The Youtube Promoted Videos (basically a video form of Adsense) can really help companies like Oracle, SAP, IBM, Netezza, SAS Insititute, AsterData, Rapid Miner, Pentaho, JasperSoft, Teradata, Revolution who create
either corporate videos/training videos or upload their seminar, webinar,conference videos to Youtube.
Making a video is hard work in itself- doing an A/ B test with Youtube Promoted videos might just get a better ROI for your video marketing budget and IMHO embeddable videos from Youtube are much better and easier to share than Videos that can be seen only after registration on a company web site. You want to get the word out for your software, or you want to get website views?
Here is a brief one question interview with James Kobielus, Senior Analyst, Forrester.
Ajay-Describe the five most important events in Predictive Analytics you saw in 2010 and the top three trends in 2011 as per you.
Jim-
Five most important developments in 2010:
Continued emergence of enterprise-grade Hadoop solutions as the core of the future cloud-based platforms for advanced analytics
Development of the market for analytic solution appliances that incorporate several key features for advanced analytics: massively parallel EDW appliance, in-database analytics and data management function processing, embedded statistical libraries, prebuilt logical domain models, and integrated modeling and mining tools
Integration of advanced analytics into core BI platforms with user-friendly, visual, wizard-driven, tools for quick, exploratory predictive modeling, forecasting, and what-if analysis by nontechnical business users
Convergence of predictive analytics, data mining, content analytics, and CEP in integrated tools geared to real-time social media analytics
Emergence of CRM and other line-of-business applications that support continuously optimized “next-best action” business processes through embedding of predictive models, orchestration engines, business rules engines, and CEP agility
Three top trends I see in the coming year, above and beyond deepening and adoption of the above-bulleted developments:
All-in-memory, massively parallel analytic architectures will begin to gain a foothold in complex EDW environments in support of real-time elastic analytics
Further crystallization of a market for general-purpose “recommendation engines” that, operating inline to EDWs, CEP environments, and BPM platforms, enable “next-best action” approaches to emerge from today’s application siloes
Incorporation of social network analysis functionality into a wider range of front-office business processes to enable fine-tuned behavioral-based customer segmentation to drive CRM optimization
James serves Business Process & Applications professionals. He is a leading expert on data warehousing, predictive analytics, data mining, and complex event processing. In addition to his core coverage areas, James contributes to Forrester’s research in business intelligence, data integration, data quality, and master data management.
PREVIOUS WORK EXPERIENCE
James has a long history in IT research and consulting and has worked for both vendors and research firms. Most recently, he was at Current Analysis, an IT research firm, where he was a principal analyst covering topics ranging from data warehousing to data integration and the Semantic Web. Prior to that position, James was a senior technical systems analyst at Exostar (a hosted supply chain management and eBusiness hub for the aerospace and defense industry). In this capacity, James was responsible for identifying and specifying product/service requirements for federated identity, PKI, and other products. He also worked as an analyst for the Burton Group and was previously employed by LCC International, DynCorp, ADEENA, International Center for Information Technologies, and the North American Telecommunications Association. He is both well versed and experienced in product and market assessments. James is a widely published business/technology author and has spoken at many industry events
Occam’s razor (or Ockham’s razor[1]) is often expressed in Latin as the lex parsimoniae(translating to the law of parsimony, law of economy or law of succinctness). The principle is popularly summarized as “the simplest explanation is more likely the correct one.
Using a simple screenshot- you can see Facebook Analytics for a Facebook page is simpler at explaining who is coming to visit rather than Google Analytics Dashboard (which has not seen the attention of a Visual UI or Graphic Redesign)
And if Facebook is going to take over the internet, well it is definitely giving better analytics in the process. What do you think?
Which Interface is simpler- and gives you better targeting. Ignore the numbers and just see the metrics measured and the way they are presented. Coincidently R is used at Facebook a lot (which has given the jjplot package)- and Google has NOT INVESTED MAJOR MONEY in creating Premium R Packages or Big Data Packages. I am talking investment at the scale Google is known for- not measly meetups.
(the summer of code dont count- it is for students mostly)
(but thanks for the Pizza G Men- and maybe revise that GA interface by putting a razor to some metrics)
Using WP- Stats I set about answering this question-
What search keywords lead here-
Clearly Michael Jackson is down this year
And R GUI, Data Mining is up.
How does that affect my writing- given I get almost 250 visitors by search engines alone daily- assume I write nothing on this blog from now on.
It doesnt- I still write what ever code or poem that comes to my mind. So it is hurtful people misunderstimate the effort in writing and jump to conclusions (esp if I write about a company- I am not on payroll of that company- just like if I write about a poem- I am not a full time poet)
Over to xkcd
All Time (for Decisionstats.Wordpress.com)
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240
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180
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PAW’s San Francisco 2011 program is the richest and most diverse yet, including over 30 sessions across two tracks – an “All Audiences” and an “Expert/Practitioner” track — so you can witness how predictive analytics is applied at Bank of America, Bank of the West, Best Buy, CA State Automobile Association, Cerebellum Capital, Chessmetrics, Fidelity, Gaia Interactive, GE Capital, Google, HealthMedia, Hewlett Packard, ICICI Bank (India), MetLife, Monster.com, Orbitz, PayPal/eBay, Richmond, VA Police Dept, U. of Melbourne, Yahoo!, YMCA, and a major N. American telecom, plus insights from projects for Anheiser-Busch, the SSA, and Netflix.
PAW’s agenda covers hot topics and advanced methods such as uplift modeling (net lift), ensemble models, social data (6 sessions on this), search marketing, crowdsourcing, blackbox trading, fraud detection, risk management, survey analysis, and other innovative applications that benefit organizations in new and creative ways.
Predictive Analytics World is the only conference of its kind, delivering vendor-neutral sessions across verticals such as banking, financial services, e-commerce, education, government, healthcare, high technology, insurance, non-profits, publishing, social gaming, retail and telecommunications
And PAW covers the gamut of commercial applications of predictive analytics, including response modeling, customer retention with churn modeling, product recommendations, fraud detection, online marketing optimization, human resource decision-making, law enforcement, sales forecasting, and credit scoring.
WORKSHOPS. PAW also features pre- and post-conference workshops that complement the core conference program. Workshop agendas include advanced predictive modeling methods, hands-on training and enterprise decision management.
Now Jim Davis is a big guy, and he is rushing from the launch of SAS Institute’s Social Media Analytics in Japan- to some arguably difficult flying conditions in time to be home in America for Thanksgiving. That and and I have not been much of a good Blog Boy recently, more swayed by love of open source, than love of software per se. I love equally, given I am bad at both equally.
Anyways, Jim’s contention ( http://twitter.com/Davis_Jim ) was customers should go in business analytics only if there is Positive Return on Investment. I am quoting him here-
What is important is that there be a positive ROI on each and every BA project. Otherwise don’t do it.
That’s not the marketing I was taught in my business school- basically it was sell, sell, sell.
However I see most BI sales vendors also go through -let me meet my sales quota for this quarter- and quantifying customer ROI is simple maths than predictive analytics but there seems to be some information assymetry in it.
Here is a paper from North Western University on ROI in IT projects-.
but overall it would be in the interest of customers and Business Analytics Vendors to publish aggregated ROI.
The opponents to this transparency in ROI would be market leaders in market share, who have trapped their customers by high migration costs (due to complexity) or contractually.
A recent study listed Oracle having a large percentage of unhappy customers who would still renew!, SAP had problems when it raised prices for licensing arbitrarily (that CEO is now CEO of HP and dodging legal notices from Oracle).
Indeed Jim Davis’s famous unsettling call for focusing on Business Analytics,as Business Intelligence is dead- that call has been implemented more aggressively by IBM in analytical acquisitions than even SAS itself which has been conservative about inorganic growth. Quantifying ROI, should theoretically aid open source software the most (since they are cheapest in up front licensing) or newer technologies like MapReduce /Hadoop (since they are quite so fast)- but I think that market has a way of factoring in these things- and customers are not as foolish neither as unaware of costs versus benefits of migration.
The contrary to this is Business Analytics and Business Intelligence are imperfect markets with duo-poly or big players thriving in absence of customer regulation.
You get more protection as a customer of $20 bag of potato chips, than as a customer of a $200,000 software. Regulators are wary to step in to ensure ROI fairness (since most bright techies are qither working for private sector, have their own startup or invested in startups)- who in Govt understands Analytics and Intelligence strong enough to ensure vendor lock-ins are not done, and market flexibility is done. It is also a lower choice for embattled regulators to ensure ROI on enterprise software unlike the aggressiveness they have showed in retail or online software.
Who will Analyze the Analysts and who can quantify the value of quants (or penalize them for shoddy quantitative analytics)- is an interesting phenomenon we expect to see more of.
some analytical positions from Analytical Searches.com
Image via Wikipedia
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DECISION STATS 