SOPA RIP

From http://www.whitehouse.gov/blog/2012/01/14/obama-administration-responds-we-people-petitions-sopa-and-online-piracy

  1.  Any effort to combat online piracy must guard against the risk of online censorship of lawful activity and must not inhibit innovation by our dynamic businesses large and small (AJ-yup)
  2. We must avoid creating new cybersecurity risks or disrupting the underlying architecture of the Internet.  (AJ-note this may include peer-to-peer browsers, browser extensions for re-routing and newer forms of encryption, or even relocation of internet routers in newer geographies )

We must avoid legislation that drives users to dangerous, unreliable DNS servers and puts next-generation security policies, such as the deployment of DNSSEC, at risk.

While we are strongly committed to the vigorous enforcement of intellectual property rights, existing tools are not strong enough to root out the worst online pirates beyond our borders.

We should never let criminals hide behind a hollow embrace of legitimate American values

and

We should all be committed to working with all interested constituencies to develop new legal tools to protect global intellectual property rights without jeopardizing the openness of the Internet. Our hope is that you will bring enthusiasm and know-how to this important challenge

Authored by

Victoria Espinel is Intellectual Property Enforcement Coordinator at Office of Management and Budget

Aneesh Chopra is the U.S. Chief Technology Officer and Assistant to the President and Associate Director for Technology at the Office of Science and Technology Policy
Howard Schmidt is Special Assistant to the President and Cybersecurity Coordinator for National Security Staff

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AJ-Why not sponser a hackathon, White House and create a monetary incentive for hackers to suggest secure ways? Atleast a secure dialogue between policy makers and policy  breakers could be a way forward. 

SOPA in its current form is dead. We live to fight another day.

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Quote-

Let us never negotiate out of fear. But let us never fear to negotiate. John F K

Interview Dan Steinberg Founder Salford Systems

Here is an interview with Dan Steinberg, Founder and President of Salford Systems (http://www.salford-systems.com/ )

Ajay- Describe your journey from academia to technology entrepreneurship. What are the key milestones or turning points that you remember.

 Dan- When I was in graduate school studying econometrics at Harvard,  a number of distinguished professors at Harvard (and MIT) were actively involved in substantial real world activities.  Professors that I interacted with, or studied with, or whose software I used became involved in the creation of such companies as Sun Microsystems, Data Resources, Inc. or were heavily involved in business consulting through their own companies or other influential consultants.  Some not involved in private sector consulting took on substantial roles in government such as membership on the President’s Council of Economic Advisors. The atmosphere was one that encouraged free movement between academia and the private sector so the idea of forming a consulting and software company was quite natural and did not seem in any way inconsistent with being devoted to the advancement of science.

 Ajay- What are the latest products by Salford Systems? Any future product plans or modification to work on Big Data analytics, mobile computing and cloud computing.

 Dan- Our central set of data mining technologies are CART, MARS, TreeNet, RandomForests, and PRIM, and we have always maintained feature rich logistic regression and linear regression modules. In our latest release scheduled for January 2012 we will be including a new data mining approach to linear and logistic regression allowing for the rapid processing of massive numbers of predictors (e.g., one million columns), with powerful predictor selection and coefficient shrinkage. The new methods allow not only classic techniques such as ridge and lasso regression, but also sub-lasso model sizes. Clear tradeoff diagrams between model complexity (number of predictors) and predictive accuracy allow the modeler to select an ideal balance suitable for their requirements.

The new version of our data mining suite, Salford Predictive Modeler (SPM), also includes two important extensions to the boosted tree technology at the heart of TreeNet.  The first, Importance Sampled learning Ensembles (ISLE), is used for the compression of TreeNet tree ensembles. Starting with, say, a 1,000 tree ensemble, the ISLE compression might well reduce this down to 200 reweighted trees. Such compression will be valuable when models need to be executed in real time. The compression rate is always under the modeler’s control, meaning that if a deployed model may only contain, say, 30 trees, then the compression will deliver an optimal 30-tree weighted ensemble. Needless to say, compression of tree ensembles should be expected to be lossy and how much accuracy is lost when extreme compression is desired will vary from case to case. Prior to ISLE, practitioners have simply truncated the ensemble to the maximum allowable size.  The new methodology will substantially outperform truncation.

The second major advance is RULEFIT, a rule extraction engine that starts with a TreeNet model and decomposes it into the most interesting and predictive rules. RULEFIT is also a tree ensemble post-processor and offers the possibility of improving on the original TreeNet predictive performance. One can think of the rule extraction as an alternative way to explain and interpret an otherwise complex multi-tree model. The rules extracted are similar conceptually to the terminal nodes of a CART tree but the various rules will not refer to mutually exclusive regions of the data.

 Ajay- You have led teams that have won multiple data mining competitions. What are some of your favorite techniques or approaches to a data mining problem.

 Dan- We only enter competitions involving problems for which our technology is suitable, generally, classification and regression. In these areas, we are  partial to TreeNet because it is such a capable and robust learning machine. However, we always find great value in analyzing many aspects of a data set with CART, especially when we require a compact and easy to understand story about the data. CART is exceptionally well suited to the discovery of errors in data, often revealing errors created by the competition organizers themselves. More than once, our reports of data problems have been responsible for the competition organizer’s decision to issue a corrected version of the data and we have been the only group to discover the problem.

In general, tackling a data mining competition is no different than tackling any analytical challenge. You must start with a solid conceptual grasp of the problem and the actual objectives, and the nature and limitations of the data. Following that comes feature extraction, the selection of a modeling strategy (or strategies), and then extensive experimentation to learn what works best.

 Ajay- I know you have created your own software. But are there other software that you use or liked to use?

 Dan- For analytics we frequently test open source software to make sure that our tools will in fact deliver the superior performance we advertise. In general, if a problem clearly requires technology other than that offered by Salford, we advise clients to seek other consultants expert in that other technology.

 Ajay- Your software is installed at 3500 sites including 400 universities as per http://www.salford-systems.com/company/aboutus/index.html What is the key to managing and keeping so many customers happy?

 Dan- First, we have taken great pains to make our software reliable and we make every effort  to avoid problems related to bugs.  Our testing procedures are extensive and we have experts dedicated to stress-testing software . Second, our interface is designed to be natural, intuitive, and easy to use, so the challenges to the new user are minimized. Also, clear documentation, help files, and training videos round out how we allow the user to look after themselves. Should a client need to contact us we try to achieve 24-hour turn around on tech support issues and monitor all tech support activity to ensure timeliness, accuracy, and helpfulness of our responses. WebEx/GotoMeeting and other internet based contact permit real time interaction.

 Ajay- What do you do to relax and unwind?

 Dan- I am in the gym almost every day combining weight and cardio training. No matter how tired I am before the workout I always come out energized so locating a good gym during my extensive travels is a must. I am also actively learning Portuguese so I look to watch a Brazilian TV show or Portuguese dubbed movie when I have time; I almost never watch any form of video unless it is available in Portuguese.

 Biography-

http://www.salford-systems.com/blog/dan-steinberg.html

Dan Steinberg, President and Founder of Salford Systems, is a well-respected member of the statistics and econometrics communities. In 1992, he developed the first PC-based implementation of the original CART procedure, working in concert with Leo Breiman, Richard Olshen, Charles Stone and Jerome Friedman. In addition, he has provided consulting services on a number of biomedical and market research projects, which have sparked further innovations in the CART program and methodology.

Dr. Steinberg received his Ph.D. in Economics from Harvard University, and has given full day presentations on data mining for the American Marketing Association, the Direct Marketing Association and the American Statistical Association. After earning a PhD in Econometrics at Harvard Steinberg began his professional career as a Member of the Technical Staff at Bell Labs, Murray Hill, and then as Assistant Professor of Economics at the University of California, San Diego. A book he co-authored on Classification and Regression Trees was awarded the 1999 Nikkei Quality Control Literature Prize in Japan for excellence in statistical literature promoting the improvement of industrial quality control and management.

His consulting experience at Salford Systems has included complex modeling projects for major banks worldwide, including Citibank, Chase, American Express, Credit Suisse, and has included projects in Europe, Australia, New Zealand, Malaysia, Korea, Japan and Brazil. Steinberg led the teams that won first place awards in the KDDCup 2000, and the 2002 Duke/TeraData Churn modeling competition, and the teams that won awards in the PAKDD competitions of 2006 and 2007. He has published papers in economics, econometrics, computer science journals, and contributes actively to the ongoing research and development at Salford.

Interview Jaime Fitzgerald President Fitzgerald Analytics

Here is an interview with noted analytics expert Jaime Fitzgerald, of Fitzgerald Analytics.

Ajay-Describe your career journey from being a Harvard economist to being a text analytics thought leader.

 Jaime- I was attracted to economics because of the logic, the structured and systematic approach to understanding the world and to solving problems. In retrospect, this is the same passion for logic in problem solving that drives my business today.

About 15 years ago, I began working in consulting and initially took a traditional career path. I worked for well-known strategy consulting firms including First Manhattan Consulting Group, Novantas LLC, Braun Consulting, and for the former Japan-focused division of Deloitte Consulting, which had spun off as an independent entity. I was the only person in their New York City office for whom Japanese was not the first language.

While I enjoyed traditional consulting, I was especially passionate about the role of data, analytics, and process improvement. In traditional strategy consulting, these are important factors, but I had a vision for a “next generation” approach to strategy consulting that would be more transparent, more robust, and more focused on the role that information, analysis, and process plays in improving business results. I often explain that while my firm is “not your father’s consulting model,” we have incorporated key best practices from traditional consulting, and combined them with an approach that is more data-centric, technology-centric, and process-centric.

At the most fundamental level, I was compelled to found Fitzgerald Analytics more than six years ago by my passion for the role information plays in improving results, and ultimately improving lives. In my vision, data is an asset waiting to be transformed into results, including profit as well as other results that matter deeply to people. For example,one of the most fulfilling aspects of our work at Fitzgerald Analytics is our support of non-profits and social entrepreneurs, who we help increase their scale and their success in achieving their goals.

Ajay- How would you describe analytics as a career option to future students. What do you think are the most essential qualities an analytics career requires.

Jaime- My belief is that analytics will be a major driver of job-growth and career growth for decades. We are just beginning to unlock the full potential of analytics, and already the demand for analytic talent far exceeds the supply.

To succeed in analytics, the most important quality is logic. Many people believe that math or statistical skills are the most important quality, but in my experience, the most essential trait is what I call “ThoughtStyle” — critical thinking, logic, an ability to break down a problem into components, into sub-parts.

Ajay -What are your favorite techniques and methodologies in text analytics. How do you see social media and Big Data analytics as components of text analytics

 Jaime-We do a lot of work for our clients measuring Customer Experience, by which I mean the experience customers have when interacting with our clients. For example, we helped a major brokerage firm to measure 12 key “Moments that Matter,” including the operational aspects of customer service, customer satisfaction and sentiment, and ultimately customer behavior. Clients care about this a lot, because customer experience drives customer loyalty, which in turn drives customer behavior, customer loyalty, and customer profitability.

Text analytics plays a key role in these projects because much of our data on customer sentiment comes via unstructured text data. For example, we have access to call center transcripts and notes, to survey responses, and to social media comments.

We use a variety of methods, some of which I’m not in a position to describe in great detail. But at a high level, I would say that our favorite text analytics methodologies are “hybrid solutions” which use a two-step process to answer key questions for clients:

Step 1: convert unstructured data into key categorical variables (for example, using contextual analysis to flag users who are critical vs. neutral vs. advocates)

Step 2: linking sentiment categories to customer behavior and profitability (for example, linking customer advocacy and loyalty with customer profits as well as referral volume, to define the ROI that clients accrue for customer satisfaction improvements)

Ajay- Describe your consulting company- Fitzgerald Analytics and some of the work that you have been engaged in.

 Jaime- Our mission is to “illuminate reality” using data and to convert Data to Dollars for our clients. We have a track record of doing this well, with concrete and measurable results in the millions of dollars. As a result, 100% of our clients have engaged us for more than one project: a 100% client loyalty rate.

Our specialties–and most frequent projects–include customer profitability management projects, customer segmentation, customer experience management, balanced scorecards, and predictive analytics. We are often engaged to address high-stakes analytic questions, including issues that help to set long-term strategy. In other cases, clients hire us to help them build their internal capabilities. We have helped build several brand new analytic teams for clients, which continue to generate millions of dollars of profits with their fact-based recommendations.

Our methodology is based on Steven Covey’s principle: “begin with the end in mind,” the concept of starting with the client’s goal and working backwards from there. I often explain that our methods are what you would have gotten if Steven Covey had been a data analyst…we are applying his principles to the world of data analytics.

Ajay- Analytics requires more and more data while privacy requires the least possible data. What do you think are the guidelines that need to be built in sharing internet browsing and user activity data and do we need regulations just like we do for sharing financial data.

 Jaime- Great question. This is an essential challenge of the big data era. My perspective is that firms who depend on user data for their analysis need to take responsibility for protecting privacy by using data management best practices. Best practices to adequately “mask” or remove private data exist…the problem is that these best practices are often not applied. For example, Facebook’s practice of sharing unique user IDs with third-party application companies has generated a lot of criticism, and could have been avoided by applying data management best practices which are well known among the data management community.

If I were able to influence public policy, my recommendation would be to adopt a core set of simple but powerful data management standards that would protect consumers from perhaps 95% of the privacy risks they face today. The number one standard would be to prohibit sharing of static, personally identifiable user IDs between companies in a manner that creates “privacy risk.” Companies can track unique customers without using a static ID…they need to step up and do that.

Ajay- What are your favorite text analytics software that you like to work with.

 Jaime- Because much of our work in deeply embedded into client operations and systems, we often use the software our clients already prefer. We avoid recommending specific vendors unless our client requests it. In tandem with our clients and alliance partners, we have particular respect for Autonomy, Open Text, Clarabridge, and Attensity.

Biography-

http://www.fitzgerald-analytics.com/jaime_fitzgerald.html

The Founder and President of Fitzgerald Analytics, Jaime has developed a distinctively quantitative, fact-based, and transparent approach to solving high stakes problems and improving results.  His approach enables translation of Data to Dollars™ using methodologies clients can repeat again and again.  He is equally passionate about the “human side of the equation,” and is known for his ability to link the human and the quantitative, both of which are needed to achieve optimal results.

Experience: During more than 15 years serving clients as a management strategy consultant, Jaime has focused on customer experience and loyalty, customer profitability, technology strategy, information management, and business process improvement.  Jaime has advised market-leading banks, retailers, manufacturers, media companies, and non-profit organizations in the United States, Canada, and Singapore, combining strategic analysis with hands-on implementation of technology and operations enhancements.

Career History: Jaime began his career at First Manhattan Consulting Group, specialists in financial services, and was later a Co-Founder at Novantas, the strategy consultancy based in New York City.  Jaime was also a Manager for Braun Consulting, now part of Fair Isaac Corporation, and for Japan-based Abeam Consulting, now part of NEC.

Background: Jaime is a graduate of Harvard University with a B.A. in Economics.  He is passionate and supportive of innovative non-profit organizations, their effectiveness, and the benefits they bring to our society.

Upcoming Speaking Engagements:   Jaime is a frequent speaker on analytics, information management strategy, and data-driven profit improvement.  He recently gave keynote presentations on Analytics in Financial Services for The Data Warehousing Institute, the New York Technology Council, and the Oracle Financial Services Industry User Group. A list of Jaime’s most interesting presentations on analyticscan be found here.

He will be presenting a client case study this fall at Text Analytics World re:   “New Insights from ‘Big Legacy Data’: The Role of Text Analytics” 

Connecting with Jaime:  Jaime can be found at Linkedin,  and Twitter.  He edits the Fitzgerald Analytics Blog.

Updated Interview Elissa Fink -VP Tableau Software

Here is an interview with Elissa Fink, VP Marketing of that new wonderful software called Tableau that makes data visualization so nice and easy to learn and work with.

Elissa Fink, VP, Marketing

Ajay-  Describe your career journey from high school to over 20 plus years in marketing. What are the various trends that you have seen come and go in marketing.

Elissa- I studied literature and linguistics in college and didn’t discover analytics until my first job selling advertising for the Wall Street Journal. Oddly enough, the study of linguistics is not that far from decision analytics: they both are about taking a structured view of information and trying to see and understand common patterns. At the Journal, I was completely captivated analyzing and comparing readership data. At the same time, the idea of using computers in marketing was becoming more common. I knew that the intersection of technology and marketing was going to radically change things – how we understand consumers, how we market and sell products, and how we engage with customers. So from that point on, I’ve always been focused on technology and marketing, whether it’s working as a marketer at technology companies or applying technology to marketing problems for other types of companies.  There have been so many interesting trends. Taking a long view, a key trend I’ve noticed is how marketers work to understand, influence and motivate consumer behavior. We’ve moved marketing from where it was primarily unpredictable, qualitative and aimed at talking to mass audiences, where the advertising agency was king. Now it’s a discipline that is more data-driven, quantitative and aimed at conversations with individuals, where the best analytics wins. As with any trend, the pendulum swings far too much to either side causing backlashes but overall, I think we are in a great place now. We are using data-driven analytics to understand consumer behavior. But pure analytics is not the be-all, end-all; good marketing has to rely on understanding human emotions, intuition and gut feel – consumers are far from rational so taking only a rational or analytical view of them will never explain everything we need to know.

Ajay- Do you think technology companies are still predominantly dominated by men . How have you seen diversity evolve over the years. What initiatives has Tableau taken for both hiring and retaining great talent.

Elissa- The thing I love about the technology industry is that its key success metrics – inventing new products that rapidly gain mass adoption in pursuit of making profit – are fairly objective. There’s little subjective nature to the counting of dollars collected selling a product and dollars spent building a product. So if a female can deliver a better product and bigger profits faster and better, then that female is going to get the resources, jobs, power and authority to do exactly that. That’s not to say that the technology industry is gender-blind, race-blind, etc. It isn’t – technology is far from perfect. For example, the industry doesn’t have enough diversity in positions of power. But I think overall, in comparison to a lot of other industries, it’s pretty darn good at giving people with great ideas the opportunities to realize their visions regardless of their backgrounds or characteristics.

At Tableau, we are very serious about bringing in and developing talented people – they are the key to our growth and success. Hiring is our #1 initiative so we’ve spent a lot of time and energy both on finding great candidates and on making Tableau a place that they want to work. This includes things like special recruiting events, employee referral programs, a flexible work environment, fun social events, and the rewards of working for a start-up. Probably our biggest advantage is the company itself – working with people you respect on amazing, cutting-edge products that delight customers and are changing the world is all too rare in the industry but a reality at Tableau. One of our senior software developers put it best when he wrote “The emphasis is on working smarter rather than longer: family and friends are why we work, not the other way around. Tableau is all about happy, energized employees executing at the highest level and delivering a highly usable, high quality, useful product to our customers.” People who want to be at a place like that should check out our openings at http://www.tableausoftware.com/jobs.

Ajay- What are most notable features in tableau’s latest edition. What are the principal software that competes with Tableau Software products and how would you say Tableau compares with them.

Elissa- Tableau 6.1 will be out in July and we are really excited about it for 3 reasons.

First, we’re introducing our mobile business intelligence capabilities. Our customers can have Tableau anywhere they need it. When someone creates an interactive dashboard or analytical application with Tableau and it’s viewed on a mobile device, an iPad in particular, the viewer will have a native, touch-optimized experience. No trying to get your fingertips to act like a mouse. And the author didn’t have to create anything special for the iPad; she just creates her analytics the usual way in Tableau. Tableau knows the dashboard is being viewed on an iPad and presents an optimized experience.

Second, we’ve take our in-memory analytics engine up yet another level. Speed and performance are faster and now people can update data incrementally rapidly. Introduced in 6.0, our data engine makes any data fast in just a few clicks. We don’t run out of memory like other applications. So if I build an incredible dashboard on my 8-gig RAM PC and you try to use it on your 2-gig RAM laptop, no problem.

And, third, we’re introducing more features for the international markets – including French and German versions of Tableau Desktop along with more international mapping options.  It’s because we are constantly innovating particularly around user experience that we can compete so well in the market despite our relatively small size. Gartner’s seminal research study about the Business Intelligence market reported a massive market shift earlier this year: for the first time, the ease-of-use of a business intelligence platform was more important than depth of functionality. In other words, functionality that lots of people can actually use is more important than having sophisticated functionality that only specialists can use. Since we focus so heavily on making easy-to-use products that help people rapidly see and understand their data, this is good news for our customers and for us.

Ajay-  Cloud computing is the next big thing with everyone having a cloud version of their software. So how would you run Cloud versions of Tableau Server (say deploying it on an Amazon Ec2  or a private cloud)

Elissa- In addition to the usual benefits espoused about Cloud computing, the thing I love best is that it makes data and information more easily accessible to more people. Easy accessibility and scalability are completely aligned with Tableau’s mission. Our free product Tableau Public and our product for commercial websites Tableau Digital are two Cloud-based products that deliver data and interactive analytics anywhere. People often talk about large business intelligence deployments as having thousands of users. With Tableau Public and Tableau Digital, we literally have millions of users. We’re serving up tens of thousands of visualizations simultaneously – talk about accessibility and scalability!  We have lots of customers connecting to databases in the Cloud and running Tableau Server in the Cloud. It’s actually not complex to set up. In fact, we focus a lot of resources on making installation and deployment easy and fast, whether it’s in the cloud, on premise or what have you. We don’t want people to have spend weeks or months on massive roll-out projects. We want it to be minutes, hours, maybe a day or 2. With the Cloud, we see that people can get started and get results faster and easier than ever before. And that’s what we’re about.

Ajay- Describe some of the latest awards that Tableau has been wining. Also how is Tableau helping universities help address the shortage of Business Intelligence and Big Data professionals.

Elissa-Tableau has been very fortunate. Lately, we’ve been acknowledged by both Gartner and IDC as the fastest growing business intelligence software vendor in the world. In addition, our customers and Tableau have won multiple distinctions including InfoWorld Technology Leadership awards, Inc 500, Deloitte Fast 500, SQL Server Magazine Editors’ Choice and Community Choice awards, Data Hero awards, CODiEs, American Business Awards among others. One area we’re very passionate about is academia, participating with professors, students and universities to help build a new generation of professionals who understand how to use data. Data analysis should not be exclusively for specialists. Everyone should be able to see and understand data, whatever their background. We come from academic roots, having been spun out of a Stanford research project. Consequently, we strongly believe in supporting universities worldwide and offer 2 academic programs. The first is Tableau For Teaching, where any professor can request free term-length licenses of Tableau for academic instruction during his or her courses. And, we offer a low-cost Student Edition of Tableau so that students can choose to use Tableau in any of their courses at any time.

Elissa Fink, VP Marketing,Tableau Software

 

Elissa Fink is Tableau Software’s Vice President of Marketing. With 20+ years helping companies improve their marketing operations through applied data analysis, Elissa has held executive positions in marketing, business strategy, product management, and product development. Prior to Tableau, Elissa was EVP Marketing at IXI Corporation, now owned by Equifax. She has also served in executive positions at Tele Atlas (acquired by TomTom), TopTier Software (acquired by SAP), and Nielsen/Claritas. Elissa also sold national advertising for the Wall Street Journal. She’s a frequent speaker and has spoken at conferences including the DMA, the NCDM, Location Intelligence, the AIR National Forum and others. Elissa is a graduate of Santa Clara University and holds an MBA in Marketing and Decision Systems from the University of Southern California.

Elissa first discovered Tableau late one afternoon at her previous company. Three hours later, she was still “at play” with her data. “After just a few minutes using the product, I was getting answers to questions that were taking my company’s programmers weeks to create. It was instantly obvious that Tableau was on a special mission with something unique to offer the world. I just had to be a part of it.”

To know more – read at http://www.tableausoftware.com/

and existing data viz at http://www.tableausoftware.com/learn/gallery

Storm seasons: measuring and tracking key indicators
What’s happening with local real estate prices?
How are sales opportunities shaping up?
Identify your best performing products
Applying user-defined parameters to provide context
Not all tech companies are rocket ships
What’s really driving the economy?
Considering factors and industry influencers
The complete orbit along the inside, or around a fixed circle
How early do you have to be at the airport?
What happens if sales grow but so does customer churn?
What are the trends for new retail locations?
How have student choices changed?
Do patients who disclose their HIV status recover better?
Closer look at where gas prices swing in areas of the U.S.
U.S. Census data shows more women of greater age
Where do students come from and how does it affect their grades?
Tracking customer service effectiveness
Comparing national and local test scores
What factors correlate with high overall satisfaction ratings?
Fund inflows largely outweighed outflows well after the bubble
Which programs are competing for federal stimulus dollars?
Oil prices and volatility
A classic candlestick chart
How do oil, gold and CPI relate to the GDP growth rate?

 

Kill Barack Obama

Then President of the United States of America...
Image via Wikipedia

From

http://www.law.cornell.edu/uscode/718/usc_sec_18_00000871—-000-.html

§ 871. Threats against President and successors to the Presidency

(a) Whoever knowingly and willfully deposits for conveyance in the mail or for a delivery from any post office or by any letter carrier any letter, paper, writing, print, missive, or document containing any threat to take the life of, to kidnap, or to inflict bodily harm upon the President of the United States, the President-elect, the Vice President or other officer next in the order of succession to the office of President of the United States, or the Vice President-elect, or knowingly and willfully otherwise makes any such threat against the President, President-elect, Vice President or other officer next in the order of succession to the office of President, or Vice President-elect, shall be fined under this title or imprisoned not more than five years, or both.
(b) The terms “President-elect” and “Vice President-elect” as used in this section shall mean such persons as are the apparent successful candidates for the offices of President and Vice President, respectively, as ascertained from the results of the general elections held to determine the electors of President and Vice President in accordance with title 3, United States Code, sections 1 and 2. The phrase “other officer next in the order of succession to the office of President” as used in this section shall mean the person next in the order of succession to act as President in accordance with title 3, United States Code, sections 19 and 20.
From the new experiment at Google Co Relate (assumptions it will take a long time to actually create a plot or conspiracy to kill the President because of his security cover) this uses the internet to actually find people who are searching for ways to kill the beloved leader of the free world. Includes state by state intensity- and expect these people to be the first to ask for ….MORE privacy (my ass)

 

 

AsterData still alive;/launches SQL-MapReduce Developer Portal

so apparantly ole client AsterData continues to thrive under gentle touch of Terrific Data

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Aster Data today launched the SQL-MapReduce Developer Portal, a new online community for data scientists and analytic developers. For your convenience, I copied the release below and it can also be found here. Please let me know if you have any questions or if there is anything else I can help you with.

Sara Korolevich

Point Communications Group for Aster Data

sarak@pointcgroup.com

Office: 602.279.1137

Mobile: 623.326.0881

Teradata Accelerates Big Data Analytics with First Collaborative Community for SQL-MapReduce®

New online community for data scientists and analytic developers enables development and sharing of powerful MapReduce analytics


San Carlos, California – Teradata Corporation (NYSE:TDC) today announced the launch of the Aster Data SQL-MapReduce® Developer Portal. This portal is the first collaborative online developer community for SQL-MapReduce analytics, an emerging framework for processing non-relational data and ultra-fast analytics.

“Aster Data continues to deliver on its unique vision for powerful analytics with a rich set of tools to make development of those analytics quick and easy,” said Tasso Argyros, vice president of Aster Data Marketing and Product Management, Teradata Corporation. “This new developer portal builds on Aster Data’s continuing SQL-MapReduce innovation, leveraging the flexibility and power of SQL-MapReduce for analytics that were previously impossible or impractical.”

The developer portal showcases the power and flexibility of Aster Data’s SQL-MapReduce – which uniquely combines standard SQL with the popular MapReduce distributed computing technology for processing big data – by providing a collaborative community for sharing SQL-MapReduce expert insights in addition to sharing SQL-MapReduce analytic functions and sample code. Data scientists, quantitative analysts, and developers can now leverage the experience, knowledge, and best practices of a community of experts to easily harness the power of SQL-MapReduce for big data analytics.

A recent report from IDC Research, “Taking Care of Your Quants: Focusing Data Warehousing Resources on Quantitative Analysts Matters,” has shown that by enabling data scientists with the tools to harness emerging types and sources of data, companies create significant competitive advantage and become leaders in their respective industry.

“The biggest positive differences among leaders and the rest come from the introduction of new types of data,” says Dan Vesset, program vice president, Business Analytics Solutions, IDC Research. “This may include either new transactional data sources or new external data feeds of transactional or multi-structured interactional data — the latter may include click stream or other data that is a by-product of social networking.”

Vesset goes on to say, “Aster Data provides a comprehensive platform for analytics and their SQL-MapReduce Developer Portal provides a community for sharing best practices and functions which can have an even greater impact to an organization’s business.”

With this announcement Aster Data extends its industry leadership in delivering the most comprehensive analytic platform for big data analytics — not only capable of processing massive volumes of multi-structured data, but also providing an extensive set of tools and capabilities that make it simple to leverage the power of MapReduce analytics. The Aster Data

SQL-MapReduce Developer Portal brings the power of SQL-MapReduce accessible to data scientists, quantitative analysis, and analytic developers by making it easy to share and collaborate with experts in developing SQL-MapReduce analytics. This portal builds on Aster Data’s history of SQL-MapReduce innovations, including:

  • The first deep integration of SQL with MapReduce
  • The first MapReduce support for .NET
  • The first integrated development environment, Aster Data
    Developer Express
  • A comprehensive suite of analytic functions, Aster Data
    Analytic Foundation

Aster Data’s patent-pending SQL-MapReduce enables analytic applications and functions that can deliver faster, deeper insights on terabytes to petabytes of data. These applications are implemented using MapReduce but delivered through standard SQL and business intelligence (BI) tools.

SQL-MapReduce makes it possible for data scientists and developers to empower business analysts with the ability to make informed decisions, incorporating vast amounts of data, regardless of query complexity or data type. Aster Data customers are using SQL-MapReduce for rich analytics including analytic applications for social network analysis, digital marketing optimization, and on-the-fly fraud detection and prevention.

“Collaboration is at the core of our success as one of the leading providers, and pioneers of social software,” said Navdeep Alam, director of Data Architecture at Mzinga. “We are pleased to be one of the early members of The Aster Data SQL-MapReduce Developer Portal, which will allow us the ability to share and leverage insights with others in using big data analytics to attain a deeper understanding of customers’ behavior and create competitive advantage for our business.”

SQL-MapReduce is one of the core capabilities within Aster Data’s flagship product. Aster DatanCluster™ 4.6, the industry’s first massively parallel processing (MPP) analytic platform has an integrated analytics engine that stores and processes both relational and non-relational data at scale. With Aster Data’s unique analytics framework that supports both SQL and
SQL-MapReduce™, customers benefit from rich, new analytics on large data volumes with complex data types. Aster Data analytic functions are embedded within the analytic platform and processed locally with data, which allows for faster data exploration. The SQL-MapReduce framework provides scalable fault-tolerance for new analytics, providing users with superior reliability, regardless of number of users, query size, or data types.


About Aster Data
Aster Data is a market leader in big data analytics, enabling the powerful combination of cost-effective storage and ultra-fast analysis of new sources and types of data. The Aster Data nCluster analytic platform is a massively parallel software solution that embeds MapReduce analytic processing with data stores for deeper insights on new data sources and types to deliver new analytic capabilities with breakthrough performance and scalability. Aster Data’s solution utilizes Aster Data’s patent-pending SQL-MapReduce to parallelize processing of data and applications and deliver rich analytic insights at scale. Companies including Barnes & Noble, Intuit, LinkedIn, Akamai, and MySpace use Aster Data to deliver applications such as digital marketing optimization, social network and relationship analysis, and fraud detection and prevention.


About Teradata
Teradata is the world’s leader in data warehousing and integrated marketing management through itsdatabase softwaredata warehouse appliances, and enterprise analytics. For more information, visitteradata.com.

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Teradata is a trademark or registered trademark of Teradata Corporation in the United States and other countries.

How to Measure and Optimize Your Marketing:Tableau

Tired of everyone calling everyone else a social media expert. What seperates the social media men from the fakes.

the grain from the chaff.

Data.

Heres a webcast you may want to think of social media tickles your curiosity on how  to leverage these strange new marketing tools.

https://cc.readytalk.com/cc/schedule/display.do?udc=xu40u1ex8tj8

Notice the form and fields below the screenshot-

is every field required – is each one required to measure

Have they optimized web registration forms yet.

Continue reading “How to Measure and Optimize Your Marketing:Tableau”