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
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. Jim Goodnight Since he co-founded SAS in 1976, Jim Goodnight has served as the company’s Chief Executive Officer.

William Hakes 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

The Top Statistical Softwares (GUI)

The list of top Statistical Softwares (GUI) is continued below. You can see the earlier post here

6. R Commander– While initially aimed at being a basic statistics GUI, the tremendous popularity of R Commander and the extensions in the form of plugins has helped make this one of the most widely used GUI. In short if you dont know ANY R, and still want to do basic descriptive stats and modeling this will come in handy- with an added script window for custom code for advanced users and extensions like that for DoE (design of experiments) and QCC (Quality Control) packages the e-plugins are a great way to extend this. I suspect the only thing holding it back is Dr Fox and the rest of R Core’s reluctance to fully embrace GUI as a software medium. You can read his earlier interview here-https://decisionstats.wordpress.com/2009/09/14/interview-professor-john-fox-creator-r-commander/

Technically it is possible to convert just about any package to a GUI menu in R Commander using the e-plugins.

7. SAS GUIs

Enterprise (Guide)

SAS Enterprise Guide was the higher end (and higher priced solution) to enhanced editor’s lack of menu driven commands. It works but many people I know prefer the text editor just as well.


The Enterprise Miner is a separate software and works more like Red R or SPSS Modeler does. Again EM is one of the major DM softwares out there, but the similarity in names is a bit confusing.

Even the Base SAS Enhanced Editor does have some menus for importing data, or querying etc, but it is rarely confused for being a GUI.

8. Oracle Data Miner and Knime

I like both the ODM and Knime but I find the lack of advertising or promotional support puzzling. Both these softwares can do well to combine technical excellence with some marketing. And since they are both free you can check them out yourself here

Oracle Data Mining

You can download it here-(note- the Oracle Web Site itself is a bit aging 🙂 )

http://www.oracle.com/technology/products/bi/odm/odminer.html

Knime is the open source GUI which can be found here-

http://www.knime.org/introduction/features

9. RAwkard

Another R GUI- it stands out on the comprehensive ways you can customize your code in menus rather than writing all or learning by rote the syntax.

From http://sourceforge.net/apps/mediawiki/rkward/index.php?title=Main_Page

you can see it below. I recommend this GUI over other GUIs especially if you are new to R and do more data visualization which needs custom graphics.

10. Red R and R JGR/ Deducer

Red R and RJGR/Deducer are both up and coming GUIs for R. While REd R is R version for Enterprise Miner, Deducer is coming up with a new GUI for ggplot the powerful graphics package in R.

Some GUIs excluded from this list are – Statistica, MatLab, EViews(?) because I dont really work with them, and thought it best to turn them over to someone who knows them better.

Hope this list of GUIs helps you- note most of the softwares can be learnt within a quick hour and two if you know basic software skills/data manipulation so going through the GUI list is a faster way of adding value to your resume/knowledge base as well.