Here is the brand new release from Jaspersoft at a groovy price of 9000$. Somebody stop these guys!
It’s a great company to watch for buyouts as well- given their expertise in REPORTING and clientele- especially for anyone looking to im prove thier standing in both open source world and reporting software branding.
Webinar: Introducing JasperReports Server Professional
Thursday October 14
In this live webinar, learn how a new solution from Jaspersoft combines the world’s favorite reporting server with powerful, mature report server functionality—for about 80% less.
The World’s Most Powerful and Affordable Reporting Server
Limited Time Introductory Offer: Starting from $9,000 (restrictions apply)
JasperReports Server is the recommended product for organizations requiring an affordable reporting solution for interactive, operational, and production-based reporting. Deployed as a standalone reporting server or integrated inside another application, JasperReports Server is a flexible, powerful, interactive reporting environment for small or large enterprises.
Powered by the world’s most popular reporting tools in JasperReports and iReport, developers and users can take advantage of more interactivity, security, and scheduling of their reports.
Key Benefits:
Affordable: Unlimited reports for unlimited users starting at $9,000
Powerful: Report scheduling and distribution to 1,000s of users on a single server
Flexible: Web service architecture simplifies application integration
If you are an analytics blogger who writes, and is aggregated on an analytical community- read on- Here’s how blog aggregation communities can help you lose 30% of all future traffic long term, while giving you a short term.
The problem is not created by Blogging Communities (like R-Bloggers, or PlanteR, or Smart Data Collective or AnalyticBridge or even BeyeBlogs )
It is created by the way Google Page Rank is structured- you see given exactly the same content on two different we pages- Google Page Rank will place the higher Page Rank results higher. This is counter intutive and quite simple to rectify- The Google Spider can just use the Time Stamp for choosing which article was published where first (Obviously on your blog, AND then later to the aggregator).
How bad is the mess? Well joining ANY blog aggregation will lead to an instant lift of upto 10-50 % of your current traffic as similar bloggers try and read about you. However you can lose the long term 30% proportion which is a benchmark of search engine created traffic for you.
So do you opt out of blog aggregation? No. It’s a SEO mess and it’s unfair to punish your blog aggregator, most of whom are running on ad-supported sponsors or their own funds on dry fumes to publish your content. Most of the fore mentioned communities are created by excellent people I interacted with heavily- and they are genuinely motivated to give readers an easy way to keep up with blogs. Especially Smart Data Collective, Analyticbridge and R-bloggers whose founders I have known personally.
You can do one thing- create manual summaries in the excerpt feature of your blog posts- it’s just below the WordPress page. And switch your RSS feed to summary rather than full. It avoids losing keyword rank to other websites, it prevents the Blog Aggregation from gaining too much influence in key word related searches, and it keeps your whole eco system happy, Best of All it helps readers of Blog Aggregators- since most of them use a summary on the front page anyways.
An additional thought on Google Page Rank- something I have sulked over but not spoken for a long long time. It ignores the value of reader- If Bill Gates, Steve Jobs, and 500 ceos from Fortune 500 companies read my blog but do not link to it- it will count daily traffic as 500. Probably it will give more weightage to Paris Hilton fans.
A suggestion-humbly- you can use IP Address lookup of visitors to see if traffic is coming from corporate sources or retail sources -Clicky from GetClicky does this. Use it as feedback in Google Analytics as well as Google Trends.
And maybe PageRank needs to add quantity and quality of visitors as additional variables . Do a A/B test guys some Chi Square juice- its not quite Mad Men Adverting but its still good fun.
New software just released from the guys in California (@RevolutionR) so if you are a Linux user and have academic credentials you can download it for free (@Cmastication doesnt), you can test it to see what the big fuss is all about (also see http://www.revolutionanalytics.com/why-revolution-r/benchmarks.php) –
Revolution Analytics has just released Revolution R Enterprise 4.0.1 for Red Hat Enterprise Linux, a significant step forward in enterprise data analytics. Revolution R Enterprise 4.0.1 is built on R 2.11.1, the latest release of the open-source environment for data analysis and graphics. Also available is the initial release of our deployment server solution, RevoDeployR 1.0, designed to help you deliver R analytics via the Web. And coming soon to Linux: RevoScaleR, a new package for fast and efficient multi-core processing of large data sets.
As a registered user of the Academic version of Revolution R Enterprise for Linux, you can take advantage of these improvements by downloading and installing Revolution R Enterprise 4.0.1 today. You can install Revolution R Enterprise 4.0.1 side-by-side with your existing Revolution R Enterprise installations; there is no need to uninstall previous versions.
Download Information
The following information is all you will need to download and install the Academic Edition.
Supported Platforms:
Revolution R Enterprise Academic edition and RevoDeployR are supported on Red Hat® Enterprise Linux® 5.4 or greater (64-bit processors).
Approximately 300MB free disk space is required for a full install of Revolution R Enterprise. We recommend at least 1GB of RAM to use Revolution R Enterprise.
For the full list of system requirements for RevoDeployR, refer to the RevoDeployR™ Installation Guide for Red Hat® Enterprise Linux®.
Download Links:
You will first need to download the Revolution R Enterprise installer.
Installation Instructions for Revolution R Enterprise Academic Edition
After downloading the installer, do the following to install the software:
Log in as root if you have not already.
Change directory to the directory containing the downloaded installer.
Unpack the installer using the following command:
tar -xzf Revo-Ent-4.0.1-RHEL5-desktop.tar.gz
Change directory to the RevolutionR_4.0.1 directory created.
Run the installer by typing ./install.py and following the on-screen prompts.
Getting Started with the Revolution R Enterprise
After you have installed the software, launch Revolution R Enterprise by typing Revo64 at the shell prompt.
Documentation is available in the form of PDF documents installed as part of the Revolution R Enterprise distribution. Type Revo.home(“doc”) at the R prompt to locate the directory containing the manuals Getting Started with Revolution R (RevoMan.pdf) and the ParallelR User’s Guide(parRman.pdf).
Installation Instructions for RevoDeployR (and RServe)
After downloading the RevoDeployR distribution, use the following steps to install the software:
Note: These instructions are for an automatic install. For more details or for manual install instructions, refer to RevoDeployR_Installation_Instructions_for_RedHat.pdf.
Log into the operating system as root.
su –
Change directory to the directory containing the downloaded distribution for RevoDeployR and RServe.
Unzip the contents of the RevoDeployR tar file. At prompt, type:
tar -xzf deployrRedHat.tar.gz
Change directories. At the prompt, type:
cd installFiles
Launch the automated installation script and follow the on-screen prompts. At the prompt, type:
./installRedHat.sh Note:Red Hat installs MySQL without a password.
Getting Started with RevoDeployR
After installing RevoDeployR, you will be directed to the RevoDeployR landing page. The landing page has links to documentation, the RevoDeployR management console, the API Explorer development tool, and sample code.
The simple R-benchmark-25.R test script is a quick-running survey of general R performance. The Community-developed test consists of three sets of small benchmarks, referred to in the script as Matrix Calculation, Matrix Functions, and Program Control.
Revolution Analytics has created its own tests to simulate common real-world computations. Their descriptions are explained below.
Linear Algebra Computation
Base R 2.9.2
Revolution R (1-core)
Revolution R (4-core)
Speedup (4 core)
Matrix Multiply
243 sec
22 sec
5.9 sec
41x
Cholesky Factorization
23 sec
3.8 sec
1.1 sec
21x
Singular Value Decomposition
62 sec
13 sec
4.9 sec
12.6x
Principal Components Analysis
237 sec
41 sec
15.6 sec
15.2x
Linear Discriminant Analysis
142 sec
49 sec
32.0 sec
4.4x
Speedup = Slower time / Faster Time – 1
Matrix Multiply
This routine creates a random uniform 10,000 x 5,000 matrix A, and then times the computation of the matrix product transpose(A) * A.
set.seed (1)
m <- 10000
n <- 5000
A <- matrix (runif (m*n),m,n)
system.time (B <- crossprod(A))
The system will respond with a message in this format:
User system elapsed
37.22 0.40 9.68
The “elapsed” times indicate total wall-clock time to run the timed code.
The table above reflects the elapsed time for this and the other benchmark tests. The test system was an INTEL® Xeon® 8-core CPU (model X55600) at 2.5 GHz with 18 GB system RAM running Windows Server 2008 operating system. For the Revolution R benchmarks, the computations were limited to 1 core and 4 cores by calling setMKLthreads(1) and setMKLthreads(4) respectively. Note that Revolution R performs very well even in single-threaded tests: this is a result of the optimized algorithms in the Intel MKL library linked to Revolution R. The slight greater than linear speedup may be due to the greater total cache available to all CPU cores, or simply better OS CPU scheduling–no attempt was made to pin execution threads to physical cores. Consult Revolution R’s documentation to learn how to run benchmarks that use less cores than your hardware offers.
Cholesky Factorization
The Cholesky matrix factorization may be used to compute the solution of linear systems of equations with a symmetric positive definite coefficient matrix, to compute correlated sets of pseudo-random numbers, and other tasks. We re-use the matrix B computed in the example above:
system.time (C <- chol(B))
Singular Value Decomposition with Applications
The Singular Value Decomposition (SVD) is a numerically-stable and very useful matrix decompisition. The SVD is often used to compute Principal Components and Linear Discriminant Analysis.
# Singular Value Deomposition
m <- 10000
n <- 2000
A <- matrix (runif (m*n),m,n)
system.time (S <- svd (A,nu=0,nv=0))
# Principal Components Analysis
m <- 10000
n <- 2000
A <- matrix (runif (m*n),m,n)
system.time (P <- prcomp(A))
# Linear Discriminant Analysis require (‘MASS’)
g <- 5
k <- round (m/2)
A <- data.frame (A, fac=sample (LETTERS[1:g],m,replace=TRUE))
train <- sample(1:m, k)
system.time (L <- lda(fac ~., data=A, prior=rep(1,g)/g, subset=train))
LibreOffice is a new fork from OpenOffice– Basically people who want to ensure OpenOffice remains free. It basically consists of efforts from everybody except Apple, Microsoft and Oracle (http://www.documentfoundation.org/supporters/) and it’s a new kind of workable office productivity suite-determined to remain free. I have used it- a bit shaky- but I really liked the new design and willingly will test it (and auto submit bugs) . It would be interesting to see the reaction of enterprise vendors like SAS, IBM,Dell, HP (and Lenovo) and etc -as their support would be critical to both Unbreakable Oracle Linux and Unshakable LibreOffice.
No, this is not about the X Box kind of games. It is about Microsoft ‘s tactical shift in the online space from going it alone, and building stuff itself, –to partnering, and sometimes investing and exiting business.
In Blogs- It recently announced a migration of MS Live Spaces to WordPress.com – It gives Automattic 30 million more users- no small change consider there were 26 million existing WP users.
Microsoft Messenger, which is the oldest online app in the suite, now provides instant messaging services to about 350 million users, and from now on Windows Live Writer works specifically with the WordPress.com blog service by default. Hopefully Skype, and Google Voice will show MS the way to monitize that business app yet.
Google buying blogger-blogspot seems to have done little, but given Biz Stone room to create another content disruption-Twitter.
With the round of lawsuits by proxy, in Android -Motorola, or for acquisitions – MS is just doing what Marc Anderseen (who’s apparently a better VC than Paul Allen was), Sun and co did to it in the nineties.
Google seems to be regretting putting a spade in the Yahoo acquisition- that would have tied up a big chunk of Idle MS cash- leaving it little room for niche investments (like the 250 mill that helped Facebook ramp up in time).
The real surprise here could be Apple- it has shown little interest in cloud computing- and it seems to be testing the waters with Ping. But Apple sure smells competition- and Android is doing to Iphone what Windows did to the Mac in the early 1990’s.
Google lacks presence in online gaming (despite it’s own Zynga investment)- and needs to start monetizing properties like Android OS (say 10$ for every phone license ??), Google Maps (as an app for GPS) and Google Voice. Indeed it may be time for the big G to start thinking of spinning off atleast some products- earning better returns, while retaining control (dual stock splits) and killing those anti trust lawyer fees forever.
As the Ancient Chinese said, May you live in interesting times. Fun to watch the online games people play.
Just go to Users-Personal Settings- and check the options shown. Thats it every time you write a post it suggests links and tags. Links are helpful for your readers (like Wikipedia links to understand dense technical jargon, or associated websites). Tags help to classify your contents so that all visitors to the web site including spiders ,search engines and your readers can search it better.
The bad thing is I need to go back to all 1025 posts on this site and auto generate tags for the archives ! Oh well. Great collaboration between zementa and Automattic for this new feature.
Google Instant is a relatively newer feature in Google Search Engine- it suggests websites at each type of keyword rather than wait for you to type the whole keyword.
The impact on user experience is incredible- rather than search or scroll through the results- you are more likely to click on the almost one of the ten websites you would have seen by the time you finished typing- or just clicking on the relevant ad (which probably changes on the right margin as fast as the websites below)
This spells a death for all those who indulged in black hat SEO– or link building, link exchanging- as these techniques pushed up your rank in search page only incrementally and rarely to the top 2-3 for a keyword.
Remember the size of the screen is such that each Google instant snapshot basically shows you or rather makes you focus on the top ranked search (and then presumably type on to get a newer result- rather than scroll down as the case was before).
It would be interesting to see or research the effect of keywords in the auction pricing, as well as compare those keyword pricing with Bing.com- Maybe there should be a website api tool for advertisers -like Adwords Instant that would show them the price instantly of keywords,comparison with Bing AND the search engine results for the keyword in a visual way.
Anyways- it is a incredible innovation and it is good Google is back to the math after the flings with being “Mad Men” of advertising.
and yes- I heard there is a new movie coming- it is called “The Search Engine” 🙂
DECISION STATS 