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		<title>Predictive Analytics Interview Dr. Zeller, Zementis</title>
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		<pubDate>Mon, 23 Feb 2009 23:06:21 +0000</pubDate>
		<dc:creator>lowes1</dc:creator>
				<category><![CDATA[Client Deployment]]></category>
		<category><![CDATA[Solution Providers]]></category>

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		<description><![CDATA[Dr. Zeller manages the strategic direction of Zementis, a software company focused on predictive analytics and advanced decisioning technology. In this interview, Dr. Zeller explains how organizations increasingly recognize the value that predictive analytics offers to their business. The complexity of development, integration, and deployment of predictive models, however, is often considered cost-prohibitive for projects. [...]]]></description>
			<content:encoded><![CDATA[<p></p><p>Dr. Zeller manages the strategic direction of Zementis, a software company focused on predictive analytics and advanced decisioning technology.   </p>
<p>In this interview, Dr. Zeller explains how organizations increasingly recognize the value that predictive analytics offers to their business. The complexity of development, integration, and deployment of predictive models, however, is often considered cost-prohibitive for projects. In light of mature open source solutions, open standards, and SOA principles we propose an agile model development life cycle that allows us to quickly leverage predictive analytics in operational environments. </p>
<p>What you will learn:</p>
<p>    * Leverage predictive analytics in real-time<br />
    *Accelerate time-to-market for decision models<br />
    * Reduce cost with SaaS</p>
<p>Transcript:</p>
<p>Bill Cullifer, WOW I am on the phone with Dr. Zeller, CEO of Zementis out of San Diego, California.  Dr. Zeller, good afternoon and thanks for agreeing to the call.</p>
<p>Dr. Zeller:  Thanks for having me on here.  I think excellent educational website.  So, I am glad to contribute.</p>
<p>Bill Cullifer, WOW:  I appreciate that.  You have experience as a computer science fellow and you have been doing predictive analytics for a number of years. You and  have a session coming up on the San Diego Computer… Supercomputer Center High Performance Scoring of Healthcare Data as it relates to predictive analytics.  Can you give us a couple of walk aways from that session?</p>
<p>Dr. Zeller:  Absolutely.  It&#8217;s going to focus on the ease of deployment for predictive analytics, which really is also the core focus of Zementis and our product line.  Taking predictive models that you have developed in various different models and bringing them into a production environment so that any other IT system can easily leverage it, utilize and kind of shorten that time to deployment, time to market predictive analytics.</p>
<p>Bill Cullifer, WOW:  And who exactly benefits from that statement?  Are we talking about the department itself organizationally, what… where is the return on investment?</p>
<p>Dr. Zeller:  Well, the return is really across the enterprise, bringing it into an operational infrastructure and much easier than it has been done in the past.  Most of the time they are great tools for data mining, analysis, and model building, but the main hurdle today actually is really the deployment of predictive analytics and…</p>
<p>Bill Cullifer, WOW:  Yeah, interesting.</p>
<p>Dr. Zeller:  So many companies are not willing or couldn&#8217;t spend you know the time and cost associated with such a project.  So, it has been I think a limiting factor for predictive analytics in general, just not being able to easily move things into a production environment at a reasonable you know very cost effective way.</p>
<p>Bill Cullifer, WOW:  Yeah and how has that changed?</p>
<p>Dr. Zeller:  Well, what we are doing is really leveraging the predictive model markup language (PMML), which is the widely known standard in the industry and supported by really the major industry players.  We are really focusing on open standards and utilizing that in order to transition from any tool, commercial or open source, into our deployment  In addition to that, we actually leverage a new trend that is a very hot topic currently in the industry.  It is called computing.  So, we leverage for example the Amazon Elastic Compute Cloud to deliver our software as a service at a much, much lower cost than you have ever seen that before.  </p>
<p>Bill Cullifer, WOW:  Excellent and that’s a subscription model.</p>
<p>Dr. Zeller:  Correct yeah.  Instead of spending $50000 or $100000 or more on software and hardware licenses, here you can get started at less than a dollar an hour.</p>
<p>Bill Cullifer, WOW:  Excellent and where might people go to get more information Dr. Zeller?</p>
<p>Dr. Zeller:  Our website, www.zementis.com should really give kind of all the details, you can sign up, you can really get started within five minutes, launch your instance and deploy your models and be in production literally within you know a few hours.</p>
<p>Bill Cullifer, WOW:  Excellent.  Sounds really good and Dr. Zeller, we certainly appreciate the information and your time today.</p>
<p>Dr. Zeller:  Very much my pleasure.</p>
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<itunes:duration>00:01:01</itunes:duration>
		<itunes:subtitle>Dr. Zeller manages the strategic direction of Zementis, a software company focused on predictive analytics and advanced decisioning technology.   

In this interview, Dr. ...</itunes:subtitle>
		<itunes:summary>Dr. Zeller manages the strategic direction of Zementis, a software company focused on predictive analytics and advanced decisioning technology.   

In this interview, Dr. Zeller explains how organizations increasingly recognize the value that predictive analytics offers to their business. The complexity of development, integration, and deployment of predictive models, however, is often considered cost-prohibitive for projects. In light of mature open source solutions, open standards, and SOA principles we propose an agile model development life cycle that allows us to quickly leverage predictive analytics in operational environments. 

What you will learn:

    * Leverage predictive analytics in real-time
    *Accelerate time-to-market for decision models
    * Reduce cost with SaaS

Transcript:

Bill Cullifer, WOW I am on the phone with Dr. Zeller, CEO of Zementis out of San Diego, California.  Dr. Zeller, good afternoon and thanks for agreeing to the call.

Dr. Zeller:  Thanks for having me on here.  I think excellent educational website.  So, I am glad to contribute.

Bill Cullifer, WOW:  I appreciate that.  You have experience as a computer science fellow and you have been doing predictive analytics for a number of years. You and  have a session coming up on the San Diego Computerhellip; Supercomputer Center High Performance Scoring of Healthcare Data as it relates to predictive analytics.  Can you give us a couple of walk aways from that session?

Dr. Zeller:  Absolutely.  It's going to focus on the ease of deployment for predictive analytics, which really is also the core focus of Zementis and our product line.  Taking predictive models that you have developed in various different models and bringing them into a production environment so that any other IT system can easily leverage it, utilize and kind of shorten that time to deployment, time to market predictive analytics.

Bill Cullifer, WOW:  And who exactly benefits from that statement?  Are we talking about the department itself organizationally, whathellip; where is the return on investment?

Dr. Zeller:  Well, the return is really across the enterprise, bringing it into an operational infrastructure and much easier than it has been done in the past.  Most of the time they are great tools for data mining, analysis, and model building, but the main hurdle today actually is really the deployment of predictive analytics andhellip;

Bill Cullifer, WOW:  Yeah, interesting.

Dr. Zeller:  So many companies are not willing or couldn't spend you know the time and cost associated with such a project.  So, it has been I think a limiting factor for predictive analytics in general, just not being able to easily move things into a production environment at a reasonable you know very cost effective way.

Bill Cullifer, WOW:  Yeah and how has that changed?

Dr. Zeller:  Well, what we are doing is really leveraging the predictive model markup language (PMML), which is the widely known standard in the industry and supported by really the major industry players.  We are really focusing on open standards and utilizing that in order to transition from any tool, commercial or open source, into our deployment  In addition to that, we actually leverage a new trend that is a very hot topic currently in the industry.  It is called computing.  So, we leverage for example the Amazon Elastic Compute Cloud to deliver our software as a service at a much, much lower cost than you have ever seen that before.  

Bill Cullifer, WOW:  Excellent and thatrsquo;s a subscription model.

Dr. Zeller:  Correct yeah.  Instead of spending $50000 or $100000 or more on software and hardware licenses, here you can get started at less than a dollar an hour.

Bill Cullifer, WOW:  Excellent and where might people go to get more information Dr. Zeller?

Dr. Zeller:  Our website, www.zementis.com should really give kind of all the details, you can sign up, you can really get s...</itunes:summary>
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		<title>Solution Provider Interview-Mary Grace Crissey, Global Marketing Manager for Analytics from SAS.</title>
		<link>http://predictiveanalytics.org/solution-provider-interview-mary-grace-crissey-global-marketing-manager-for-analytics-from-sas.htm</link>
		<comments>http://predictiveanalytics.org/solution-provider-interview-mary-grace-crissey-global-marketing-manager-for-analytics-from-sas.htm#comments</comments>
		<pubDate>Wed, 07 May 2008 18:43:57 +0000</pubDate>
		<dc:creator>lowes1</dc:creator>
				<category><![CDATA[Solution Providers]]></category>
		<category><![CDATA[Predictive Analytics]]></category>
		<category><![CDATA[Predictive Analytics Solutions Providers]]></category>

		<guid isPermaLink="false">http://predictiveanalytics.org/?p=11</guid>
		<description><![CDATA[Today s podcast is a continuation of the coverage of the topic Predictive Analytics, To help us better understand the topic from a solution provider point of view, I interviewed Mary Grace Crissey, Global Marketing Manager for Analytics from SAS.  To listen to the entire interview follow the “click to play” link at the bottom [...]]]></description>
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<p>Today s podcast is a continuation of the coverage of the topic Predictive Analytics, To help us better understand the topic from a solution provider point of view, I interviewed Mary Grace Crissey, Global Marketing Manager for Analytics from SAS.  To listen to the entire interview follow the “click to play” link at the bottom of this post.</p>
<p>Transcript of Interview with Mary Grace Crissey</p>
<p>BILL CULLIFER: Greetings WOW Members and Web Professionals everywhere! Bill Cullifer here with the World Organization of Webmasters (WOW) and the WOW Technology Minute. Today’s podcast is a continuation of a series of podcasts on the subject of predictive analytics. To assist us in better understanding the topic from a solution provider point of view, I’m on the phone with Mary Grace Crissey, Global Marketing Manager for Analytics for SAS. Good afternoon Mary Grace and thanks for agreeing to this interview.</p>
<p>MARY GRACE CRISSEY: Well thank you for inviting me.</p>
<p>BILL: You bet. Mary Grace, SAS recently announced the company supercharges predictive analytics. What exactly do you mean when you write that SAS supercharges predictive analytics? And can you explain to the listeners and the viewers of this podcast what predictive analytics means to you?</p>
<p>MARY: Certainly. Well, the word supercharging was tossed in there because it shows my enthusiasm on this topic here.</p>
<p>BILL: All right.</p>
<p>MARY GRACE: I really am a firm believer that you can get some magical power, some turbo-charge and super-boost out of your day to day business, be it making decisions as an executive leader at the company or as a Web professional designing and promoting your webpage. All of these tasks that are commonly done in businesses today can be supercharged if you take advantage of predictive analytics. So when I say predictive analytics I’m talking about looking forward into the future with a strategic mindset. Analytics is a term that represents numbers and metrics and when you want to find patterns, you’re digging through data that you have collected, say of people who visited your website, or demographics of who these customers are, you can look at historical data and there’s a lot of valuable analytic information that you can find. But when you want to look forward and project onto the future, that’s when you’re talking about predictive analytics.</p>
<p>What was once reserved to say an Ivory Tower of the scientific investigations where the academic analyses were punching and forming and computing these number-crunching, data-mining technique, now it’s catching the eyes of successful business leaders. So armed with this latest technology we can all benefit today from crunching word and numbers at the same time. We can automate manual tasks that used to take a lot of people power and actually make informed, fact-based decisions.</p>
<p>BILL: Excellent. Excellent explanation. I’m curious to know Mary Grace, from your point of view, how much of this is preparation and how much of the process, if you will, is technology?</p>
<p>MARY GRACE: Good question because actually the technology and data-mining is sometimes looked at as one little piece of building a predictive model, but SAS has an enterprise intelligence platform that actually spans from the beginning where you collect the data and where you present the information on the webpage, or Web analytics, and where you make the models and actually where you make the decisions. SAS is talking about a solution which truly does entail consultants and experts, people power, behind the software.</p>
<p>BILL: Excellent. Well said. Thank you so much Mary Grace for your time today and for your terrific explanation of predictive analytics. We appreciate it. Bill Cullifer here with the World Organization of Webmasters (WOW), on the phone with Mary Grace Crissey, Global Marketing Manager for Analytics for SAS. Thanks for your time Mary Grace.</p>
<p>MARY GRACE: You’re welcome.</p>
]]></content:encoded>
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			<enclosure url="http://www.predictiveanalytics.org/predictive-analytics-video-podcast/predictive-analytics-sas-interview.flv" length="1" type="video/flv"/>
<itunes:duration>00:01:01</itunes:duration>
		<itunes:subtitle>Today s podcast is a continuation of the coverage of the topic Predictive Analytics, To help us better understand the topic from a solution provider ...</itunes:subtitle>
		<itunes:summary>Today s podcast is a continuation of the coverage of the topic Predictive Analytics, To help us better understand the topic from a solution provider point of view, I interviewed Mary Grace Crissey, Global Marketing Manager for Analytics from SAS.nbsp; To listen to the entire interview follow the ldquo;click to playrdquo; link at the bottom of this post.

Transcript of Interview with Mary Grace Crissey

BILL CULLIFER: Greetings WOW Members and Web Professionals everywhere! Bill Cullifer here with the World Organization of Webmasters (WOW) and the WOW Technology Minute. Todayrsquo;s podcast is a continuation of a series of podcasts on the subject of predictive analytics. To assist us in better understanding the topic from a solution provider point of view, Irsquo;m on the phone with Mary Grace Crissey, Global Marketing Manager for Analytics for SAS. Good afternoon Mary Grace and thanks for agreeing to this interview.

MARY GRACE CRISSEY: Well thank you for inviting me.

BILL: You bet. Mary Grace, SAS recently announced the company supercharges predictive analytics. What exactly do you mean when you write that SAS supercharges predictive analytics? And can you explain to the listeners and the viewers of this podcast what predictive analytics means to you?

MARY: Certainly. Well, the word supercharging was tossed in there because it shows my enthusiasm on this topic here.

BILL: All right.

MARY GRACE: I really am a firm believer that you can get some magical power, some turbo-charge and super-boost out of your day to day business, be it making decisions as an executive leader at the company or as a Web professional designing and promoting your webpage. All of these tasks that are commonly done in businesses today can be supercharged if you take advantage of predictive analytics. So when I say predictive analytics Irsquo;m talking about looking forward into the future with a strategic mindset. Analytics is a term that represents numbers and metrics and when you want to find patterns, yoursquo;re digging through data that you have collected, say of people who visited your website, or demographics of who these customers are, you can look at historical data and therersquo;s a lot of valuable analytic information that you can find. But when you want to look forward and project onto the future, thatrsquo;s when yoursquo;re talking about predictive analytics.

What was once reserved to say an Ivory Tower of the scientific investigations where the academic analyses were punching and forming and computing these number-crunching, data-mining technique, now itrsquo;s catching the eyes of successful business leaders. So armed with this latest technology we can all benefit today from crunching word and numbers at the same time. We can automate manual tasks that used to take a lot of people power and actually make informed, fact-based decisions.

BILL: Excellent. Excellent explanation. Irsquo;m curious to know Mary Grace, from your point of view, how much of this is preparation and how much of the process, if you will, is technology?

MARY GRACE: Good question because actually the technology and data-mining is sometimes looked at as one little piece of building a predictive model, but SAS has an enterprise intelligence platform that actually spans from the beginning where you collect the data and where you present the information on the webpage, or Web analytics, and where you make the models and actually where you make the decisions. SAS is talking about a solution which truly does entail consultants and experts, people power, behind the software.

BILL: Excellent. Well said. Thank you so much Mary Grace for your time today and for your terrific explanation of predictive analytics. We appreciate it. Bill Cullifer here with the World Organization of Webmasters (WOW), on the phone with Mary Grace Crissey, Global Marketing Manager for Analytics for SAS. Thanks for your time Mary Grace.

MARY GRACE: Yoursquo;re welcome.</itunes:summary>
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