Timo Elliott on 2012

Continuing the DecisionStats series on  trends for 2012, Timo Elliott , Technology Evangelist  at SAP Business Objects, looks at the predictions he made in the beginning of  2011 and follows up with the things that surprised him in 2011, and what he foresees in 2012.

You can read last year’s predictions by Mr Elliott at http://www.decisionstats.com/brief-interview-timo-elliott/

Timo- Here are my comments on the “top three analytics trends” predictions I made last year:

(1) Analytics, reinvented. New DW techniques make it possible to do sub-second, interactive analytics directly against row-level operational data. Now BI processes and interfaces need to be rethought and redesigned to make best use of this — notably by blurring the distinctions between the “design” and “consumption” phases of BI.

I spent most of 2011 talking about this theme at various conferences: how existing BI technology israpidly becoming obsolete and how the changes are akin to the move from film to digital photography. Technology that has been around for many years (in-memory, column stores, datawarehouse appliances, etc.) came together to create exciting new opportunities and even generally-skeptical industry analysts put out press releases such as “Gartner Says Data Warehousing Reaching Its Most Significant Inflection Point Since Its Inception.” Some of the smaller BI vendors had been pushing in-memory analytics for years, but the general market started paying more attention when megavendors like SAP started painting a long-term vision of in-memory becoming a core platform for applications, not just analytics. Database leader Oracle was forced to upgrade their in-memory messaging from “It’s a complete fantasy” to “we have that too”.

(2) Corporate and personal BI come together. The ability to mix corporate and personal data for quick, pragmatic analysis is a common business need. The typical solution to the problem — extracting and combining the data into a local data store (either Excel or a departmental data mart) — pleases users, but introduces duplication and extra costs and makes a mockery of information governance. 2011 will see the rise of systems that let individuals and departments load their data into personal spaces in the corporate environment, allowing pragmatic analytic flexibility without compromising security and governance.

The number of departmental “data discovery” initiatives continued to rise through 2011, but new tools do make it easier for business people to upload and manipulate their own information while using the corporate standards. 2012 will see more development of “enterprise data discovery” interfaces for casual users.

(3) The next generation of business applications. Where are the business applications designed to support what people really do all day, such as implementing this year’s strategy, launching new products, or acquiring another company? 2011 will see the first prototypes of people-focused, flexible, information-centric, and collaborative applications, bringing together the best of business intelligence, “enterprise 2.0”, and existing operational applications.

2011 saw the rise of sophisticated, user-centric mobile applications that combine data from corporate systems with GPS mapping and the ability to “take action”, such as mobile medical analytics for doctors or mobile beauty advisor applications, and collaborative BI started becoming a standard part of enterprise platforms.

And one that should happen, but probably won’t: (4) Intelligence = Information + PEOPLE. Successful analytics isn’t about technology — it’s about people, process, and culture. The biggest trend in 2011 should be organizations spending the majority of their efforts on user adoption rather than technical implementation.

Unsurprisingly, there was still high demand for presentations on why BI projects fail and how to implement BI competency centers.  The new architectures probably resulted in even more emphasis on technology than ever, while business peoples’ expectations skyrocketed, fueled by advances in the consumer world. The result was probably even more dissatisfaction in the past, but the benefits of the new architectures should start becoming clearer during 2012.

What surprised me the most:

The rapid rise of Hadoop / NoSQL. The potentials of the technology have always been impressive, but I was surprised just how quickly these technology has been used to address real-life business problems (beyond the “big web” vendors where it originated), and how quickly it is becoming part of mainstream enterprise analytic architectures (e.g. Sybase IQ 15.4 includes native MapReduce APIs, Hadoop integration and federation, etc.)

Prediction for 2012:

As I sat down to gather my thoughts about BI in 2012, I quickly came up with the same long laundry list of BI topics as everybody else: in-memory, mobile, predictive, social, collaborative decision-making, data discovery, real-time, etc. etc.  All of these things are clearly important, and where going to continue to see great improvements this year. But I think that the real “next big thing” in BI is what I’m seeing when I talk to customers: they’re using these new opportunities not only to “improve analytics” but also fundamentally rethink some of their key business processes.

Instead of analytics being something that is used to monitor and eventually improve a business process, analytics is becoming a more fundamental part of the business process itself. One example is a large telco company that has transformed the way they attract customers. Instead of laboriously creating a range of rate plans, promoting them, and analyzing the results, they now use analytics to automatically create hundreds of more complex, personalized rate plans. They then throw them out into the market, monitor in real time, and quickly cull any that aren’t successful. It’s a way of doing business that would have been inconceivable in the past, and a lot more common in the future.

 

About

 

Timo Elliott

Timo Elliott is a 20-year veteran of SAP BusinessObjects, and has spent the last quarter-century working with customers around the world on information strategy.

He works closely with SAP research and innovation centers around the world to evangelize new technology prototypes.

His popular Business Analytics blog tracks innovation in analytics and social media, including topics such as augmented corporate reality, collaborative decision-making, and social network analysis.

His PowerPoint Twitter Tools lets presenters see and react to tweets in real time, embedded directly within their slides.

A popular and engaging speaker, Elliott presents regularly to IT and business audiences at international conferences, on subjects such as why BI projects fail and what to do about it, and the intersection of BI and enterprise 2.0.

Prior to Business Objects, Elliott was a computer consultant in Hong Kong and led analytics projects for Shell in New Zealand. He holds a first-class honors degree in Economics with Statistics from Bristol University, England

Timo can be contacted via Twitter at https://twitter.com/timoelliott

 Part 1 of this series was from James Kobielus, Forrestor at http://www.decisionstats.com/jim-kobielus-on-2012/

Interview JJ Allaire Founder, RStudio

Here is an interview with JJ Allaire, founder of RStudio. RStudio is the IDE that has overtaken other IDE within the R Community in terms of ease of usage. On the eve of their latest product launch, JJ talks to DecisionStats on RStudio and more.

Ajay-  So what is new in the latest version of RStudio and how exactly is it useful for people?

JJ- The initial release of RStudio as well as the two follow-up releases we did last year were focused on the core elements of using R: editing and running code, getting help, and managing files, history, workspaces, plots, and packages. In the meantime users have also been asking for some bigger features that would improve the overall work-flow of doing analysis with R. In this release (v0.95) we focused on three of these features:

Projects. R developers tend to have several (and often dozens) of working contexts associated with different clients, analyses, data sets, etc. RStudio projects make it easy to keep these contexts well separated (with distinct R sessions, working directories, environments, command histories, and active source documents), switch quickly between project contexts, and even work with multiple projects at once (using multiple running versions of RStudio).

Version Control. The benefits of using version control for collaboration are well known, but we also believe that solo data analysis can achieve significant productivity gains by using version control (this discussion on Stack Overflow talks about why). In this release we introduced integrated support for the two most popular open-source version control systems: Git and Subversion. This includes changelist management, file diffing, and browsing of project history, all right from within RStudio.

Code Navigation. When you look at how programmers work a surprisingly large amount of time is spent simply navigating from one context to another. Modern programming environments for general purpose languages like C++ and Java solve this problem using various forms of code navigation, and in this release we’ve brought these capabilities to R. The two main features here are the ability to type the name of any file or function in your project and go immediately to it; and the ability to navigate to the definition of any function under your cursor (including the definition of functions within packages) using a keystroke (F2) or mouse gesture (Ctrl+Click).

Ajay- What’s the product road map for RStudio? When can we expect the IDE to turn into a full fledged GUI?

JJ- Linus Torvalds has said that “Linux is evolution, not intelligent design.” RStudio tries to operate on a similar principle—the world of statistical computing is too deep, diverse, and ever-changing for any one person or vendor to map out in advance what is most important. So, our internal process is to ship a new release every few months, listen to what people are doing with the product (and hope to do with it), and then start from scratch again making the improvements that are considered most important.

Right now some of the things which seem to be top of mind for users are improved support for authoring and reproducible research, various editor enhancements including code folding, and debugging tools.

What you’ll see is us do in a given release is to work on a combination of frequently requested features, smaller improvements to usability and work-flow, bug fixes, and finally architectural changes required to support current or future feature requirements.

While we do try to base what we work on as closely as possible on direct user-feedback, we also adhere to some core principles concerning the overall philosophy and direction of the product. So for example the answer to the question about the IDE turning into a full-fledged GUI is: never. We believe that textual representations of computations provide fundamental advantages in transparency, reproducibility, collaboration, and re-usability. We believe that writing code is simply the right way to do complex technical work, so we’ll always look for ways to make coding better, faster, and easier rather than try to eliminate coding altogether.

Ajay -Describe your journey in science from a high school student to your present work in R. I noticed you have been very successful in making software products that have been mostly proprietary products or sold to companies.

Why did you get into open source products with RStudio? What are your plans for monetizing RStudio further down the line?

JJ- In high school and college my principal areas of study were Political Science and Economics. I also had a very strong parallel interest in both computing and quantitative analysis. My first job out of college was as a financial analyst at a government agency. The tools I used in that job were SAS and Excel. I had a dim notion that there must be a better way to marry computation and data analysis than those tools, but of course no concept of what this would look like.

From there I went more in the direction of general purpose computing, starting a couple of companies where I worked principally on programming languages and authoring tools for the Web. These companies produced proprietary software, which at the time (between 1995 and 2005) was a workable model because it allowed us to build the revenue required to fund development and to promote and distribute the software to a wider audience.

By 2005 it was however becoming clear that proprietary software would ultimately be overtaken by open source software in nearly all domains. The cost of development had shrunken dramatically thanks to both the availability of high-quality open source languages and tools as well as the scale of global collaboration possible on open source projects. The cost of promoting and distributing software had also collapsed thanks to efficiency of both distribution and information diffusion on the Web.

When I heard about R and learned more about it, I become very excited and inspired by what the project had accomplished. A group of extremely talented and dedicated users had created the software they needed for their work and then shared the fruits of that work with everyone. R was a platform that everyone could rally around because it worked so well, was extensible in all the right ways, and most importantly was free (as in speech) so users could depend upon it as a long-term foundation for their work.

So I started RStudio with the aim of making useful contributions to the R community. We started with building an IDE because it seemed like a first-rate development environment for R that was both powerful and easy to use was an unmet need. Being aware that many other companies had built successful businesses around open-source software, we were also convinced that we could make RStudio available under a free and open-source license (the AGPLv3) while still creating a viable business. At this point RStudio is exclusively focused on creating the best IDE for R that we can. As the core product gets where it needs to be over the next couple of years we’ll then also begin to sell other products and services related to R and RStudio.

About-

http://rstudio.org/docs/about

Jjallaire

JJ Allaire

JJ Allaire is a software engineer and entrepreneur who has created a wide variety of products including ColdFusion,Windows Live WriterLose It!, and RStudio.

From http://en.wikipedia.org/wiki/Joseph_J._Allaire
In 1995 Joseph J. (JJ) Allaire co-founded Allaire Corporation with his brother Jeremy Allaire, creating the web development tool ColdFusion.[1] In March 2001, Allaire was sold to Macromedia where ColdFusion was integrated into the Macromedia MX product line. Macromedia was subsequently acquired by Adobe Systems, which continues to develop and market ColdFusion.
After the sale of his company, Allaire became frustrated at the difficulty of keeping track of research he was doing using Google. To address this problem, he co-founded Onfolio in 2004 with Adam Berrey, former Allaire co-founder and VP of Marketing at Macromedia.
On March 8, 2006, Onfolio was acquired by Microsoft where many of the features of the original product are being incorporated into the Windows Live Toolbar. On August 13, 2006, Microsoft released the public beta of a new desktop blogging client called Windows Live Writer that was created by Allaire’s team at Microsoft.
Starting in 2009, Allaire has been developing a web-based interface to the widely used R technical computing environment. A beta version of RStudio was publicly released on February 28, 2011.
JJ Allaire received his B.A. from Macalester College (St. Paul, MN) in 1991.
RStudio-

RStudio is an integrated development environment (IDE) for R which works with the standard version of R available from CRAN. Like R, RStudio is available under a free software license. RStudio is designed to be as straightforward and intuitive as possible to provide a friendly environment for new and experienced R users alike. RStudio is also a company, and they plan to sell services (support, training, consulting, hosting) related to the open-source software they distribute.

Amazon gives away 750 hours /month of Windows based computing

and an additional 750 hours /month of Linux based computing. The windows instance is really quite easy for users to start getting the hang of cloud computing. and it is quite useful for people to tinker around, given Google’s retail cloud offerings are taking so long to hit the market

But it is only for new users.

http://aws.typepad.com/aws/2012/01/aws-free-usage-tier-now-includes-microsoft-windows-on-ec2.html

WS Free Usage Tier now Includes Microsoft Windows on EC2

The AWS Free Usage Tier now allows you to run Microsoft Windows Server 2008 R2 on an EC2 t1.micro instance for up to 750 hours per month. This benefit is open to new AWS customers and to those who are already participating in the Free Usage Tier, and is available in all AWS Regions with the exception of GovCloud. This is an easy way for Windows users to start learning about and enjoying the benefits of cloud computing with AWS.

The micro instances provide a small amount of consistent processing power and the ability to burst to a higher level of usage from time to time. You can use this instance to learn about Amazon EC2, support a development and test environment, build an AWS application, or host a web site (or all of the above). We’ve fine-tuned the micro instances to make them even better at running Microsoft Windows Server.

You can launch your instance from the AWS Management Console:

We have lots of helpful resources to get you started:

Along with 750 instance hours of Windows Server 2008 R2 per month, the Free Usage Tier also provides another 750 instance hours to run Linux (also on a t1.micro), Elastic Load Balancer time and bandwidth, Elastic Block Storage, Amazon S3 Storage, and SimpleDB storage, a bunch of Simple Queue Service and Simple Notification Service requests, and some CloudWatch metrics and alarms (see the AWS Free Usage Tier page for details). We’ve also boosted the amount of EBS storage space offered in the Free Usage Tier to 30GB, and we’ve doubled the I/O requests in the Free Usage Tier, to 2 million.

 

C4ISTAR for Hacking and Cyber Conflict

As per http://en.wikipedia.org/wiki/C4ISTAR

C2I stands for command, control, and intelligence.

C3I stands for command, control, communications, and intelligence.

C4I stands for command, control, communications, computers, and (military) intelligence.

C4ISTAR is the British acronym used to represent the group of the military functions designated by C4 (command, control, communications, computers), I (military intelligence), and STAR (surveillance, target acquisition, and reconnaissance) in order to enable the coordination of operations

I increasingly believe that cyber conflict will develop its own terminology and theory and paradigms in due time. In the meantime, it will adopt paradigms from existing military literature and adapt it to the unique sub culture of cyber conflict for both offensive, defensive as well as pre-emptive actions. Here I am theorizing for a case of targeted hacking attacks rather than massive attacks that bring down a website for a few hours and achieve nothing but a few press headlines . I would also theorize on countering such attacks.

So what would be the C4ISTAR for –

1) Media company supporting SOPA/PIPA/Take down Mega Upload-

Command and Control refers to the ability of commanders to direct forces-

This will be the senior executives including the members of board, legal officers, and public relationship/marketing people. Their name is available from corporate websites, and social media scraping can ensure both a list of contact addresses (online) as well as biases for phishing /malware attacks. This could also include phone (flooding or voicemail hacking ) attacks , and attacks against the email server of the company rather than the corporate website.

Communications– This will include all online and social media channels including websites of the media company , but also  those of the press relations firms handling communications , phones,websites- anything which the target is likely to communicate externally (and if possible internal communication)

Timing is everything- coordinating attacks immediately is juevenile, but it might be more mature to attack on vulnerable days like product launches or just before a board of directors meeting

Intelligence

Most corporates have an in-house research team, they can be easily targeted using social media channels, but also offline research and digging deep. Targeting intelligence corps of the target corporate is likely to produce a much better disruption. Eventually they can be persuaded to stop working for that corporate.

Computers– Anything that runs on electricity and can be disabled – should be disabled. This might require much more creativity than just flooding.

 surveillance-  This can be both online as well as offline, and would be of electronic assets, likely responses for the attack, and the key people who are to be disrupted.

target acquisition-  at least ten people within each corporate can and should be ideally disrupted, rather than just the website. this would call for social media scraping, and prior planning. even email in-boxes can be disrupted (if all else fails)

and reconnaissance-

study your target companies, target employees, and their strategies.

Then segment and prioritize in a list of  matrix of 10  to 10, who is more vulnerable and who is more valuable to attack.

the C4ISTAR for -a hacker activist organization is much more complicated but forensics reveal that most hackers tend to leave a signature style (in terms of computers,operating systems,machine ids,communication, tools, or even port numbers used)

the best defense for a media rich company to prevent hacking attacks is to first identify its own C4ISTAR structure for its digital content strategy and then fortify as well as scrub vulnerabilities (including from online information regarding its own employees)

(to be continued)

http://www.catb.org/~esr/faqs/hacker-howto.html

The Hacker Attitude

Going off Search Radar for 2012 Q1

I just used the really handy tools at

https://www.google.com/webmasters/tools/crawl-access

, clicked Remove URL

https://www.google.com/webmasters/tools/crawl-access?hl=en&siteUrl=https://decisionstats.com/&tid=removal-list

and submitted http://www.decisionstats.com

and I also modified my robots.txt file to

User-agent: *
Disallow: /

Just to make sure- I added the meta tag to each right margin of my blog

“<meta name=”robots” content=”noindex”>”

Now for last six months of 2011 as per Analytics, search engines were really generous to me- Giving almost 170 K page views,

Source                            Visits          Pages/Visit
1. google                       58,788                       2.14
2. (direct)                     10,832                       2.24
3. linkedin.com            2,038                       2.50
4. google.com                1,823                       2.15
5. bing                              1,007                      2.04
6. reddit.com                    749                       1.93
7. yahoo                              740                      2.25
8. google.co.in                  576                       2.13
9. search                             572                       2.07

 

I do like to experiment though, and I wonder if search engines just –

1) Make people lazy to bookmark or type the whole website name in Chrome/Opera  toolbars

2) Help disguise sources of traffic by encrypted search terms

3) Help disguise corporate traffic watchers and aggregators

So I am giving all spiders a leave for Q1 2012. I am interested in seeing impact of this on my traffic , and I suspect that the curves would not be as linear as I think.

Is search engine optimization over rated? Let the data decide…. 🙂

I am also interested in seeing how social sharing can impact traffic in the absence of search engine interaction effects- and whether it is possible to retain a bigger chunk of traffic by reducing SEO efforts and increasing social efforts!

 

Some Ways Anonymous Could Disrupt the Internet if SOPA is passed

This is a piece of science fiction. I wrote while reading Isaac Assimov’s advice to writers in GOLD, while on a beach in Anjuna.

1) Identify senators, lobbyists, senior executives of companies advocating for SOPA. Go for selective targeting of these people than massive Denial of Service Attacks.

This could also include election fund raising websites in the United States.

2) Create hacking tools with simple interfaces to probe commonly known software errors, to enable wider audience including the Occupy Movement students to participate in hacking. thus making hacking more democratic. What are the top 25 errors as per  http://cwe.mitre.org/cwss/

http://www.decisionstats.com/top-25-most-dangerous-software-errors/ ?

 

Easy interface tools to check vulnerabilities would be the next generation to flooding tools like HOIC, LOIC – Massive DDOS atttacks make good press coverage but not so good technically

3) Disrupt digital payment mechanisms for selected targets (in step1) using tools developed in Step 2, and introduce random noise errors in payment transfers.

4) Help create a better secure internet by embedding Tor within Chromium with all tools for anonymity embedded for easy usage – a more secure peer to peer browser (like a mashup of Opera , tor and chromium).

or maybe embed bit torrents within a browser.

5) Disrupt media companies and cloud computing based companies like iTunes, Spotify or Google Music, just like virus, ant i viruses disrupted the desktop model of computing. After that offer solutions to the problems like companies of anti virus software did for decades.

6) Hacking websites is fine fun, but hacking internet databases and massively parallel data scrapers can help disrupt some of the status quo.

This applies to databases that offer data for sale, like credit bureaus etc. Making this kind of data public will eliminate data middlemen.

7) Use cross border, cross country regulatory arbitrage for better risk control of hacker attacks.

8) recruiting among universities using easy to use hacking tools to expand the pool of dedicated hacker armies.

9) using operations like those targeting child pornography to increase political acceptability of the hacker sub culture. Refrain from overtly negative and unimaginative bad Press Relations

10) If you cant convince  them to pass SOPA, confuse them 😉 Use bots for random clicks on ads to confuse internet commerce.

 

Does Facebook deserve a 100 billion Valuation

some  questions in my Mind as I struggle to bet my money and pension savings on Facebook IPO

1) Revenue Mix- What percentage of revenues for Facebook come from Banner ads versus gaming partners like Zynga. How dependent is Facebook on Gaming partners. (Zynga has Google as an investor). What mix of revenue is dependent on privacy regulation countries like Europe vs countries like USA.

2) Do 800 million users of Facebook mean 100 billion valuation ? Thats a valuation of $125 in customer life time in terms of NPV . Since ad revenue is itself a percentage of actual good and services sold- how much worth of goods and services do consumers have to buy per capita , to give $125 worth of ads to FB. Eg . companies spend 5% of product cost on Facebook ads, so does that mean each FB account will hope to buy 2500$ worth of Goods from the Internet and from Facebook (assuming they also buy from Amazon etc)

3) Corporate Governance- Unlike Google, Facebook has faced troubling questions of ethics from the day it has started. This includes charges of intellectual property theft, but also non transparent FB stock option pricing in secondary markets before IPO, private placement by Wall Street Bankers like GoldMan Saachs, major investments by Russian Internet media corporations. (read- http://money.cnn.com/2011/01/03/technology/facebook_goldman/index.htm)

4) Retention of key employees post IPO- Key Employees at Google are actually ex- Microsofties. Key FB staff are ex-Google people. Where will the key -FB people go when bored and rich after IPO.

5) Does the macro Economic Condition justify the premium and Private Equity multiple of Facebook?

Will FB be the next Google (in terms of investor retruns) or will it be like Groupon. I suspect the answer  is- it depends on market discounting these assumptions while factoring in sentiment (as well as unloading of stock from large number of FB stock holders on week1).

Baby You Are a Rich Man. but not 100 billion rich. yet. Maybe 80 billion isnt that bad.