Tag: intelligence

RevoDeployR and commercial BI using R and R based cloud computing using Open CPU

Revolution Analytics has of course had RevoDeployR, and in a  webinar strive to bring it back to center spotlight.

BI is a good lucrative market, and visualization is a strength in R, so it is matter of time before we have more R based BI solutions. I really liked the two slides below for explaining RevoDeployR better to newbies like me (and many others!)

Integrating R into 3rd party and Web applications using RevoDeployR

Please click here to download the PDF.

Here are some additional links that may be of interest to you:

 

( I still think someone should make a commercial version of Jeroen Oom’s web interfaces and Jeff Horner’s web infrastructure (see below) for making customized Business Intelligence (BI) /Data Visualization solutions , UCLA and Vanderbilt are not exactly Stanford when it comes to deploying great academic solutions in the startup-tech world). I kind of think Google or someone at Revolution  should atleast dekko OpenCPU as a credible cloud solution in R.

I still cant figure out whether Revolution Analytics has a cloud computing strategy and Google seems to be working mysteriously as usual in broadening access to the Google Compute Cloud to the rest of R Community.

Open CPU  provides a free and open platform for statistical computing in the cloud. It is meant as an open, social analysis environment where people can share and run R functions and objects. For more details, visit the websit: www.opencpu.org

and esp see

https://public.opencpu.org/userapps/opencpu/opencpu.demo/runcode/

Jeff Horner’s

http://rapache.net/

Jerooen Oom’s

Google Visualization Tools Can Help You Build a Personal Dashboard

The Google Visualization API is a great way for people to make dashboards with slick graphics based  on data without getting into the fine print of the scripting language  itself.  It utilizes the same tools as Google itself does, and makes visualizing data using API calls to the Visualization API. Thus a real-time customizable dashboard that is publishable to the internet can be created within minutes, and more importantly insights can be much more easily drawn from graphs than from looking at rows of tables and numbers.

  1. There are 41 gadgets (including made by both Google and third-party developers ) available in the Gadget  Gallery ( https://developers.google.com/chart/interactive/docs/gadgetgallery)
  2. There are 12 kinds of charts available in the Chart Gallery (https://developers.google.com/chart/interactive/docs/gallery) .
  3. However there 26 additional charts in the charts page at https://developers.google.com/chart/interactive/docs/more_charts )

Building and embedding charts is simplified to a few steps

  • Load the AJAX API
  • Load the Visualization API and the appropriate package (like piechart or barchart from the kinds of chart)
  • Set a callback to run when the Google Visualization API is loaded
    • Within the Callback – It creates and populates a data table, instantiates the particular chart type chosen, passes in the data and draws it.
    • Create the data table with appropriately named columns and data rows.
    • Set chart options with Title, Width and Height
  • Instantiate and draw the chart, passing in some options including the name and id
  • Finally write the HTML/ Div that will hold the chart

You can simply copy and paste the code directly from https://developers.google.com/chart/interactive/docs/quick_start without getting into any details, and tweak them according to your data, chart preference and voila your web dashboard is ready!
That is the beauty of working with API- you can create and display genius ideas without messing with the scripting languages and code (too much). If you like to dive deeper into the API, you can look at the various objects at https://developers.google.com/chart/interactive/docs/reference

First launched in Mar 2008, Google Visualization API has indeed come a long way in making dashboards easier to build for people wanting to utilize advanced data visualization . It came about directly as a result of Google’s 2007 acquisition of GapMinder (of Hans Rosling fame).
As invariably and inevitably computing shifts to the cloud, visualization APIs will be very useful. Tableau Software has been a pioneer in selling data visualizing to the lucrative business intelligence and business dashboards community (you can see the Tableau Software API at http://onlinehelp.tableausoftware.com/v7.0/server/en-us/embed_api.htm ), and Google Visualization can do the same and capture business dashboard and visualization market , if there is more focus on integrating it from Google in it’s multiple and often confusing API offerings.
However as of now, this is quite simply the easiest way to create a web dashboard for your personal needs. Google guarantees 3 years of backward compatibility with this API and it is completely free.

Anonymous grows up and matures…Anonanalytics.com

I liked the design, user interfaces and the conceptual ideas behind the latest Anonymous hactivist websites (much better than the shabby graphic design of Wikileaks, or Friends of Wikileaks, though I guess they have been busy what with Julian’s escapades and Syrian emails)

 

I disagree  (and let us agree to disagree some of the time)

with the complete lack of respect for Graphical User Interfaces for tools. If dDOS really took off due to LOIC, why not build a GUI for SQL Injection (or atleats the top 25 vulnerability testing as by this list http://www.sans.org/top25-software-errors/

Shouldnt Tor be embedded within the next generation of Loic.

Automated testing tools are used by companies like Adobe (and others)… so why not create simple GUI for the existing tools.., I may be completely offtrack here.. but I think hacker education has been a critical misstep[ that has undermined Western Democracies preparedness for Cyber tactics by hostile regimes)…. how to create the next generation of hackers by easy tutorials (see codeacademy and build appropriate modules)

-A slick website to be funded by Bitcoins (Money can buy everything including Mastercard and Visa, but Bitcoins are an innovative step towards an internet economy  currency)

-A collobrative wiki

http://wiki.echelon2.org/wiki/Main_Page

Seriously dude, why not make this a part of Wikipedia- (i know Jimmy Wales got shifty eyes, but can you trust some1 )

-Analytics for Anonymous (sighs! I should have thought about this earlier)

http://anonanalytics.com/ (can be used to play and bill both sides of corporate espionage and be cyber private investigators)

What We Do

We provide the public with investigative reports exposing corrupt companies. Our team includes analysts, forensic accountants, statisticians, computer experts, and lawyers from various jurisdictions and backgrounds. All information presented in our reports is acquired through legal channels, fact-checked, and vetted thoroughly before release. This is both for the protection of our associates as well as groups/individuals who rely on our work.

_and lastly creative content for Pinterest.com and Public Relations ( what next-? Tom Cruise to play  Julian Assange in the new Movie ?)

http://www.par-anoia.net/ />Potentially Alarming Research: Anonymous Intelligence AgencyInformation is and will be free. Expect it. ~ Anonymous

Links of interest

  • Latest Scientology Mails (Austria)
  • Full FBI call transcript
  • Arrest Tracker
  • HBGary Email Viewer
  • The Pirate Bay Proxy
  • We Are Anonymous – Book
  • To be announced…

 

R for Business Analytics- Book by Ajay Ohri

So the cover art is ready, and if you are a reviewer, you can reserve online copies of the book I have been writing for past 2 years. Special thanks to my mentors, detractors, readers and students- I owe you a beer!

You can also go here-

http://www.springer.com/statistics/book/978-1-4614-4342-1

 

R for Business Analytics

R for Business Analytics

Ohri, Ajay

2012, 2012, XVI, 300 p. 208 illus., 162 in color.

Hardcover
Information

ISBN 978-1-4614-4342-1

Due: September 30, 2012

(net)

approx. 44,95 €
  • Covers full spectrum of R packages related to business analytics
  • Step-by-step instruction on the use of R packages, in addition to exercises, references, interviews and useful links
  • Background information and exercises are all applied to practical business analysis topics, such as code examples on web and social media analytics, data mining, clustering and regression models

R for Business Analytics looks at some of the most common tasks performed by business analysts and helps the user navigate the wealth of information in R and its 4000 packages.  With this information the reader can select the packages that can help process the analytical tasks with minimum effort and maximum usefulness. The use of Graphical User Interfaces (GUI) is emphasized in this book to further cut down and bend the famous learning curve in learning R. This book is aimed to help you kick-start with analytics including chapters on data visualization, code examples on web analytics and social media analytics, clustering, regression models, text mining, data mining models and forecasting. The book tries to expose the reader to a breadth of business analytics topics without burying the user in needless depth. The included references and links allow the reader to pursue business analytics topics.

 

This book is aimed at business analysts with basic programming skills for using R for Business Analytics. Note the scope of the book is neither statistical theory nor graduate level research for statistics, but rather it is for business analytics practitioners. Business analytics (BA) refers to the field of exploration and investigation of data generated by businesses. Business Intelligence (BI) is the seamless dissemination of information through the organization, which primarily involves business metrics both past and current for the use of decision support in businesses. Data Mining (DM) is the process of discovering new patterns from large data using algorithms and statistical methods. To differentiate between the three, BI is mostly current reports, BA is models to predict and strategize and DM matches patterns in big data. The R statistical software is the fastest growing analytics platform in the world, and is established in both academia and corporations for robustness, reliability and accuracy.

Content Level » Professional/practitioner

Keywords » Business Analytics – Data Mining – Data Visualization – Forecasting – GUI – Graphical User Interface – R software – Text Mining

Related subjects » Business, Economics & Finance – Computational Statistics – Statistics

TABLE OF CONTENTS

Why R.- R Infrastructure.- R Interfaces.- Manipulating Data.- Exploring Data.- Building Regression Models.- Data Mining using R.- Clustering and Data Segmentation.- Forecasting and Time-Series Models.- Data Export and Output.- Optimizing your R Coding.- Additional Training Literature.- Appendix

Interview: Hjálmar Gíslason, CEO of DataMarket.com

Here is an interview with Hjálmar Gíslason, CEO of Datamarket.com  . DataMarket is an active marketplace for structured data and statistics. Through powerful search and visual data exploration, DataMarket connects data seekers with data providers.

 

Ajay-  Describe your journey as an entrepreneur and techie in Iceland. What are the 10 things that surprised you most as a tech entrepreneur.

HG- DataMarket is my fourth tech start-up since at age 20 in 1996. The previous ones have been in gaming, mobile and web search. I come from a technical background but have been moving more and more to the business side over the years. I can still prototype, but I hope there isn’t a single line of my code in production!

Funny you should ask about the 10 things that have surprised me the most on this journey, as I gave a presentation – literally yesterday – titled: “9 things nobody told me about the start-up business”

They are:
* Do NOT generalize – especially not to begin with
* Prioritize – and find a work-flow that works for you
* Meet people – face to face
* You are a sales person – whether you like it or not
* Technology is not a product – it’s the entire experience
* Sell the current version – no matter how amazing the next one is
* Learn from mistakes – preferably others’
* Pick the right people – good people is not enough
* Tell a good story – but don’t make them up

I obviously elaborate on each of these points in the talk, but the points illustrate roughly some of the things I believe I’ve learned … so far 😉

9 things nobody told me about the start-up business

Ajay-

Both Amazon  and Google  have entered the public datasets space. Infochimps  has 14,000+ public datasets. The US has http://www.data.gov/

So clearly the space is both competitive and yet the demand for public data repositories is clearly under served still. 

How does DataMarket intend to address this market in a unique way to differentiate itself from others.

HG- DataMarket is about delivering business data to decision makers. We help data seekers find the data they need for planning and informed decision making, and data publishers reaching this audience. DataMarket.com is the meeting point, where data seekers can come to find the best available data, and data publishers can make their data available whether for free or for a fee. We’ve populated the site with a wealth of data from public sources such as the UN, Eurostat, World Bank, IMF and others, but there is also premium data that is only available to those that subscribe to and pay for the access. For example we resell the entire data offering from the EIU (Economist Intelligence Unit) (link: http://datamarket.com/data/list/?q=provider:eiu)

DataMarket.com allows all this data to be searched, visualized, compared and downloaded in a single place in a standard, unified manner.

We see many of these efforts not as competition, but as valuable potential sources of data for our offering, while others may be competing with parts of our proposition, such as easy access to the public data sets.

 

Ajay- What are your views on data confidentiality and access to data owned by Governments funded by tax payer money.

HG- My views are very simple: Any data that is gathered or created for taxpayers’ money should be open and free of charge unless higher priorities such as privacy or national security indicate otherwise.

Reflecting that, any data that is originally open and free of charge is still open and free of charge on DataMarket.com, just easier to find and work with.

Ajay-  How is the technology entrepreneurship and venture capital scene in Iceland. What things work and what things can be improved?

HG- The scene is quite vibrant, given the small community. Good teams with promising concepts have been able to get the funding they need to get started and test their footing internationally. When the rapid growth phase is reached outside funding may still be needed.

There are positive and negative things about any location. Among the good things about Iceland from the stand point of a technology start-up are highly skilled tech people and a relatively simple corporate environment. Among the bad things are a tiny local market, lack of skills in international sales and marketing and capital controls that were put in place after the crash of the Icelandic economy in 2008.

I’ve jokingly said that if a company is hot in the eyes of VCs it would get funding even if it was located in the jungles of Congo, while if they’re only lukewarm towards you, they will be looking for any excuse not to invest. Location can certainly be one of them, and in that case being close to the investor communities – physically – can be very important.

We’re opening up our sales and marketing offices in Boston as we speak. Not to be close to investors though, but to be close to our market and current customers.

Ajay- Describe your hobbies when you are not founding amazing tech startups.

HG- Most of my time is spent working – which happens to by my number one hobby.

It is still important to step away from it all every now and then to see things in perspective and come back with a clear mind.

I *love* traveling to exotic places. Me and my wife have done quite a lot of traveling in Africa and S-America: safari, scuba diving, skiing, enjoying nature. When at home I try to do some sports activities 3-4 times a week at least, and – recently – play with my now 8 month old son as much as I can.

About-

http://datamarket.com/p/about/team/

Management

Hjalmar GislasonHjálmar Gíslason, Founder and CEO: Hjalmar is a successful entrepreneur, founder of three startups in the gaming, mobile and web sectors since 1996. Prior to launching DataMarket, Hjalmar worked on new media and business development for companies in the Skipti Group (owners of Iceland Telecom) after their acquisition of his search startup – Spurl. Hjalmar offers a mix of business, strategy and technical expertise. DataMarket is based largely on his vision of the need for a global exchange for structured data.

hjalmar.gislason@datamarket.com

To know more, have a quick  look at  http://datamarket.com/

Oracle launches its version of R #rstats

From-

http://www.oracle.com/us/corporate/press/1515738

Integrates R Statistical Programming Language into Oracle Database 11g

News Facts

Oracle today announced the availability of Oracle Advanced Analytics, a new option for Oracle Database 11g that bundles Oracle R Enterprise together with Oracle Data Mining.
Oracle R Enterprise delivers enterprise class performance for users of the R statistical programming language, increasing the scale of data that can be analyzed by orders of magnitude using Oracle Database 11g.
R has attracted over two million users since its introduction in 1995, and Oracle R Enterprise dramatically advances capability for R users. Their existing R development skills, tools, and scripts can now also run transparently, and scale against data stored in Oracle Database 11g.
Customer testing of Oracle R Enterprise for Big Data analytics on Oracle Exadata has shown up to 100x increase in performance in comparison to their current environment.
Oracle Data Mining, now part of Oracle Advanced Analytics, helps enable customers to easily build and deploy predictive analytic applications that help deliver new insights into business performance.
Oracle Advanced Analytics, in conjunction with Oracle Big Data Appliance, Oracle Exadata Database Machine and Oracle Exalytics In-Memory Machine, delivers the industry’s most integrated and comprehensive platform for Big Data analytics.

Comprehensive In-Database Platform for Advanced Analytics

Oracle Advanced Analytics brings analytic algorithms to data stored in Oracle Database 11g and Oracle Exadata as opposed to the traditional approach of extracting data to laptops or specialized servers.
With Oracle Advanced Analytics, customers have a comprehensive platform for real-time analytic applications that deliver insight into key business subjects such as churn prediction, product recommendations, and fraud alerting.
By providing direct and controlled access to data stored in Oracle Database 11g, customers can accelerate data analyst productivity while maintaining data security throughout the enterprise.
Powered by decades of Oracle Database innovation, Oracle R Enterprise helps enable analysts to run a variety of sophisticated numerical techniques on billion row data sets in a matter of seconds making iterative, speed of thought, and high-quality numerical analysis on Big Data practical.
Oracle R Enterprise drastically reduces the time to deploy models by eliminating the need to translate the models to other languages before they can be deployed in production.
Oracle R Enterprise integrates the extensive set of Oracle Database data mining algorithms, analytics, and access to Oracle OLAP cubes into the R language for transparent use by R users.
Oracle Data Mining provides an extensive set of in-database data mining algorithms that solve a wide range of business problems. These predictive models can be deployed in Oracle Database 11g and use Oracle Exadata Smart Scan to rapidly score huge volumes of data.
The tight integration between R, Oracle Database 11g, and Hadoop enables R users to write one R script that can run in three different environments: a laptop running open source R, Hadoop running with Oracle Big Data Connectors, and Oracle Database 11g.
Oracle provides single vendor support for the entire Big Data platform spanning the hardware stack, operating system, open source R, Oracle R Enterprise and Oracle Database 11g.
To enable easy enterprise-wide Big Data analysis, results from Oracle Advanced Analytics can be viewed from Oracle Business Intelligence Foundation Suite and Oracle Exalytics In-Memory Machine.

Supporting Quotes

“Oracle is committed to meeting the challenges of Big Data analytics. By building upon the analytical depth of Oracle SQL, Oracle Data Mining and the R environment, Oracle is delivering a scalable and secure Big Data platform to help our customers solve the toughest analytics problems,” said Andrew Mendelsohn, senior vice president, Oracle Server Technologies.
“We work with leading edge customers who rely on us to deliver better BI from their Oracle Databases. The new Oracle R Enterprise functionality allows us to perform deep analytics on Big Data stored in Oracle Databases. By leveraging R and its library of open source contributed CRAN packages combined with the power and scalability of Oracle Database 11g, we can now do that,” said Mark Rittman, co-founder, Rittman Mead.
Oracle Advanced Analytics — an option to Oracle Database 11g Enterprise Edition – extends the database into a comprehensive advanced analytics platform through two major components: Oracle R Enterprise and Oracle Data Mining. With Oracle Advanced Analytics, customers have a comprehensive platform for real-time analytic applications that deliver insight into key business subjects such as churn prediction, product recommendations, and fraud alerting.

Oracle R Enterprise tightly integrates the open source R programming language with the database to further extend the database with Rs library of statistical functionality, and pushes down computations to the database. Oracle R Enterprise dramatically advances the capability for R users, and allows them to use their existing R development skills and tools, and scripts can now also run transparently and scale against data stored in Oracle Database 11g.

Oracle Data Mining provides powerful data mining algorithms that run as native SQL functions for in-database model building and model deployment. It can be accessed through the SQL Developer extension Oracle Data Miner to build, evaluate, share and deploy predictive analytics methodologies. At the same time the high-performance Oracle-specific data mining algorithms are accessible from R.

BENEFITS
  • Scalability—Allows customers to easily scale analytics as data volume increases by bringing the algorithms to where the data resides – in the database
  • Performance—With analytical operations performed in the database, R users can take advantage of the extreme performance of Oracle Exadata
  • Security—Provides data analysts with direct but controlled access to data in Oracle Database 11g, accelerating data analyst productivity while maintaining data security
  • Save Time and Money—Lowers overall TCO for data analysis by eliminating data movement and shortening the time it takes to transform “raw data” into “actionable information”
Oracle R Hadoop Connector Gives R users high performance native access to Hadoop Distributed File System (HDFS) and MapReduce programming framework.
This is a  R package
From the datasheet at

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

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