tech support issues and monitor all tech support activity to ensure timeliness, accuracy, and helpfulness of our responses. WebEx/GotoMeeting and other internet based contact permit real time interaction.

 Ajay- What do you do to relax and unwind?

 Dan- I am in the gym almost every day combining weight and cardio training. No matter how tired I am before the workout I always come out energized so locating a good gym during my extensive travels is a must. I am also actively learning Portuguese so I look to watch a Brazilian TV show or Portuguese dubbed movie when I have time; I almost never watch any form of video unless it is available in Portuguese.

 Biography-

http://www.salford-systems.com/blog/dan-steinberg.html

Dan Steinberg, President and Founder of Salford Systems, is a well-respected member of the statistics and econometrics communities. In 1992, he developed the first PC-based implementation of the original CART procedure, working in concert with Leo Breiman, Richard Olshen, Charles Stone and Jerome Friedman. In addition, he has provided consulting services on a number of biomedical and market research projects, which have sparked further innovations in the CART program and methodology.

Dr. Steinberg received his Ph.D. in Economics from Harvard University, and has given full day presentations on data mining for the American Marketing Association, the Direct Marketing Association and the American Statistical Association. After earning a PhD in Econometrics at Harvard Steinberg began his professional career as a Member of the Technical Staff at Bell Labs, Murray Hill, and then as Assistant Professor of Economics at the University of California, San Diego. A book he co-authored on Classification and Regression Trees was awarded the 1999 Nikkei Quality Control Literature Prize in Japan for excellence in statistical literature promoting the improvement of industrial quality control and management.

His consulting experience at Salford Systems has included complex modeling projects for major banks worldwide, including Citibank, Chase, American Express, Credit Suisse, and has included projects in Europe, Australia, New Zealand, Malaysia, Korea, Japan and Brazil. Steinberg led the teams that won first place awards in the KDDCup 2000, and the 2002 Duke/TeraData Churn modeling competition, and the teams that won awards in the PAKDD competitions of 2006 and 2007. He has published papers in economics, econometrics, computer science journals, and contributes actively to the ongoing research and development at Salford.

Careers in #Rstats

I saw a posting for career with Revolution Analytics. Now I am probably on the wrong side of a H1 visa and the C,R skill-o-meter, but these look great for any aspiring R coder. Includes one free lance opp as well.

http://www.revolutionanalytics.com/aboutus/careers.php

We have many opportunities opening up—among them:

Job Title Location
Pre-sales Consultants / Technical Sales Palo Alto, CA
Parallel Computing Developer Palo Alto, CA or Seattle, WA
R Programmer (Freelance) Palo Alto, CA
Software Training Course Developer (Freelance) Palo Alto, CA
Build / Release Engineer Seattle, WA
QA Engineer Seattle, WA
Technical Writer Seattle, WA

 

Please send your resume to careers@revolutionanalytics.com

2) Indeed.com

Searching for “R” jobs and not just , R jobs, gives better results in search engines and job sites. It is still a tough keyword to search but it is getting better.

You can use this RSS feed http://www.indeed.co.in/rss?q=%22R%22++analytics+jobs or send by email option to get alerts

3) http://icrunchdata.com/

 

I Crunch Data has a good number of Analytics Jobs, and again using the keyword as R within quotes of “R” you can see lots of jobs here

http://www.icrunchdata.com/ViewJob.aspx?id=334914&keys=%22R%22

There used to be a Google Group on R jobs, but is too low volume compared to the actual number of R jobs out there.

Note the big demand is for analytics, and knowing more than one platform helps you in the job search than knowing just a single language.

 

 

 

Interview Eberhard Miethke and Dr. Mamdouh Refaat, Angoss Software

Here is an interview with Eberhard Miethke and Dr. Mamdouh Refaat, of Angoss Software. Angoss is a global leader in delivering business intelligence software and predictive analytics solutions that help businesses capitalize on their data by uncovering new opportunities to increase sales and profitability and to reduce risk.

Ajay-  Describe your personal journey in software. How can we guide young students to pursue more useful software development than just gaming applications.

 Mamdouh- I started using computers long time ago when they were programmed using punched cards! First in Fortran, then C, later C++, and then the rest. Computers and software were viewed as technical/engineering tools, and that’s why we can still see the heavy technical orientation of command languages such as Unix shells and even in the windows Command shell. However, with the introduction of database systems and Microsoft office apps, it was clear that business will be the primary user and field of application for software. My personal trip in software started with scientific applications, then business and database systems, and finally statistical software – which you can think of it as returning to the more scientific orientation. However, with the wide acceptance of businesses of the application of statistical methods in different fields such as marketing and risk management, it is a fast growing field that in need of a lot of innovation.

Ajay – Angoss makes multiple data mining and analytics products. could you please introduce us to your product portfolio and what specific data analytics need they serve.

a- Attached please find our main product flyers for KnowledgeSTUDIO and KnowledgeSEEKER. We have a 3rd product called “strategy builder” which is an add-on to the decision tree modules. This is also described in the flyer.

(see- Angoss Knowledge Studio Product Guide April2011  and http://www.scribd.com/doc/63176430/Angoss-Knowledge-Seeker-Product-Guide-April2011  )

Ajay-  The trend in analytics is for big data and cloud computing- with hadoop enabling processing of massive data sets on scalable infrastructure. What are your plans for cloud computing, tablet based as well as mobile based computing.

a- This is an area where the plan is still being figured out in all organizations. The current explosion of data collected from mobile phones, text messages, and social websites will need radically new applications that can utilize the data from these sources. Current applications are based on the relational database paradigm designed in the 70’s through the 90’s of the 20th century.

But data sources are generating data in volumes and formats that are challenging this paradigm and will need a set of new tools and possibly programming languages to fit these needs. The cloud computing, tablet based and mobile computing (which are the same thing in my opinion, just different sizes of the device) are also two technologies that have not been explored in analytics yet.

The approach taken so far by most companies, including Angoss, is to rely on new xml-based standards to represent data structures for the particular models. In this case, it is the PMML (predictive modelling mark-up language) standard, in order to allow the interoperability between analytics applications. Standardizing on the representation of models is viewed as the first step in order to allow the implementation of these models to emerging platforms, being that the cloud or mobile, or social networking websites.

The second challenge cited above is the rapidly increasing size of the data to be analyzed. Angoss has already identified this challenge early on and is currently offering in-database analytics drivers for several database engines: Netezza, Teradata and SQL Server.

These drivers allow our analytics products to translate their routines into efficient SQL-based scripts that run in the database engine to exploit its performance as well as the powerful hardware on which it runs. Thus, instead of copying the data to a staging format for analytics, these drivers allow the data to be analyzed “in-place” within the database without moving it.

Thus offering performance, security and integrity. The performance is improved because of the use of the well tuned database engines running on powerful hardware.

Extra security is achieved by not copying the data to other platforms, which could be less secure. And finally, the integrity of the results are vastly improved by making sure that the results are always obtained by analyzing the up-to-date data residing in the database rather than an older copy of the data which could be obsolete by the time the analysis is concluded.

Ajay- What are the principal competing products to your offerings, and what makes your products special or differentiated in value to them (for each customer segment).

a- There are two major players in today’s market that we usually encounter as competitors, they are: SAS and IBM.

SAS offers a data mining workbench in the form of SAS Enterprise Miner, which is closely tied to SAS data mining methodology known as SEMMA.

On the other hand, IBM has recently acquired SPSS, which offered its Clementine data mining software. IBM has now rebranded Clementine as IBM SPSS Modeller.

In comparison to these products, our KnowledgeSTUDIO and KnowledgeSEEKER offer three main advantages: ease of use; affordability; and ease of integration into existing BI environments.

Angoss products were designed to look-and-feel-like popular Microsoft office applications. This makes the learning curve indeed very steep. Typically, an intermediate level analyst needs only 2-3 days of training to become proficient in the use of the software with all its advanced features.

Another important feature of Angoss software products is their integration with SAS/base product, and SQL-based database engines. All predictive models generated by Angoss can be automatically translated to SAS and SQL scripts. This allows the generation of scoring code for these common platforms. While the software interface simplifies all the tasks to allow business users to take advantage of the value added by predictive models, the software includes advanced options to allow experienced statisticians to fine-tune their models by adjusting all model parameters as needed.

In addition, Angoss offers a unique product called StrategyBuilder, which allows the analyst to add key performance indicators (KPI’s) to predictive models. KPI’s such as profitability, market share, and loyalty are usually required to be calculated in conjunction with any sales and marketing campaign. Therefore, StrategyBuilder was designed to integrate such KPI’s with the results of a predictive model in order to render the appropriate treatment for each customer segment. These results are all integrated into a deployment strategy that can also be translated into an execution code in SQL or SAS.

The above competitive features offered by the software products of Angoss is behind its success in serving over 4000 users from over 500 clients worldwide.

Ajay -Describe a major case study where using Angoss software helped save a big amount of revenue/costs by innovative data mining.

a-Rogers Telecommunications Inc. is one of the largest Canadian telecommunications providers, serving over 8.5 million customers and a revenue of 11.1 Billion Canadian Dollars (2009). In 2008, Rogers engaged Angoss in order to help with the problem of ballooning accounts receivable for a period of 18 months.

The problem was approached by improving the efficiency of the call centre serving the collections process by a set of predictive models. The first set of models were designed to find accounts likely to default ahead of time in order to take preventative measures. A second set of models were designed to optimize the call centre resources to focus on delinquent accounts likely to pay back most of the outstanding balance. Accounts that were identified as not likely to pack quickly were good candidates for “Early-out” treatment, by forwarding them directly to collection agencies. Angoss hosted Rogers’ data and provided on a regular interval the lists of accounts for each treatment to be deployed by the call centre dialler. As a result of this Rogers estimated an improvement of 10% of the collected sums.

Biography-

Mamdouh has been active in consulting, research, and training in various areas of information technology and software development for the last 20 years. He has worked on numerous projects with major organizations in North America and Europe in the areas of data mining, business analytics, business analysis, and engineering analysis. He has held several consulting positions for solution providers including Predict AG in Basel, Switzerland, and as ANGOSS Corp. Mamdouh is the Director of Professional services for EMEA region of ANGOSS Software. Mamdouh received his PhD in engineering from the University of Toronto and his MBA from the University of Leeds, UK.

Mamdouh is the author of:

"Credit Risk Scorecards: Development and Implmentation using SAS"
 "Data Preparation for Data Mining Using SAS",
 (The Morgan Kaufmann Series in Data Management Systems) (Paperback)
 and co-author of
 "Data Mining: Know it all",Morgan Kaufmann



Eberhard Miethke  works as a senior sales executive for Angoss

 

About Angoss-

Angoss is a global leader in delivering business intelligence software and predictive analytics to businesses looking to improve performance across sales, marketing and risk. With a suite of desktop, client-server and in-database software products and Software-as-a-Service solutions, Angoss delivers powerful approaches to turn information into actionable business decisions and competitive advantage.

Angoss software products and solutions are user-friendly and agile, making predictive analytics accessible and easy to use.