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  )

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.


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.

Analytics 2011 Conference


The Analytics 2011 Conference Series combines the power of SAS’s M2010 Data Mining Conference and F2010 Business Forecasting Conference into one conference covering the latest trends and techniques in the field of analytics. Analytics 2011 Conference Series brings the brightest minds in the field of analytics together with hundreds of analytics practitioners. Join us as these leading conferences change names and locations. At Analytics 2011, you’ll learn through a series of case studies, technical presentations and hands-on training. If you are in the field of analytics, this is one conference you can’t afford to miss.

Conference Details

October 24-25, 2011
Grande Lakes Resort
Orlando, FL

Analytics 2011 topic areas include:

Youtube’s variance in interface/s for sharing

Youtube seems to have a different  interface for sharing a channel, a playlist or an individual song. Also it seems to be missing out on revenue from Itunes (or maybe it isnt). and it seems to promoting Facebook and Twitter to the expense of other social media sharing buttons which can be only seen when you click share more (or maybe the buttons/social media channels change based on sharing activity analytics🙂 )

on a slightly different note read my techie tutorial on boosting your youtube channel views

Creating an Anonymous Bot


See the following interface snapshots/views-

youtube song share expanded
youtube song share expanded


youtube song share
youtube song share default
youtube playlist share
youtube playlist share
utube channel share
youtube channel share

Youtube's variance in interface/s for sharing

Youtube seems to have a different  interface for sharing a channel, a playlist or an individual song. Also it seems to be missing out on revenue from Itunes (or maybe it isnt). and it seems to promoting Facebook and Twitter to the expense of other social media sharing buttons which can be only seen when you click share more (or maybe the buttons/social media channels change based on sharing activity analytics🙂 )

on a slightly different note read my techie tutorial on boosting your youtube channel views

Creating an Anonymous Bot


See the following interface snapshots/views-

youtube song share expanded
youtube song share expanded


youtube song share
youtube song share default
youtube playlist share
youtube playlist share
utube channel share
youtube channel share

Interview David Katz ,Dataspora /David Katz Consulting

Here is an interview with David Katz ,founder of David Katz Consulting ( and an analyst at the noted firm He is a featured speaker at Predictive Analytics World

Ajay-  Describe your background working with analytics . How can we make analytics and science more attractive career options for young students

David- I had an interest in math from an early age, spurred by reading lots of science fiction with mathematicians and scientists in leading roles. I was fortunate to be at Harry and David (Fruit of the Month Club) when they were in the forefront of applying multivariate statistics to the challenge of targeting catalogs and other snail-mail offerings. Later I had the opportunity to expand these techniques to the retail sphere with Williams-Sonoma, who grew their retail business with the support of their catalog mailings. Since they had several catalog titles and product lines, cross-selling presented additional analytic challenges, and with the growth of the internet there was still another channel to consider, with its own dynamics.

After helping to found Abacus Direct Marketing, I became an independent consultant, which provided a lot of variety in applying statistics and data mining in a variety of settings from health care to telecom to credit marketing and education.

Students should be exposed to the many roles that analytics plays in modern life, and to the excitement of finding meaningful and useful patterns in the vast profusion of data that is now available.

Ajay-  Describe your most challenging project in 3 decades of experience in this field.

David- Hard to choose just one, but the educational field has been particularly interesting. Partnering with Olympic Behavior Labs, we’ve developed systems to help identify students who are most at-risk for dropping out of school to help target interventions that could prevent dropout and promote success.

Ajay- What do you think are the top 5 trends in analytics for 2011.

David- Big Data, Privacy concerns, quick response to consumer needs, integration of testing and analysis into business processes, social networking data.

Ajay- Do you think techniques like RFM and LTV are adequately utilized by organization. How can they be propagated further.

David- Organizations vary amazingly in how sophisticated or unsophisticated the are in analytics. A key factor in success as a consultant is to understand where each client is on this continuum and how well that serves their needs.

Ajay- What are the various software you have worked for in this field- and name your favorite per category.

David- I started out using COBOL (that dates me!) then concentrated on SAS for many years. More recently R is my favorite because of its coverage, currency and programming model, and it’s debugging capabilities.

Ajay- Independent consulting can be a strenuous job. What do you do to unwind?

David- Cycling, yoga, meditation, hiking and guitar.


David Katz, Senior Analyst, Dataspora, and President, David Katz Consulting.

David Katz has been in the forefront of applying statistical models and database technology to marketing problems since 1980. He holds a Master’s Degree in Mathematics from the University of California, Berkeley. He is one of the founders of Abacus Direct Marketing and was previously the Director of Database Development for Williams-Sonoma.

He is the founder and President of David Katz Consulting, specializing in sophisticated statistical services for a variety of applications, with a special focus on the Direct Marketing Industry. David Katz has an extensive background that includes experience in all aspects of direct marketing from data mining, to strategy, to test design and implementation. In addition, he consults on a variety of data mining and statistical applications from public health to collections analysis. He has partnered with consulting firms such as Ernst and Young, Prediction Impact, and most recently on this project with Dataspora.

For more on David’s Session in Predictive Analytics World, San Fransisco on (

Room: Salon 5 & 6
4:45pm – 5:05pm

Track 2: Social Data and Telecom 
Case Study: Major North American Telecom
Social Networking Data for Churn Analysis

A North American Telecom found that it had a window into social contacts – who has been calling whom on its network. This data proved to be predictive of churn. Using SQL, and GAM in R, we explored how to use this data to improve the identification of likely churners. We will present many dimensions of the lessons learned on this engagement.

Speaker: David Katz, Senior Analyst, Dataspora, and President, David Katz Consulting

Exhibit Hours
Monday, March 14th:10:00am to 7:30pm

Tuesday, March 15th:9:45am to 4:30pm

Why do bloggers blog ?

Xbox (revision 1.0) internal layout. Including...
Image via Wikipedia

Step 1 is to create internal motivation to create a blog in the first place

Step 2 is to find what to write

Reasons Bloggers Blog-

Basic -Ranting

Examples- I hate Facebook Platform team treats me badly with waits, and breaks my code.

SAS Marketing wont give me  a big discount to make me look good in front of my boss.

Companies  wont give me their software for free- even though I will use it to make money (and not play X Box)

I want my vendors to be FOSS but my customers to switch to SaaS.

Google wont do this- Apple wont do that- Microsoft wont do those.

Revolution would give me 4 great packages but not the open source for RevoScaler (which only 300 people would understand in the first place)


I better kiss the Professor and give a Turkey for dinner, as he sits on my thesis committee.

I will recommend Prof X’s lousy book in the hope he recommends my lousy book as a textbook too.

It is safe to laugh when the boss is making a joke-I should comment on her corporate blog, and retweet her.


I belong to this great online community of smart people. Let me agree to what they say.

I really believe in EVERYTHING that ALL the 2 MILLION members of the community have to say ALL the TIME.

I belong to this online community because all my friends are on my computer.

4 Egositic

My blog page rank is now X plus delta tau because of sugary key words (2004)

My technorati numbers rise (2005)

I was once on Digg (2007)

I have Z * exp N followers on Twitter and even more on Facebook (2008)

My Klout is increasing on twitter, My stack overflow reputation ‘s cup floweth over. (2009)

My Karma on Reddit is more important than my Karma in real life (2010)

Self Actualization-

I got time to kill- and I think I may learn more, meet intersting people and discover something wandering on the internet.

All those who wonder are not lost- Wikiquote

I got a story to tell, poems to write, code to give away. A free  Blog is something a Chinese , an Iranian  and a North korean really really know what the value is.

But after all that, WHY Do Bloggers Blog?

  • Because we are still waiting for Facebook to create the Blog Killer.
  • Its better than saying I am unemployed and a social loner
  • Reddit Karma feels good. Any Karma of any kind.