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Analytics 2012 Conference
SAS and more than 1,000 analytics experts gather at
Analytics 2012 Conference Details
Pre-Conference Workshops – Oct 7
Conference – Oct 8-9
Post-Conference Training – Oct 10-12
Caesars Palace, Las Vegas
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 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.
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.
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.
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.
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.
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.
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.
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.
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.
Sunday, Oct. 7, 1-5 p.m
I am mostly language agnostic, though I dislike shoddy design in software (like SAS Enterprise Guide), shoddy websites (like the outdated designed of
site) , and dishonest marketing in inventing buzz words (or as they say — excessively dishonest marketing).
At the same time I love nicely designed software (Rattle,Rapid Miner, JMP), great websites for software (like
) and suitably targeted marketing (like IBM’s) and appreciate intellectual honesty in a field where honest men are rare to find (
I digress- Here are some papers I find interesting to read.
I have been busy-
1) Finally my divorce came through. My advice – dont do it without a pre-nup ! Alimony means all the money.
2) Spending time on Quora after getting bored from LinkedIn, Twitter,Facebook,Google Plus,Tumblr, WordPress
See this answer to-
1) we will change the world
2) if we get 1% of a billion people market, we will be rich
3) if we have got funding, most of the job is done
4) lets pay ourselves high salaries since we got funded
5) our idea is awesome and cant be copied, improvised, stolen, replicated
6) startups are painless
7) it is a better life than a corporate career
8) long term vision is important than short term cash burn
9) we will never sell out or exit. never
10) its a great idea to make startups with friend
Say hello to me – http://www.quora.com/Ajay-Ohri/answers
3) Writing freelance articles on APIs for Programmable Web
Why write pro? See point 1)
4) Writing poetry on http://poemsforkush.com/. It now gets 23000 views a month. I wish I could say my poems were great, but the readers are kind (364 subscribers!) and also Google Image Search is very very kind.
5) Kicking tires with next book ” R for Cloud Computing” and be tuned for another writing announcement
6) Waiting for Paul Kent, VP, SAS Big Data to reply to my emails for interview after HE promised me!! You dont get to 105 interviews without being a bit stubborn!
7) Sighing on politics engulfing my American friends especially with regards to Chic-fil-A and Romney’s gaffes. Now thats what I call a first world problem! Protesting by eating or boycotting chicken sandwiches! In India we had the world’s biggest blackout two days in a row- and no one is attending the Hunger Fast against corruption protests!
8) Watching Olympics! Our glorious nation of 1.2 billion very smart people has managed to win 1 Bronze till today!! Michael Phelps has won more medals and more gold than the whole of India has since the Olympics Games began!!
9) Consulting to pay the bills. includes writing R code, making presentations. Why consult when I have writing to do? See point 1)
10) Reading New York Times to get insights on Big Data and Analytics. Trust them- they know what they are doing!
Increasingly Big Data is used in writing where Business Analytics was used, and data mining is thrown in as a word just to keep liberal art majors happy that they are reading a scientific article.
Some Big Words I have noticed in my Short life-
Big Data? High Performance Analytics? High Performance Computing ? Cloud Computing? Time Sharing? Data Mining? SEMMA? CRISP-DM? KDD? Business Intelligence? Business Analytics and Optimization? (pick a card and any card)
(or Just Moore’s Law catching up with the analytics)
Replace Big Data with Analytics in these articles and let me know if you can make out much of a difference
- Big Data on Campus
- From the man who famously said BI is dead, is now burying Business Analytics within the new buzzword , SAS CMO Jim Davis
How to transform big data from an obstacle into an asset
(Related- Is big data over hyped? by Jim Davis
I am sure by 2015, Jim Davis, NYT and the merry men of analytics will find some other buzzwords to rally the troops. In the meantime, let me throw out the flag and call it Big .
Udacity is a smaller player but welcome competition to Coursera. I think companies that have on demand learning programs should consider donating a course to these online education players (like SAS Institute for SAS , Revolution Analytics for R, SAP, Oracle for in-memory analytics etc)
Coursera is doing a superb job with huge number of free courses from notable professors. 111 courses!
Awesomely informative post on sascom magazine (whose editor I have I interviewed before here at
/ – )
Great piece by Michael Ames ,SAS Data Integration Product Manager.
Also see SAS’s big data thingys here at
Solutions and Capabilities Using SAS® In-Memory Analytics
- High-Performance Analytics – Get near-real-time insights with appliance-ready analytics software designed to tackle big data and complex problems.
- High-Performance Risk – Faster, better risk management decisions based on the most up-to-date views of your overall risk exposure.
- High-Performance Liquidity Risk Management – Take quick, decisive actions to secure adequate funding, especially in times of volatility.
- High-Performance Stress Testing – Make faster, more precise decisions to protect the health of the firm.
- Visual Analytics – Explore big data using in-memory capabilities to better understand all of your data, discover new patterns and publish reports to the Web and iPad®.
(Ajay- I liked the Visual Analytics piece especially for Big Data )