Analytics 2012 Conference

from http://www.sas.com/events/analytics/us/index.html

Analytics 2012 Conference

SAS and more than 1,000 analytics experts gather at

Caesars Palace

Analytics 2012 Conference Details

Pre-Conference Workshops – Oct 7
Conference – Oct 8-9
Post-Conference Training – Oct 10-12
Caesars Palace, Las Vegas

Keynote Speakers

The following are confirmed keynote speakers for Analytics 2012. Since he co-founded SAS in 1976, Jim Goodnight has served as the company’s Chief Executive Officer.

Dr. William Hakes is the CEO and co-founder of Link Analytics, an analytical technology company focused on mobile, energy and government verticals.

Tim Rey Tim Rey has written over 100 internal papers, published 21 external papers, and delivered numerous keynote presentations and technical talks at various quantitative methods forums. Recently he has co-chaired both forecasting and data mining conferences. He is currently in the process of co-writing a book, Applied Data Mining for Forecasting.

http://www.sas.com/events/analytics/us/train.html

Pre-Conference

Plan to come to Analytics 2012 a day early and participate in one of the pre-conference workshops or take a SAS Certification exam. Prices for all of the preconference workshops, except for SAS Sentiment Analysis Studio: Introduction to Building Models and the Business Analytics Consulting Workshops, are included in the conference package pricing. You will be prompted to select your pre-conference training options when you register.

Sunday Morning Workshop

SAS Sentiment Analysis Studio: Introduction to Building Models

This course provides an introduction to SAS Sentiment Analysis Studio. It is designed for system designers, developers, analytical consultants and managers who want to understand techniques and approaches for identifying sentiment in textual documents.
View outline
Sunday, Oct. 7, 8:30a.m.-12p.m. – $250

Sunday Afternoon Workshops

Business Analytics Consulting Workshops

This workshop is designed for the analyst, statistician, or executive who wants to discuss best-practice approaches to solving specific business problems, in the context of analytics. The two-hour workshop will be customized to discuss your specific analytical needs and will be designed as a one-on-one session for you, including up to five individuals within your company sharing your analytical goal. This workshop is specifically geared for an expert tasked with solving a critical business problem who needs consultation for developing the analytical approach required. The workshop can be customized to meet your needs, from a deep-dive into modeling methods to a strategic plan for analytic initiatives. In addition to the two hours at the conference location, this workshop includes some advanced consulting time over the phone, making it a valuable investment at a bargain price.
View outline
Sunday, Oct. 7; 1-3 p.m. or 3:30-5:30 p.m. – $200

Demand-Driven Forecasting: Sensing Demand Signals, Shaping and Predicting Demand

This half-day lecture teaches students how to integrate demand-driven forecasting into the consensus forecasting process and how to make the current demand forecasting process more demand-driven.
View outline
Sunday, Oct. 7; 1-5 p.m.

Forecast Value Added Analysis

Forecast Value Added (FVA) is the change in a forecasting performance metric (such as MAPE or bias) that can be attributed to a particular step or participant in the forecasting process. FVA analysis is used to identify those process activities that are failing to make the forecast any better (or might even be making it worse). This course provides step-by-step guidelines for conducting FVA analysis – to identify and eliminate the waste, inefficiency, and worst practices from your forecasting process. The result can be better forecasts, with fewer resources and less management time spent on forecasting.
View outline
Sunday, Oct. 7; 1-5 p.m.

SAS Enterprise Content Categorization: An Introduction

This course gives an introduction to methods of unstructured data analysis, document classification and document content identification. The course also uses examples as the basis for constructing parse expressions and resulting entities.
View outline
Sunday, Oct. 7; 1-5 p.m.

Introduction to Data Mining and SAS Enterprise Miner

This course serves as an introduction to data mining and SAS Enterprise Miner for Desktop software. It is designed for data analysts and qualitative experts as well as those with less of a technical background who want a general understanding of data mining.
View outline
Sunday, Oct. 7, 1-5 p.m.

Modeling Trend, Cycles, and Seasonality in Time Series Data Using PROC UCM

This half-day lecture teaches students how to model, interpret, and predict time series data using UCMs. The UCM procedure analyzes and forecasts equally spaced univariate time series data using the unobserved components models (UCM). This course is designed for business analysts who want to analyze time series data to uncover patterns such as trend, seasonal effects, and cycles using the latest techniques.
View outline
Sunday, Oct. 7, 1-5 p.m.

SAS Rapid Predictive Modeler

This seminar will provide a brief introduction to the use of SAS Enterprise Guide for graphical and data analysis. However, the focus will be on using SAS Enterprise Guide and SAS Enterprise Miner along with the Rapid Predictive Modeling component to build predictive models. Predictive modeling will be introduced using the SEMMA process developed with the introduction of SAS Enterprise Miner. Several examples will be used to illustrate the use of the Rapid Predictive Modeling component, and interpretations of the model results will be provided.
View outline
Sunday, Oct. 7, 1-5 p.m

RCOMM 2012 goes live in August

An awesome conference by an awesome software Rapid Miner remains one of the leading enterprise grade open source software , that can help you do a lot of things including flow driven data modeling ,web mining ,web crawling etc which even other software cant.

Presentations include:

Mining Machine 2 Machine Data (Katharina Morik, TU Dortmund University)
Handling Big Data (Andras Benczur, MTA SZTAKI)
Introduction of RapidAnalytics at Telenor (Telenor and United Consult)
and more

Here is a list of complete program

Program

Time Slot	Tuesday Training / Workshop 1	Wednesday Conference 1	Thursday Conference 2	Friday Training / Workshop 2
09:00 – 10:30		Introductory Speech Ingo Mierswa (Rapid-I)Resource-aware Data Mining or M2M Mining (Invited Talk) Katharina Morik (TU Dortmund University) More information Data Analysis NeurophRM: Integration of the Neuroph framework into RapidMiner Miloš Jovanović, Jelena Stojanović, Milan Vukićević, Vera Stojanović, Boris Delibašić (University of Belgrade)	To be announced (Invited Talk) Andras Benczur Recommender Systems Extending RapidMiner with Recommender Systems Algorithms Matej Mihelčić, Nino Antulov-Fantulin, Matko Bošnjak, Tomislav Šmuc (Ruđer Bošković Institute) Implementation of User Based Collaborative Filtering in RapidMiner Sérgio Morais, Carlos Soares (Universidade do Porto)	Parallel Training / Workshop Session Advanced Data Mining and Data Transformations or Development Workshop Part 2
10:30 – 11:00		Coffee Break	Coffee Break	Coffee Break
11:00 – 12:30		Data Analysis Nearest-Neighbor and Clustering based Anomaly Detection Algorithms for RapidMiner Mennatallah Amer, Markus Goldstein (DFKI) Customers’ LifeStyle Targeting on Big Data using Rapid Miner Maksim Drobyshev (LifeStyle Marketing Ltd) Robust GPGPU Plugin Development for RapidMiner Andor Kovács, Zoltán Prekopcsák (Budapest University of Technology and Economics)	Extensions Optimization Plugin For RapidMiner Venkatesh Umaashankar, Sangkyun Lee (TU Dortmund University; presented by Hendrik Blom) Image Mining Extension – Year After Radim Burget, Václav Uher, Jan Mašek (Brno University of Technology) Incorporating R Plots into RapidMiner Reports Peter Jeszenszky (University of Debrecen)
12:30 – 13:30		Lunch	Lunch	Lunch
13:30 – 15:30	Parallel Training / Workshop Session Basic Data Mining and Data Transformations or Development Workshop Part 1	Applications Introduction of RapidAnalyticy Enterprise Edition at Telenor Hungary t.b.a. (Telenor Hungary and United Consult) Application of RapidMiner in Steel Industry Research and Development Bengt-Henning Maas, Hakan Koc, Martin Bretschneider (Salzgitter Mannesmann Forschung) A Comparison of Data-driven Models for Forecast River Flow Milan Cisty, Juraj Bezak (Slovak University of Technology) Portfolio Optimization Using Local Linear Regression Ensembles in Rapid Miner Gábor Nagy, Tamás Henk, Gergő Barta (Budapest University of Technology and Economics)	Extensions An Octave Extension for RapidMiner Sylvain Marié (Schneider Electric) Unstructured Data Processing Data Streams with the RapidMiner Streams-Plugin Christian Bockermann, Hendrik Blom (TU Dortmund) Automated Creation of Corpuses for the Needs of Sentiment Analysis Peter Koncz, Jan Paralic (Technical University of Kosice) Demonstration: News from the Rapid-I Labs Simon Fischer; Rapid-I This short session demonstrates the latest developments from the Rapid-I lab and will let you how you can build powerful analysis processes and routines by using those RapidMiner tools.	Certification Exam
15:30 – 16:00	Coffee Break	Coffee Break	Coffee Break
16:00 – 18:00		Book Presentation and Game Show Data Mining for the Masses: A New Textbook on Data Mining for Everyone Matthew North (Washington & Jefferson College) Matthew North presents his new book “Data Mining for the Masses” introducing data mining to a broader audience and making use of RapidMiner for practical data mining problems. Game Show Did you miss last years’ game show “Who wants to be a data miner?”? Use RapidMiner for problems it was never created for and beat the time and other contestants!	User Support Get some Coffee for free – Writing Operators with RapidMiner Beans Christian Bockermann, Hendrik Blom (TU Dortmund) Meta-Modeling Execution Times of RapidMiner operators Matija Piškorec, Matko Bošnjak, Tomislav Šmuc (Ruđer Bošković Institute) Conference day ends at ca. 17:00.
19:30		Social Event (Conference Dinner)	Social Event (Visit of Bar District)

and you should have a look at https://rapid-i.com/rcomm2012f/index.php?option=com_content&view=article&id=65

Conference is in Budapest, Hungary,Europe.

( Disclaimer- Rapid Miner is an advertising sponsor of Decisionstats.com in case you didnot notice the two banner sized ads.)

Interview Rob J Hyndman Forecasting Expert #rstats

Here is an interview with Prof Rob J Hyndman who has created many time series forecasting methods and authored books as well as R packages on the same.

Ajay -Describe your journey from being a student of science to a Professor. What were some key turning points along that journey?

Rob- I started a science honours degree at the University of Melbourne in 1985. By the end of 1985 I found myself simultaneously working as a statistical consultant (having completed all of one year of statistics courses!). For the next three years I studied mathematics, statistics and computer science at university, and tried to learn whatever I needed to in order to help my growing group of clients. Often we would cover things in classes that I’d already taught myself through my consulting work. That really set the trend for the rest of my career. I’ve always been an academic on the one hand, and a statistical consultant on the other. The consulting work has led me to learn a lot of things that I would not otherwise have come across, and has also encouraged me to focus on research problems that are of direct relevance to the clients I work with.

I never set out to be an academic. In fact, I thought that I would get a job in the business world as soon as I finished my degree. But once I completed the degree, I was offered a position as a statistical consultant within the University of Melbourne, helping researchers in various disciplines and doing some commercial work. After a year, I was getting bored doing only consulting, and I thought it would be interesting to do a PhD. I was lucky enough to be offered a generous scholarship which meant I was paid more to study than to continue working.

Again, I thought that I would probably go and get a job in the business world after I finished my PhD. But I finished it early and my scholarship was going to be cut off once I submitted my thesis. So instead, I offered to teach classes for free at the university and delayed submitting my thesis until the scholarship period ran out. That turned out to be a smart move because the university saw that I was a good teacher, and offered me a lecturing position starting immediately I submitted my thesis. So I sort of fell into an academic career.

I’ve kept up the consulting work part-time because it is interesting, and it gives me a little extra money. But I’ve also stayed an academic because I love the freedom to be able to work on anything that takes my fancy.

Ajay- Describe your upcoming book on Forecasting.

Rob- My first textbook on forecasting (with Makridakis and Wheelwright) was written a few years after I finished my PhD. It has been very popular, but it costs a lot of money (about $140 on Amazon). I estimate that I get about $1 for every book sold. The rest goes to the publisher (Wiley) and all they do is print, market and distribute it. I even typeset the whole thing myself and they print directly from the files I provided. It is now about 15 years since the book was written and it badly needs updating. I had a choice of writing a new edition with Wiley or doing something completely new. I decided to do a new one, largely because I didn’t want a publisher to make a lot of money out of students using my hard work.

It seems to me that students try to avoid buying textbooks and will search around looking for suitable online material instead. Often the online material is of very low quality and contains many errors.

As I wasn’t making much money on my textbook, and the facilities now exist to make online publishing very easy, I decided to try a publishing experiment. So my new textbook will be online and completely free. So far it is about 2/3 completed and is available at http://otexts.com/fpp/. I am hoping that my co-author (George Athanasopoulos) and I will finish it off before the end of 2012.

The book is intended to provide a comprehensive introduction to forecasting methods. We don’t attempt to discuss the theory much, but provide enough information for people to use the methods in practice. It is tied to the forecast package in R, and we provide code to show how to use the various forecasting methods.

The idea of online textbooks makes a lot of sense. They are continuously updated so if we find a mistake we fix it immediately. Also, we can add new sections, or update parts of the book, as required rather than waiting for a new edition to come out. We can also add richer content including video, dynamic graphics, etc.

For readers that want a print edition, we will be aiming to produce a print version of the book every year (available via Amazon).

I like the idea so much I’m trying to set up a new publishing platform (otexts.com) to enable other authors to do the same sort of thing. It is taking longer than I would like to make that happen, but probably next year we should have something ready for other authors to use.

Ajay- How can we make textbooks cheaper for students as well as compensate authors fairly

Rob- Well free is definitely cheaper, and there are a few businesses trying to make free online textbooks a reality. Apart from my own efforts, http://www.flatworldknowledge.com/ is producing a lot of free textbooks. And textbookrevolution.org is another great resource.

With otexts.com, we will compensate authors in two ways. First, the print versions of a book will be sold (although at a vastly cheaper rate than other commercial publishers). The royalties on print sales will be split 50/50 with the authors. Second, we plan to have some features of each book available for subscription only (e.g., solutions to exercises, some multimedia content, etc.). Again, the subscription fees will be split 50/50 with the authors.

Ajay- Suppose a person who used to use forecasting software from another company decides to switch to R. How easy and lucid do you think the current documentation on R website for business analytics practitioners such as these – in the corporate world.

Rob- The documentation on the R website is not very good for newcomers, but there are a lot of other R resources now available. One of the best introductions is Matloff’s “The Art of R Programming”. Provided someone has done some programming before (e.g., VBA, python or java), learning R is a breeze. The people who have trouble are those who have only ever used menu interfaces such as Excel. Then they are not only learning R, but learning to think about computing in a different way from what they are used to, and that can be tricky. However, it is well worth it. Once you know how to code, you can do so much more. I wish some basic programming was part of every business and statistics degree.

If you are working in a particular area, then it is often best to find a book that uses R in that discipline. For example, if you want to do forecasting, you can use my book (otexts.com/fpp/). Or if you are using R for data visualization, get hold of Hadley Wickham’s ggplot2 book.

Ajay- In a long and storied career- What is the best forecast you ever made ? and the worst?

Rob- Actually, my best work is not so much in making forecasts as in developing new forecasting methodology. I’m very proud of my forecasting models for electricity demand which are now used for all long-term planning of electricity capacity in Australia (see http://robjhyndman.com/papers/peak-electricity-demand/ for the details). Also, my methods for population forecasting (http://robjhyndman.com/papers/stochastic-population-forecasts/ ) are pretty good (in my opinion!). These methods are now used by some national governments (but not Australia!) for their official population forecasts.

Of course, I’ve made some bad forecasts, but usually when I’ve tried to do more than is reasonable given the available data. One of my earliest consulting jobs involved forecasting the sales for a large car manufacturer. They wanted forecasts for the next fifteen years using less than ten years of historical data. I should have refused as it is unreasonable to forecast that far ahead using so little data. But I was young and naive and wanted the work. So I did the forecasts, and they were clearly outside the company’s (reasonable) expectations, and they then refused to pay me. Lesson learned. It’s better to refuse work than do it poorly.

Probably the biggest impact I’ve had is in helping the Australian government forecast the national health budget. In 2001 and 2002, they had underestimated health expenditure by nearly $1 billion in each year which is a lot of money to have to find, even for a national government. I was invited to assist them in developing a new forecasting method, which I did. The new method has forecast errors of the order of plus or minus $50 million which is much more manageable. The method I developed for them was the basis of the ETS models discussed in my 2008 book on exponential smoothing (www.exponentialsmoothing.net)

. And now anyone can use the method with the ets() function in the forecast package for R.

About-

Rob J Hyndman is Professor of Statistics in the Department of Econometrics and Business Statistics at Monash University and Director of the Monash University Business & Economic Forecasting Unit. He is also Editor-in-Chief of the International Journal of Forecasting and a Director of the International Institute of Forecasters. Rob is the author of over 100 research papers in statistical science. In 2007, he received the Moran medal from the Australian Academy of Science for his contributions to statistical research, especially in the area of statistical forecasting. For 25 years, Rob has maintained an active consulting practice, assisting hundreds of companies and organizations. His recent consulting work has involved forecasting electricity demand, tourism demand, the Australian government health budget and case volume at a US call centre.

Rapid Miner User Conference 2012

One of those cool conferences that is on my bucket list- this time in Hungary (That’s a nice place)

But I am especially interested in seeing how far Radoop has come along !

Disclaimer- Rapid Miner has been a Decisionstats.com sponsor for many years. It is also a very cool software but I like the R Extension facility even more!

—————————————————————

and not very expensive too compared to other User Conferences in Europe!-

http://rcomm2012.org/index.php/registration/prices

Information about Registration

Early Bird registration until July 20th, 2012.
Normal registration from July 21st, 2012 until August 13th, 2012.
Latest registration from August 14th, 2012 until August 24th, 2012.
Students have to provide a valid Student ID during registration.
The Dinner is included in the All Days and in the Conference packages.
All prices below are net prices. Value added tax (VAT) has to be added if applicable.

Prices for Regular Visitors

Days and Event	Early Bird Rate	Normal Rate	Latest Registration
Tuesday (Training / Development 1)	190 Euro	230 Euro	280 Euro
Wednesday + Thursday (Conference)	290 Euro	350 Euro	420 Euro
Friday (Training / Development 2 and Exam)	190 Euro	230 Euro	280 Euro
All Days *(Full Package)*	610 Euro	740 Euro	900 Euro

Prices for Authors and Students

In case of students, please note that you will have to provide a valid student ID during registration.

Days and Event	Early Bird Rate	Normal Rate	Latest Registration
Tuesday (Training / Development 1)	90 Euro	110 Euro	140 Euro
Wednesday + Thursday (Conference)	140 Euro	170 Euro	210 Euro
Friday (Training / Development 2 and Exam)	90 Euro	110 Euro	140 Euro
All Days *(Full Package)*	290 Euro	350 Euro	450 Euro

http://rcomm2012.org/index.php/program

Program

Time Slot	Tuesday Training / Workshop 1	Wednesday Conference 1	Thursday Conference 2	Friday Training / Workshop 2
09:00 – 10:30		Introductory Speech Ingo Mierswa; Rapid-I Data Analysis NeurophRM: Integration of the Neuroph framework into RapidMiner Miloš Jovanović, Jelena Stojanović, Milan Vukićević, Vera Stojanović, Boris Delibašić (University of Belgrade)	To be announced (Invited Talk) To be announced Recommender Systems Extending RapidMiner with Recommender Systems Algorithms Matej Mihelčić, Nino Antulov-Fantulin, Matko Bošnjak, Tomislav Šmuc (Ruđer Bošković Institute) Implementation of User Based Collaborative Filtering in RapidMiner Sérgio Morais, Carlos Soares (Universidade do Porto)	Parallel Training / Workshop Session Advanced Data Mining and Data Transformations or Development Workshop Part 2
10:30 – 12:30		Data Analysis Nearest-Neighbor and Clustering based Anomaly Detection Algorithms for RapidMiner Mennatallah Amer, Markus Goldstein (DFKI) Customers’ LifeStyle Targeting on Big Data using Rapid Miner Maksim Drobyshev (LifeStyle Marketing Ltd) Robust GPGPU Plugin Development for RapidMiner Andor Kovács, Zoltán Prekopcsák (Budapest University of Technology and Economics)	Extensions Image Mining Extension – Year After Radim Burget, Václav Uher, Jan Mašek (Brno University of Technology) Incorporating R Plots into RapidMiner Reports Peter Jeszenszky (University of Debrecen) An Octave Extension for RapidMiner Sylvain Marié (Schneider Electric)
12:30 – 13:30		Lunch	Lunch	Lunch
13:30 – 15:00	Parallel Training / Workshop Session Basic Data Mining and Data Transformations or Development Workshop Part 1	Applications Application of RapidMiner in Steel Industry Research and Development Bengt-Henning Maas, Hakan Koc, Martin Bretschneider (Salzgitter Mannesmann Forschung) A Comparison of Data-driven Models for Forecast River Flow Milan Cisty, Juraj Bezak (Slovak University of Technology) Portfolio Optimization Using Local Linear Regression Ensembles in Rapid Miner Gábor Nagy, Tamás Henk, Gergő Barta (Budapest University of Technology and Economics)	Unstructured Data Processing Data Streams with the RapidMiner Streams-Plugin Christian Bockermann, Hendrik Blom (TU Dortmund) Automated Creation of Corpuses for the Needs of Sentiment Analysis Peter Koncz, Jan Paralic (Technical University of Kosice) Demonstration News from the Rapid-I Labs Simon Fischer; Rapid-I This short session demonstrates the latest developments from the Rapid-I lab and will let you how you can build powerful analysis processes and routines by using those RapidMiner tools.	Certification Exam
15:00 – 17:00		Book Presentation and Game Show Data Mining for the Masses: A New Textbook on Data Mining for Everyone Matthew North (Washington & Jefferson College) Matthew North presents his new book “Data Mining for the Masses” introducing data mining to a broader audience and making use of RapidMiner for practical data mining problems. Game Show Did you miss last years’ game show “Who wants to be a data miner?”? Use RapidMiner for problems it was never created for and beat the time and other contestants!	User Support Get some Coffee for free – Writing Operators with RapidMiner Beans Christian Bockermann, Hendrik Blom (TU Dortmund) Meta-Modeling Execution Times of RapidMiner operators Matija Piškorec, Matko Bošnjak, Tomislav Šmuc (Ruđer Bošković Institute)
19:00		Social Event (Conference Dinner)	Social Event (Visit of Bar District)

Training: Basic Data Mining and Data Transformations

This is a short introductory training course for users who are not yet familiar with RapidMiner or only have a few experiences with RapidMiner so far. The topics of this training session include

Basic Usage
- User Interface
- Creating and handling RapidMiner repositories
- Starting a new RapidMiner project
- Operators and processes
- Loading data from flat files
- Storing data, processes, and results
Predictive Models
- Linear Regression
- Naïve Bayes
- Decision Trees
Basic Data Transformations
- Changing names and roles
- Handling missing values
- Changing value types by discretization and dichotimization
- Normalization and standardization
- Filtering examples and attributes
Scoring and Model Evaluation
- Applying models
- Splitting data
- Evaluation methods
- Performance criteria
- Visualizing Model Performance

Training: Advanced Data Mining and Data Transformations

This is a short introductory training course for users who already know some basic concepts of RapidMiner and data mining and have already used the software before, for example in the first training on Tuesday. The topics of this training session include

Advanced Data Handling
- Sampling
- Balancing data
- Joins and Aggregations
- Detection and removal of outliers
- Dimensionality reduction
Control process execution
- Remember process results
- Recall process results
- Loops
- Using branches and conditions
- Exception handling
- Definition of macros
- Usage of macros
- Definition of log values
- Clearing log tables
- Transforming log tables to data

Development Workshop Part 1 and Part 2

Want to exchange ideas with the developers of RapidMiner? Or learn more tricks for developing own operators and extensions? During our development workshops on Tuesday and Friday, we will build small groups of developers each working on a small development project around RapidMiner. Beginners will get a comprehensive overview of the architecture of RapidMiner before making the first steps and learn how to write own operators. Advanced developers will form groups with our experienced developers, identify shortcomings of RapidMiner and develop a new extension which might be presented during the conference already. Unfinished work can be continued in the second workshop on Friday before results might be published on the Marketplace or can be taken home as a starting point for new custom operators.