You cant DELETE a Facebook Account- it gets deactivated NOT DELETED.
You have to delete photo albums one by one, but if you have a folder like profile photos or wall photos or mobile uploads (you cant delete these folders you have to delete those photos one by one)
So I had to delete 1100 friends, delete all Facebook Pages I created, and then download the account- (photos) which were now a more easy to download zip file of 92 mb. And I deleted all the 250+ Likes I had given to things I had flippantly liked- it was horrifying because if you accumulate all that info- it basically gives you a big lead in estimating my psychological profile- and thats not stuff I want to be used for selling.
Then I deactivated it- no like Lord Voldermort’s horcruxes you cant delete it all.
and Facebook shows you ads even if you clean your profile and your friends and can longer see any preference for any product.
Facebook treats data like prisoners – even if you are released they WILL maintain your record.
20 years later they would be able to blackmail all the people of all countries in the WORLD- by that much info.
And Linkedin is still getting deleted- I got this email from them-
basically if you have an active group for whom you are the only owner you cant delete yourself- you have to delete the group or find another owner.
Sigh!
If it took me 2 days to download all my info, and wipe my social media for just 3 yrs of using it (albiet at an expert enough level to act as a social media consultant to some companies)- I am not sure what today’s generation of young people who jump to twitter and Facebook at early ages would face after say 5-10 years of data is collected on them. Lots of Ads I guess!
Here is a set of very nice, screenshot enabled tutorials from SAP BI. They are a bit outdated (3 years old) but most of it is quite relevant- especially from a Tutorial Design Perspective –
Most people would rather see screenshot based step by step powerpoints, than cluttered or clever presentations , or even videos that force you to sit like a TV zombie. Unfortunately most tutorial presentations I see especially for BI are either slides with one or two points, that abruptly shift to “concepts” or videos that are atleast more than 10 minutes long. That works fine for scripting tutorials or hands on workshops, but cannot be reproduced for later instances of study.
The mode of tutorials especially for GUI software can vary, it may be Slideshare, Scribd, Google Presentation,Microsoft Powerpoint but a step by step screenshot by screenshot tutorial is much better for understanding than commando line jargon/ Youtub Videos presentations, or Powerpoint with Points.
Have a look at these SAP BI 7 slideshares
and
Speaking of BI, the R Package called Brew is going to brew up something special especially combined with R Apache. However I wish R Apache, or R Web, or RServe had step by step install screenshot tutorials to increase their usage in Business Intelligence.
I tried searching for JMP GUI Tutorials too, but I believe putting all your content behind a registration wall is not so great. Do a Pareto Analysis of your training material, surely you can share a couple more tutorials without registration. It also will help new wanna-migrate users to get a test and feel for the installation complexities as well as final report GUI.
Here is an interview with James Dixon the founder of Pentaho, self confessed Chief Geek and CTO. Pentaho has been growing very rapidly and it makes open source Business Intelligence solutions- basically the biggest chunk of enterprise software market currently.
Ajay- How would you describe Pentaho as a BI product for someone who is completely used to traditional BI vendors (read non open source). Do the Oracle lawsuits over Java bother you from a business perspective?
The Oracle/Java issue does not bother me much. There are a lot of software companies dependent on Java. If Oracle abandons Java a lot resources will suddenly focus on OpenJDK. It would be good for OpenJDK and might be the best thing for Java in the long term.
Ajay- What parts of Pentaho’s technology do you personally like the best as having an advantage over other similar proprietary packages.
Describe the latest Pentaho for Hadoop offering and Hadoop/HIVE ‘s advantage over say Map Reduce and SQL.
James- The coolest thing is that everything is pluggable:
* ETL: New data transformation steps can be added. New orchestration controls (job entries) can be added. New perspectives can be added to the design UI. New data sources and destinations can be added.
* Reporting: New content types and report objects can be added. New data sources can be added.
* BI Server: Every factory, engine, and layer can be extended or swapped out via configuration. BI components can be added. New visualizations can be added.
This means it is very easy for Pentaho, partners, customers, and community member to extend our software to do new things.
In addition every engine and component can be fully embedded into a desktop or web-based application. I made a youtube video about our philosophy: http://www.youtube.com/watch?v=uMyR-In5nKE
Our Hadoop offerings allow ETL developers to work in a familiar graphical design environment, instead of having to code MapReduce jobs in Java or Python.
90% of the Hadoop use cases we hear about are transformation/reporting/analysis of structured/semi-structured data, so an ETL tool is perfect for these situations.
Using Pentaho Data Integration reduces implementation and maintenance costs significantly. The fact that our ETL engine is Java and is embeddable means that we can deploy the engine to the Hadoop data nodes and transform the data within the nodes.
Ajay- Do you think the combination of recession, outsourcing,cost cutting, and unemployment are a suitable environment for companies to cut technology costs by going out of their usual vendor lists and try open source for a change /test projects.
Jamie- Absolutely. Pentaho grew (downloads, installations, revenue) throughout the recession. We are on target to do 250% of what we did last year, while the established vendors are flat in terms of new license revenue.
Ajay- How would you compare the user interface of reports using Pentaho versus other reporting software. Please feel free to be as specific.
James- We have all of the everyday, standard reporting features covered.
Over the years the old tools, like Crystal Reports, have become bloated and complicated.
We don’t aim to have 100% of their features, because we’d end us just as complicated.
The 80:20 rule applies here. 80% of the time people only use 20% of their features.
We aim for 80% feature parity, which should cover 95-99% of typical use cases.
Ajay- Could you describe the Pentaho integration with R as well as your relationship with Weka. Jaspersoft already has a partnership with Revolution Analytics for RevoDeployR (R on a web server)-
Any R plans for Pentaho as well?
James- The feature set of R and Weka overlap to a small extent – both of them include basic statistical functions. Weka is focused on predictive models and machine learning, whereas R is focused on a full suite of statistical models. The creator and main Weka developer is a Pentaho employee. We have integrated R into our ETL tool. (makes me happy 🙂 )
(probably not a good time to ask if SAS integration is done as well for a big chunk of legacy base SAS/ WPS users)
About-
As “Chief Geek” (CTO) at Pentaho, James Dixon is responsible for Pentaho’s architecture and technology roadmap. James has over 15 years of professional experience in software architecture, development and systems consulting. Prior to Pentaho, James held key technical roles at AppSource Corporation (acquired by Arbor Software which later merged into Hyperion Solutions) and Keyola (acquired by Lawson Software). Earlier in his career, James was a technology consultant working with large and small firms to deliver the benefits of innovative technology in real-world environments.
it is a simple utility that adds on your Firefox browser– and simply traps all cookies floating around on public wi-fis like airports, university campuses, caltrain and soon san fransisco
Basically White Hat Hacking made easy so you can pose as anyone else on Facebook– if they are logged in nearby
When logging into a website you usually start by submitting your username and password. The server then checks to see if an account matching this information exists and if so, replies back to you with a “cookie” which is used by your browser for all subsequent requests.
It’s extremely common for websites to protect your password by encrypting the initial login, but surprisingly uncommon for websites to encrypt everything else. This leaves the cookie (and the user) vulnerable. HTTP session hijacking (sometimes called “sidejacking“) is when an attacker gets a hold of a user’s cookie, allowing them to do anything the user can do on a particular website. On an open wireless network, cookies are basically shouted through the air, making these attacks extremely easy.
Here is a short list of resources and material I put together as starting points for R and Cloud Computing It’s a bit messy but overall should serve quite comprehensively.
Cloud computing is a commonly used expression to imply a generational change in computing from desktop-servers to remote and massive computing connections,shared computers, enabled by high bandwidth across the internet.
As per the National Institute of Standards and Technology Definition,
Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.
Rweb is developed and maintained by Jeff Banfield. The Rweb Home Page provides access to all three versions of Rweb—a simple text entry form that returns output and graphs, a more sophisticated JavaScript version that provides a multiple window environment, and a set of point and click modules that are useful for introductory statistics courses and require no knowledge of the R language. All of the Rweb versions can analyze Web accessible datasets if a URL is provided.
The paper “Rweb: Web-based Statistical Analysis”, providing a detailed explanation of the different versions of Rweb and an overview of how Rweb works, was published in the Journal of Statistical Software (http://www.jstatsoft.org/v04/i01/).
Ulf Bartel has developed R-Online, a simple on-line programming environment for R which intends to make the first steps in statistical programming with R (especially with time series) as easy as possible. There is no need for a local installation since the only requirement for the user is a JavaScript capable browser. See http://osvisions.com/r-online/ for more information.
Rcgi is a CGI WWW interface to R by MJ Ray. It had the ability to use “embedded code”: you could mix user input and code, allowing the HTMLauthor to do anything from load in data sets to enter most of the commands for users without writing CGI scripts. Graphical output was possible in PostScript or GIF formats and the executed code was presented to the user for revision. However, it is not clear if the project is still active.
Currently, a modified version of Rcgi by Mai Zhou (actually, two versions: one with (bitmap) graphics and one without) as well as the original code are available from http://www.ms.uky.edu/~statweb/.
David Firth has written CGIwithR, an R add-on package available from CRAN. It provides some simple extensions to R to facilitate running R scripts through the CGI interface to a web server, and allows submission of data using both GET and POST methods. It is easily installed using Apache under Linux and in principle should run on any platform that supports R and a web server provided that the installer has the necessary security permissions. David’s paper “CGIwithR: Facilities for Processing Web Forms Using R” was published in the Journal of Statistical Software (http://www.jstatsoft.org/v08/i10/). The package is now maintained by Duncan Temple Lang and has a web page athttp://www.omegahat.org/CGIwithR/.
Rpad, developed and actively maintained by Tom Short, provides a sophisticated environment which combines some of the features of the previous approaches with quite a bit of JavaScript, allowing for a GUI-like behavior (with sortable tables, clickable graphics, editable output), etc.
Jeff Horner is working on the R/Apache Integration Project which embeds the R interpreter inside Apache 2 (and beyond). A tutorial and presentation are available from the project web page at http://biostat.mc.vanderbilt.edu/twiki/bin/view/Main/RApacheProject.
Rserve is a project actively developed by Simon Urbanek. It implements a TCP/IP server which allows other programs to use facilities of R. Clients are available from the web site for Java and C++ (and could be written for other languages that support TCP/IP sockets).
OpenStatServer is being developed by a team lead by Greg Warnes; it aims “to provide clean access to computational modules defined in a variety of computational environments (R, SAS, Matlab, etc) via a single well-defined client interface” and to turn computational services into web services.
Two projects use PHP to provide a web interface to R. R_PHP_Online by Steve Chen (though it is unclear if this project is still active) is somewhat similar to the above Rcgi and Rweb. R-php is actively developed by Alfredo Pontillo and Angelo Mineo and provides both a web interface to R and a set of pre-specified analyses that need no R code input.
webbioc is “an integrated web interface for doing microarray analysis using several of the Bioconductor packages” and is designed to be installed at local sites as a shared computing resource.
Rwui is a web application to create user-friendly web interfaces for R scripts. All code for the web interface is created automatically. There is no need for the user to do any extra scripting or learn any new scripting techniques. Rwui can also be found at http://rwui.cryst.bbk.ac.uk.
Finally, the R.rsp package by Henrik Bengtsson introduces “R Server Pages”. Analogous to Java Server Pages, an R server page is typically HTMLwith embedded R code that gets evaluated when the page is requested. The package includes an internal cross-platform HTTP server implemented in Tcl, so provides a good framework for including web-based user interfaces in packages. The approach is similar to the use of the brew package withRapache with the advantage of cross-platform support and easy installation.
Remote access to R/Bioconductor on EBI’s 64-bit Linux Cluster
Start the workbench by downloading the package for your operating system (Macintosh or Windows), or via Java Web Start, and you will get access to an instance of R running on one of EBI’s powerful machines. You can install additional packages, upload your own data, work with graphics and collaborate with colleagues, all as if you are running R locally, but unlimited by your machine’s memory, processor or data storage capacity.
Most up-to-date R version built for multicore CPUs
Access to all Bioconductor packages
Access to our computing infrastructure
Fast access to data stored in EBI’s repositories (e.g., public microarray data in ArrayExpress)
Using R Google Docs http://www.omegahat.org/RGoogleDocs/run.pdf
It uses the XML and RCurl packages and illustrates that it is relatively quick and easy
to use their primitives to interact with Web services.
Amazon’s EC2 is a type of cloud that provides on demand computing infrastructures called an Amazon Machine Images or AMIs. In general, these types of cloud provide several benefits:
Simple and convenient to use. An AMI contains your applications, libraries, data and all associated configuration settings. You simply access it. You don’t need to configure it. This applies not only to applications like R, but also can include any third-party data that you require.
On-demand availability. AMIs are available over the Internet whenever you need them. You can configure the AMIs yourself without involving the service provider. You don’t need to order any hardware and set it up.
Elastic access. With elastic access, you can rapidly provision and access the additional resources you need. Again, no human intervention from the service provider is required. This type of elastic capacity can be used to handle surge requirements when you might need many machines for a short time in order to complete a computation.
Pay per use. The cost of 1 AMI for 100 hours and 100 AMI for 1 hour is the same. With pay per use pricing, which is sometimes called utility pricing, you simply pay for the resources that you use.
#This example requires you had previously created a bucket named data_language on your Google Storage and you had uploaded a CSV file named language_id.txt (your data) into this bucket – see for details
library(predictionapirwrapper)
Elastic-R is a new portal built using the Biocep-R platform. It enables statisticians, computational scientists, financial analysts, educators and students to use cloud resources seamlessly; to work with R engines and use their full capabilities from within simple browsers; to collaborate, share and reuse functions, algorithms, user interfaces, R sessions, servers; and to perform elastic distributed computing with any number of virtual machines to solve computationally intensive problems.
Also see Karim Chine’s http://biocep-distrib.r-forge.r-project.org/
R for Salesforce.com
At the point of writing this, there seem to be zero R based apps on Salesforce.com This could be a big opportunity for developers as both Apex and R have similar structures Developers could write free code in R and charge for their translated version in Apex on Salesforce.com
Force.com and Salesforce have many (1009) apps at http://sites.force.com/appexchange/home for cloud computing for
businesses, but very few forecasting and statistical simulation apps.
These are like iPhone apps except meant for business purposes (I am
unaware if any university is offering salesforce.com integration
though google apps and amazon related research seems to be on)
Personal Note-Mentioning SAS in an email to a R list is a big no-no in terms of getting a response and love. Same for being careless about which R help list to email (like R devel or R packages or R help)
I am currently playing/ trying out RApache- one more excellent R product from Vanderbilt’s excellent Dept of Biostatistics and it’s prodigious coder Jeff Horner.
I really liked the virtual machine idea- you can download a virtual image of Rapache and play with it- .vmx is easy to create and great to share-
Basically using R Apache (with an EC2 on backend) can help you create customized dashboards, BI apps, etc all using R’s graphical and statistical capabilities.
Rapache embeds the R interpreter inside the Apache 2 web server. By doing this, Rapache realizes the full potential of R and its facilities over the web. R programmers configure appache by mapping Universal Resource Locaters (URL’s) to either R scripts or R functions. The R code relies on CGI variables to read a client request and R’s input/output facilities to write the response.
One advantage to Rapache’s architecture is robust multi-process management by Apache. In contrast to Rserve and RSOAP, Rapache is a pre-fork server utilizing HTTP as the communications protocol. Another advantage is a clear separation, a loose coupling, of R code from client code. With Rserve and RSOAP, the client must send data and R commands to be executed on the server. With Rapache the only client requirements are the ability to communicate via HTTP. Additionally, Rapache gains significant authentication, authorization, and encryption mechanism by virtue of being embedded in Apache.
Existing Demos of Architechture based on R Apache-
You can download version 1.1.10 of rApache now. There
are only two significant changes and you don’t have to edit your
apache config or change any code (just recompile rApache and
reinstall):
1) Error reporting should be more informative. both when you
accidentally introduce errors in the Apache config, and when your code
introduces warnings and errors from web requests.
I’ve struggled with this one for awhile, not really knowing what
strategy would be best. Basically, rApache hooks into the R I/O layer
at such a low level that it’s hard to capture all warnings and errors
as they occur and introduce them to the user in a sane manner. In
prior releases, when ROutputErrors was in effect (either the apache
directive or the R function) one would typically see a bunch of grey
boxes with a red outline with a title of RApache Warning/Error!!!.
Unfortunately those grey boxes could contain empty lines, one line of
error, or a few that relate to the lines in previously displayed
boxes. Really a big uninformative mess.
The new approach is to print just one warning box with the title
“”Oops!!! <b>rApache</b> has something to tell you. View source and
read the HTML comments at the end.” and then as the title implies you
can read the HTML comment located at the end of the file… after the
closing html. That way, you’re actually reading how R would present
the warnings and errors to you as if you executed the code at the R
command prompt. And if you don’t use ROutputErrors, the warning/error
messages are printed in the Apache log file, just as they were before,
but nicer 😉
2) Code dispatching has changed so please let me know if I’ve
introduced any strange behavior.
This was necessary to enhance error reporting. Prior to this release,
rApache would use R’s C API exclusively to build up the call to your
code that is then passed to R’s evaluation engine. The advantage to
this approach is that it’s much more efficient as there is no parsing
involved, however all information about parse errors, files which
produced errors, etc. were lost. The new approach uses R’s built-in
parse function to build up the call and then passes it of to R. A
slight overhead, but it should be negligible. So, if you feel that
this approach is too slow OR I’ve introduced bugs or strange behavior,
please let me know.
FUTURE PLANS
I’m gaining more experience building Debian/Ubuntu packages each day,
so hopefully by some time in 2011 you can rely on binary releases for
these distributions and not install rApache from source! Fingers
crossed!
Development on the rApache 1.1 branch will be winding down (save bug
fix releases) as I transition to the 1.2 branch. This will involve
taking out a small chunk of code that defines the rApache development
environment (all the CGI variables and the functions such as
setHeader, setCookie, etc) and placing it in its own R package…
unnamed as of yet. This is to facilitate my development of the ralite
R package, a small single user cross-platform web server.
The goal for ralite is to speed up development of R web applications,
take out a bit of friction in the development process by not having to
run the full rApache server. Plus it would allow users to develop in
the rApache enronment while on windows and later deploy on more
capable server environments. The secondary goal for ralite is it’s use
in other web server environments (nginx and IIS come to mind) as a
persistent per-client process.
And finally, wiki.rapache.net will be the new www.rapache.net once I
translate the manual over… any day now.
Cisco SocialMiner is a social media customer care solution that can help you proactively respond to customers and prospects communicating through public social media networks like Twitter, Facebook, or other public forums or blogging sites. By providing social media monitoring, queuing, and workflow to organize customer posts on social media networks and deliver them to your social media customer care team, your company can respond to customers in real time using the same social network they are using.
Cisco SocialMiner provides:
The ability to configure multiple campaigns to search for customer postings on the public social web about your company’s products, services, or area of expertise
Filtering of social contacts based on preconfigured campaign filters to focus campaign searches
Routing of social contacts to skilled customer care representatives in the contact center or to experts in the enterprise–multiple people can work together to handle responses to customer postings through shared work queues
Detailed metrics for social media customer care activities, campaign reports, and team reports
With Cisco SocialMiner, your company can listen and respond to customer conversations originating in the social web. Being proactive can help your company enhance its service, improve customer loyalty, garner new customers, and protect your brand.
Table 1. Features and Benefits of Cisco SocialMiner 8.5
Feature
Benefits
Product Baseline Features
Social media feeds
• Feeds are configurable sources to capture public social contacts that contain specific words, terms, or phrases.
• Feeds enable you to search for information on the public social web about your company’s products, services, or area of expertise.
• Cisco SocialMiner supports the following types of feeds:
• Groups feeds into campaigns to organize all posting activity related to a product category or business objective
• Produces metrics on campaign activity
• Provides the ability to configure multiple campaigns to search for customer postings on specific products or services
• Groups social contacts for handling by the social media customer care team
• Enables filtering of social contacts based on preconfigured campaign filters to focus campaign searches
Route and queue social contacts
• Enables routing of social contacts to skilled customer care representatives in the contact center
• Draws on expertise in the enterprise by allowing multiple people in the enterprise to work together to handle responses to customer postings through shared work queues
• Enables automated distribution of work to improve efficiency and effectiveness of social media engagement
Tagging
• Allows work to be routed to the appropriate team by grouping each post or social contact into different categories; for example, a post can be marked with the “customer_support” tag; this post will then appear on a customer support agent’s queue for processing
Social media customer care metrics
• Provides detailed metrics on social media customer care activities, campaign reports, and team reports
• Measures work and results
• Manages to service-level goals
• Supports brand management
• Optimizes staffing
• Includes dashboarding of social media posting activity when Cisco Unified Intelligence Center is used
Reporting for social contacts
• Provides a reporting database that can be accessed using any reporting tool, including Cisco Unified Intelligence Center
• Enables customer care management to accurately report on and track social media interactions by the contact center
OpenSocial-compliant gadgets
Representational State Transfer (REST) application programming interfaces (APIs)
• Provides flexible user interface options
• Enables extensive opportunities for customization
Optional integration with full suite of Cisco Collaboration tools
• Allows you to take advantage of the full suite of Cisco Collaboration tools, including Cisco Quad, Cisco Show and Share, and Cisco Pulse technology, to help your social media customer care team quickly find answers to help customers efficiently and effectively
• Requires a Cisco UCS C-Series or B-Series Server.
• Server consolidation means lower cost per server with Cisco UCS Servers.
Architecture
Scalability
• One server supports up to 30 simultaneous social media customer care users and 10,000 social contacts per hour.
Management
Cisco Unified Real-Time Monitoring Tool (RTMT)
• Operational management is enhanced through integration with the Cisco Unified RTMT, providing consistent application monitoring across Cisco Unified Communications Solutions.
Simple Network Management Protocol (SNMP)
• SNMP with an associated MIB is supported through the Cisco Voice Operating System (VOS).
Reporting
Cisco Unified Intelligence Center
• Create customizable reports of social media customer care events using Cisco Unified Intelligence Center (purchased separately).
DECISION STATS 