Some ways to test and use cloud computing for free for yourself-
- Windows Azure
- Amazon Ec2
- Google Storage
The folks at Microsoft Azure announced a 90 day free trial Continue reading “Cloud Computing by Windows , Amazon and Google for free”
Tag: Database
Interview Mike Boyarski Jaspersoft
Here is an interview with Mike Boyarski , Director Product Marketing at Jaspersoft
.
the largest BI community with over 14 million downloads, nearly 230,000 registered members, representing over 175,000 production deployments, 14,000 customers, across 100 countries.
Ajay- Describe your career in science from Biology to marketing great software.
Mike- I studied Biology with the assumption I’d pursue a career in medicine. It took about 2 weeks during an internship at a Los Angeles hospital to determine I should do something else. I enjoyed learning about life science, but the whole health care environment was not for me. I was initially introduced to enterprise-level software while at Applied Materials within their Microcontamination group. I was able to assist with an internal application used to collect contamination data. I later joined Oracle to work on an Oracle Forms application used to automate the production of software kits (back when documentation and CDs had to be physically shipped to recognize revenue). This gave me hands on experience with Oracle 7, web application servers, and the software development process.
I then transitioned to product management for various products including application servers, software appliances, and Oracle’s first generation SaaS based software infrastructure. In 2006, with the Siebel and PeopleSoft acquisitions underway, I moved on to Ingres to help re-invigorate their solid yet antiquated technology. This introduced me to commercial open source software and the broader Business Intelligence market. From Ingres I joined Jaspersoft, one of the first and most popular open source Business Intelligence vendors, serving as head of product marketing since mid 2009.
Ajay- Describe some of the new features in Jaspersoft 4.1 that help differentiate it from the rest of the crowd. What are the exciting product features we can expect from Jaspersoft down the next couple of years.
Mike- Jaspersoft 4.1 was an exciting release for our customers because we were able to extend the latest UI advancements in our ad hoc report designer to the data analysis environment. Now customers can use a unified intuitive web-based interface to perform several powerful and interactive analytic functions across any data source, whether its relational, non-relational, or a Big Data source.
The reality is that most (roughly 70%) of todays BI adoption is in the form of reports and dashboards. These tools are used to drive and measure an organizations business, however, data analysis presents the most strategic opportunity for companies because it can identify new opportunities, efficiencies, and competitive differentiation. As more data comes online, the difference between those companies that are successful and those that are not will likely be attributed to their ability to harness data analysis techniques to drive and improve business performance. Thus, with Jaspersoft 4.1, and our improved ad hoc reporting and analysis UI we can effectively address a broader set of BI requirements for organizations of all sizes.
Ajay- What do you think is a good metric to measure influence of an open source software product – is it revenue or is it number of downloads or number of users. How does Jaspersoft do by these counts.
Mike- History has shown that open source software is successful as a “bottoms up” disrupter within IT or the developer market. Today, many new software projects and startup ventures are birthed on open source software, often initiated with little to no budget. As the organization achieves success with a particular project, the next initiative tends to be larger and more strategic, often displacing what was historically solved with a proprietary solution. These larger deployments strengthen the technology over time.
Thus, the more proven and battle tested an open source solution is, often measured via downloads, deployments, community size, and community activity, usually equates to its long term success. Linux, Tomcat, and MySQL have plenty of statistics to model this lifecycle. This model is no different for open source BI.
The success to date of Jaspersoft is directly tied to its solid proven technology and the vibrancy of the community. We proudly and openly claim to have the largest BI community with over 14 million downloads, nearly 230,000 registered members, representing over 175,000 production deployments, 14,000 customers, across 100 countries. Every day, 30,000 developers are using Jaspersoft to build BI applications. Behind Excel, its hard to imagine a more widely used BI tool in the market. Jaspersoft could not reach these kind of numbers with crippled or poorly architected software.
Ajay- What are your plans for leveraging cloud computing, mobile and tablet platforms and for making Jaspersoft more easy and global to use.
Mike-The cloud Continue reading “Interview Mike Boyarski Jaspersoft”
Analytics 2011 Conference
From http://www.sas.com/events/analytics/us/
The Analytics 2011 Conference Series combines the power of SAS’s M2010 Data Mining Conference and F2010 Business Forecasting Conference into one conference covering the latest trends and techniques in the field of analytics. Analytics 2011 Conference Series brings the brightest minds in the field of analytics together with hundreds of analytics practitioners. Join us as these leading conferences change names and locations. At Analytics 2011, you’ll learn through a series of case studies, technical presentations and hands-on training. If you are in the field of analytics, this is one conference you can’t afford to miss.
Conference Details
October 24-25, 2011
Grande Lakes Resort
Orlando, FL
Analytics 2011 topic areas include:
- Data Mining
- Forecasting
- Text Analytics
- Fraud Detection
- Data Visualization Continue reading “Analytics 2011 Conference”
Amazon Ec2 goes Red Hat
message from Amazing Amazon’s cloud team- this will also help for #rstats users given that revolution Analytics full versions on RHEL.
—————————————————-
on-demand instances of Amazon EC2 running Red Hat Enterprise Linux (RHEL) for as little as $0.145 per instance hour. The offering combines the cost-effectiveness, scalability and flexibility of running in Amazon EC2 with the proven reliability of Red Hat Enterprise Linux.
Highlights of the offering include:
- Support is included through subscription to AWS Premium Support with back-line support by Red Hat
- Ongoing maintenance, including security patches and bug fixes, via update repositories available in all Amazon EC2 regions
- Amazon EC2 running RHEL currently supports RHEL 5.5, RHEL 5.6, RHEL 6.0 and RHEL 6.1 in both 32 bit and 64 bit formats, and is available in all Regions.
- Customers who already own Red Hat licenses will continue to be able to use those licenses at no additional charge.
- Like all services offered by AWS, Amazon EC2 running Red Hat Enterprise Linux offers a low-cost, pay-as-you-go model with no long-term commitments and no minimum fees.
For more information, please visit the Amazon EC2 Red Hat Enterprise Linux page.
which is
Amazon EC2 Running Red Hat Enterprise Linux
Amazon EC2 running Red Hat Enterprise Linux provides a dependable platform to deploy a broad range of applications. By running RHEL on EC2, you can leverage the cost effectiveness, scalability and flexibility of Amazon EC2, the proven reliability of Red Hat Enterprise Linux, and AWS premium support with back-line support from Red Hat.. Red Hat Enterprise Linux on EC2 is available in versions 5.5, 5.6, 6.0, and 6.1, both in 32-bit and 64-bit architectures.
Amazon EC2 running Red Hat Enterprise Linux provides seamless integration with existing Amazon EC2 features including Amazon Elastic Block Store (EBS), Amazon CloudWatch, Elastic-Load Balancing, and Elastic IPs. Red Hat Enterprise Linux instances are available in multiple Availability Zones in all Regions.
Pricing
Pay only for what you use with no long-term commitments and no minimum fee.
On-Demand Instances
On-Demand Instances let you pay for compute capacity by the hour with no long-term commitments.
Region:US – N. VirginiaUS – N. CaliforniaEU – IrelandAPAC – SingaporeAPAC – Tokyo
| Standard Instances | Red Hat Enterprise Linux |
|---|---|
| Small (Default) | $0.145 per hour |
| Large | $0.40 per hour |
| Extra Large | $0.74 per hour |
| Micro Instances | Red Hat Enterprise Linux |
| Micro | $0.08 per hour |
| High-Memory Instances | Red Hat Enterprise Linux |
| Extra Large | $0.56 per hour |
| Double Extra Large | $1.06 per hour |
| Quadruple Extra Large | $2.10 per hour |
| High-CPU Instances | Red Hat Enterprise Linux |
| Medium | $0.23 per hour |
| Extra Large | $0.78 per hour |
| Cluster Compute Instances | Red Hat Enterprise Linux |
| Quadruple Extra Large | $1.70 per hour |
| Cluster GPU Instances | Red Hat Enterprise Linux |
| Quadruple Extra Large | $2.20 per hour |
Pricing is per instance-hour consumed for each instance type. Partial instance-hours consumed are billed as full hours.
and
Available Instance Types
Standard Instances
Instances of this family are well suited for most applications.
Small Instance – default*
1.7 GB memory
1 EC2 Compute Unit (1 virtual core with 1 EC2 Compute Unit)
160 GB instance storage
32-bit platform
I/O Performance: Moderate
API name: m1.small
Large Instance
7.5 GB memory
4 EC2 Compute Units (2 virtual cores with 2 EC2 Compute Units each)
850 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.large
Extra Large Instance
15 GB memory
8 EC2 Compute Units (4 virtual cores with 2 EC2 Compute Units each)
1,690 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.xlarge
Micro Instances
Instances of this family provide a small amount of consistent CPU resources and allow you to burst CPU capacity when additional cycles are available. They are well suited for lower throughput applications and web sites that consume significant compute cycles periodically.
Micro Instance
613 MB memory
Up to 2 EC2 Compute Units (for short periodic bursts)
EBS storage only
32-bit or 64-bit platform
I/O Performance: Low
API name: t1.micro
High-Memory Instances
Instances of this family offer large memory sizes for high throughput applications, including database and memory caching applications.
High-Memory Extra Large Instance
17.1 GB of memory
6.5 EC2 Compute Units (2 virtual cores with 3.25 EC2 Compute Units each)
420 GB of instance storage
64-bit platform
I/O Performance: Moderate
API name: m2.xlarge
High-Memory Double Extra Large Instance
34.2 GB of memory
13 EC2 Compute Units (4 virtual cores with 3.25 EC2 Compute Units each)
850 GB of instance storage
64-bit platform
I/O Performance: High
API name: m2.2xlarge
High-Memory Quadruple Extra Large Instance
68.4 GB of memory
26 EC2 Compute Units (8 virtual cores with 3.25 EC2 Compute Units each)
1690 GB of instance storage
64-bit platform
I/O Performance: High
API name: m2.4xlarge
High-CPU Instances
Instances of this family have proportionally more CPU resources than memory (RAM) and are well suited for compute-intensive applications.
High-CPU Medium Instance
1.7 GB of memory
5 EC2 Compute Units (2 virtual cores with 2.5 EC2 Compute Units each)
350 GB of instance storage
32-bit platform
I/O Performance: Moderate
API name: c1.medium
High-CPU Extra Large Instance
7 GB of memory
20 EC2 Compute Units (8 virtual cores with 2.5 EC2 Compute Units each)
1690 GB of instance storage
64-bit platform
I/O Performance: High
API name: c1.xlarge
Cluster Compute Instances
Instances of this family provide proportionally high CPU resources with increased network performance and are well suited for High Performance Compute (HPC) applications and other demanding network-bound applications. Learn more about use of this instance type for HPC applications.
Cluster Compute Quadruple Extra Large Instance
23 GB of memory
33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core “Nehalem” architecture)
1690 GB of instance storage
64-bit platform
I/O Performance: Very High (10 Gigabit Ethernet)
API name: cc1.4xlarge
Cluster GPU Instances
Instances of this family provide general-purpose graphics processing units (GPUs) with proportionally high CPU and increased network performance for applications benefitting from highly parallelized processing, including HPC, rendering and media processing applications. While Cluster Compute Instances provide the ability to create clusters of instances connected by a low latency, high throughput network, Cluster GPU Instances provide an additional option for applications that can benefit from the efficiency gains of the parallel computing power of GPUs over what can be achieved with traditional processors. Learn more about use of this instance type for HPC applications.
Cluster GPU Quadruple Extra Large Instance
22 GB of memory
33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core “Nehalem” architecture)
2 x NVIDIA Tesla “Fermi” M2050 GPUs
1690 GB of instance storage
64-bit platform
I/O Performance: Very High (10 Gigabit Ethernet)
API name: cg1.4xlarge
Getting Started
To get started using Red Hat Enterprise Linux on Amazon EC2, perform the following steps:
- Open and log into the AWS Management Console
- Click on Launch Instance from the EC2 Dashboard
- Select the Red Hat Enterprise Linux AMI from the QuickStart tab
- Specify additional details of your instance and click Launch
- Additional details can be found on each AMI’s Catalog Entry page
The AWS Management Console is an easy tool to start and manage your instances. If you are looking for more details on launching an instance, a quick video tutorial on how to use Amazon EC2 with the AWS Management Console can be found here .
A full list of Red Hat Enterprise Linux AMIs can be found in the AWS AMI Catalog.
Support
All customers running Red Hat Enterprise Linux on EC2 will receive access to repository updates from Red Hat. Moreover, AWS Premium support customers can contact AWS to get access to a support structure from both Amazon and Red Hat.
Resources
- Red Hat solution provider page in EC2
- Red Hat Images in the Amazon Machine Image catalog
- Cloud Computing with Red Hat
About Red Hat
Red Hat, the world’s leading open source solutions provider, is headquartered in Raleigh, NC with over 50 satellite offices spanning the globe. Red Hat provides high-quality, low-cost technology with its operating system platform, Red Hat Enterprise Linux, together with applications, management and Services Oriented Architecture (SOA) solutions, including the JBoss Enterprise Middleware Suite. Red Hat also offers support, training and consulting services to its customers worldwide.
also from Revolution Analytics- in case you want to #rstats in the cloud and thus kill all that talk of RAM dependency, slow R than other softwares (just increase the RAM above in the instances to keep it simple)
,or Revolution not being open enough
http://www.revolutionanalytics.com/downloads/gpl-sources.php
GPL SOURCES
Revolution Analytics uses an Open-Core Licensing model. We provide open- source R bundled with proprietary modules from Revolution Analytics that provide additional functionality for our users. Open-source R is distributed under the GNU Public License (version 2), and we make our software available under a commercial license.
Revolution Analytics respects the importance of open source licenses and has contributed code to the open source R project and will continue to do so. We have carefully reviewed our compliance with GPLv2 and have worked with Mark Radcliffe of DLA Piper, the outside General Legal Counsel of the Open Source Initiative, to ensure that we fully comply with the obligations of the GPLv2.
For our Revolution R distribution, we may make some minor modifications to the R sources (the ChangeLog file lists all changes made). You can download these modified sources of open-source R under the terms of the GPLv2, using either the links below or those in the email sent to you when you download a specific version of Revolution R.
Download GPL Sources
| Product | Version | Platform | Modified R Sources |
| Revolution R Community | 3.2 | Windows | R 2.10.1 |
| Revolution R Community | 3.2 | MacOS | R 2.10.1 |
| Revolution R Enterprise | 3.1.1 | RHEL | R 2.9.2 |
| Revolution R Enterprise | 4.0 | Windows | R 2.11.1 |
| Revolution R Enterprise | 4.0.1 | RHEL | R 2.11.1 |
| Revolution R Enterprise | 4.1.0 | Windows | R 2.11.1 |
| Revolution R Enterprise | 4.2 | Windows | R 2.11.1 |
| Revolution R Enterprise | 4.2 | RHEL | R 2.11.1 |
| Revolution R Enterprise | 4.3 | Windows & RHEL | R 2.12.2 |
#Rstats for Business Intelligence
This is a short list of several known as well as lesser known R ( #rstats) language codes, packages and tricks to build a business intelligence application. It will be slightly Messy (and not Messi) but I hope to refine it someday when the cows come home.
It assumes that BI is basically-
a Database, a Document Database, a Report creation/Dashboard pulling software as well unique R packages for business intelligence.
What is business intelligence?
Seamless dissemination of data in the organization. In short let it flow- from raw transactional data to aggregate dashboards, to control and test experiments, to new and legacy data mining models- a business intelligence enabled organization allows information to flow easily AND capture insights and feedback for further action.
BI software has lately meant to be just reporting software- and Business Analytics has meant to be primarily predictive analytics. the terms are interchangeable in my opinion -as BI reports can also be called descriptive aggregated statistics or descriptive analytics, and predictive analytics is useless and incomplete unless you measure the effect in dashboards and summary reports.
Data Mining- is a bit more than predictive analytics- it includes pattern recognizability as well as black box machine learning algorithms. To further aggravate these divides, students mostly learn data mining in computer science, predictive analytics (if at all) in business departments and statistics, and no one teaches metrics , dashboards, reporting in mainstream academia even though a large number of graduates will end up fiddling with spreadsheets or dashboards in real careers.
Using R with
1) Databases-
I created a short list of database connectivity with R here at https://rforanalytics.wordpress.com/odbc-databases-for-r/ but R has released 3 new versions since then.
The RODBC package remains the package of choice for connecting to SQL Databases.
http://cran.r-project.org/web/packages/RODBC/RODBC.pdf
Details on creating DSN and connecting to Databases are given at https://rforanalytics.wordpress.com/odbc-databases-for-r/
For document databases like MongoDB and CouchDB
( what is the difference between traditional RDBMS and NoSQL if you ever need to explain it in a cocktail conversation http://dba.stackexchange.com/questions/5/what-are-the-differences-between-nosql-and-a-traditional-rdbms
Basically dispensing with the relational setup, with primary and foreign keys, and with the additional overhead involved in keeping transactional safety, often gives you extreme increases in performance
NoSQL is a kind of database that doesn’t have a fixed schema like a traditional RDBMS does. With the NoSQL databases the schema is defined by the developer at run time. They don’t write normal SQL statements against the database, but instead use an API to get the data that they need.
instead relating data in one table to another you store things as key value pairs and there is no database schema, it is handled instead in code.)
I believe any corporation with data driven decision making would need to both have atleast one RDBMS and one NoSQL for unstructured data-Ajay. This is a sweeping generic statement 😉 , and is an opinion on future technologies.
- Use RMongo
From- http://tommy.chheng.com/2010/11/03/rmongo-accessing-mongodb-in-r/
- use the C API for MongoDB to fetch some MongoDB data from R.
http://plindenbaum.blogspot.com/2010/09/connecting-to-mongodb-database-from-r.html
Connecting to a MongoDB database from R using Java
http://nsaunders.wordpress.com/2010/09/24/connecting-to-a-mongodb-database-from-r-using-java/
Also see a nice basic analysis using R Mongo from
http://pseudofish.com/blog/2011/05/25/analysis-of-data-with-mongodb-and-r/
For CouchDB
please see https://github.com/wactbprot/R4CouchDB and
http://digitheadslabnotebook.blogspot.com/2010/10/couchdb-and-r.html
2) External Report Creating Software-
Jaspersoft- It has good integration with R and is a certified Revolution Analytics partner (who seem to be the only ones with a coherent #Rstats go to market strategy- which begs the question – why is the freest and finest stats software having only ONE vendor- if it was so great lots of companies would make exclusive products for it – (and some do -see https://rforanalytics.wordpress.com/r-business-solutions/ and https://rforanalytics.wordpress.com/using-r-from-other-software/)
From
http://www.jaspersoft.com/sites/default/files/downloads/events/Analytics%20-Jaspersoft-SEP2010.pdf
we see
http://jasperforge.org/projects/rrevodeployrbyrevolutionanalytics
RevoConnectR for JasperReports Server
RevoConnectR for JasperReports Server RevoConnectR for JasperReports Server is a Java library interface between JasperReports Server and Revolution R Enterprise’s RevoDeployR, a standardized collection of web services that integrates security, APIs, scripts and libraries for R into a single server. JasperReports Server dashboards can retrieve R charts and result sets from RevoDeployR.
http://jasperforge.org/plugins/esp_frs/optional_download.php?group_id=409
Using R and Pentaho
Extending Pentaho with R analytics”R” is a popular open source statistical and analytical language that academics and commercial organizations alike have used for years to get maximum insight out of information using advanced analytic techniques. In this twelve-minute video, David Reinke from Pentaho Certified Partner OpenBI provides an overview of R, as well as a demonstration of integration between R and Pentaho.
and from
R and BI – Integrating R with Open Source Business Intelligence Platforms Pentaho and Jaspersoft David Reinke, Steve Miller Keywords: business intelligence Increasingly, R is becoming the tool of choice for statistical analysis, optimization, machine learning and visualization in the business world. This trend will only escalate as more R analysts transition to business from academia. But whereas in academia R is often the central tool for analytics, in business R must coexist with and enhance mainstream business intelligence (BI) technologies. A modern BI portfolio already includes relational databeses, data integration (extract, transform, load – ETL), query and reporting, online analytical processing (OLAP), dashboards, and advanced visualization. The opportunity to extend traditional BI with R analytics revolves on the introduction of advanced statistical modeling and visualizations native to R. The challenge is to seamlessly integrate R capabilities within the existing BI space. This presentation will explain and demo an initial approach to integrating R with two comprehensive open source BI (OSBI) platforms – Pentaho and Jaspersoft. Our efforts will be successful if we stimulate additional progress, transparency and innovation by combining the R and BI worlds. The demonstration will show how we integrated the OSBI platforms with R through use of RServe and its Java API. The BI platforms provide an end user web application which include application security, data provisioning and BI functionality. Our integration will demonstrate a process by which BI components can be created that prompt the user for parameters, acquire data from a relational database and pass into RServer, invoke R commands for processing, and display the resulting R generated statistics and/or graphs within the BI platform. Discussion will include concepts related to creating a reusable java class library of commonly used processes to speed additional development.
If you know Java- try http://ramanareddyg.blog.com/2010/07/03/integrating-r-and-pentaho-data-integration/
and I like this list by two venerable powerhouses of the BI Open Source Movement
http://www.openbi.com/demosarticles.html
Open Source BI as disruptive technology
http://www.openbi.biz/articles/osbi_disruption_openbi.pdf
Open Source Punditry
| TITLE | AUTHOR | COMMENTS |
|---|---|---|
| Commercial Open Source BI Redux | Dave Reinke & Steve Miller | An review and update on the predictions made in our 2007 article focused on the current state of the commercial open source BI market. Also included is a brief analysis of potential options for commercial open source business models and our take on their applicability. |
| Open Source BI as Disruptive Technology | Dave Reinke & Steve Miller | Reprint of May 2007 DM Review article explaining how and why Commercial Open Source BI (COSBI) will disrupt the traditional proprietary market. |
Spotlight on R
| TITLE | AUTHOR | COMMENTS |
|---|---|---|
| R You Ready for Open Source Statistics? | Steve Miller | R has become the “lingua franca” for academic statistical analysis and modeling, and is now rapidly gaining exposure in the commercial world. Steve examines the R technology and community and its relevancy to mainstream BI. |
| R and BI (Part 1): Data Analysis with R | Steve Miller | An introduction to R and its myriad statistical graphing techniques. |
| R and BI (Part 2): A Statistical Look at Detail Data | Steve Miller | The usage of R’s graphical building blocks – dotplots, stripplots and xyplots – to create dashboards which require little ink yet tell a big story. |
| R and BI (Part 3): The Grooming of Box and Whiskers | Steve Miller | Boxplots and variants (e.g. Violin Plot) are explored as an essential graphical technique to summarize data distributions by categories and dimensions of other attributes. |
| R and BI (Part 4): Embellishing Graphs | Steve Miller | Lattices and logarithmic data transformations are used to illuminate data density and distribution and find patterns otherwise missed using classic charting techniques. |
| R and BI (Part 5): Predictive Modelling | Steve Miller | An introduction to basic predictive modelling terminology and techniques with graphical examples created using R. |
| R and BI (Part 6) : Re-expressing Data |
Steve Miller | How do you deal with highly skewed data distributions? Standard charting techniques on this “deviant” data often fail to illuminate relationships. This article explains techniques to re-express skewed data so that it is more understandable. |
| The Stock Market, 2007 | Steve Miller | R-based dashboards are presented to demonstrate the return performance of various asset classes during 2007. |
| Bootstrapping for Portfolio Returns: The Practice of Statistical Analysis | Steve Miller | Steve uses the R open source stats package and Monte Carlo simulations to examine alternative investment portfolio returns…a good example of applied statistics using R. |
| Statistical Graphs for Portfolio Returns | Steve Miller | Steve uses the R open source stats package to analyze market returns by asset class with some very provocative embedded trellis charts. |
| Frank Harrell, Iowa State and useR!2007 | Steve Miller | In August, Steve attended the 2007 Internation R User conference (useR!2007). This article details his experiences, including his meeting with long-time R community expert, Frank Harrell. |
| An Open Source Statistical “Dashboard” for Investment Performance | Steve Miller | The newly launched Dashboard Insight web site is focused on the most useful of BI tools: dashboards. With this article discussing the use of R and trellis graphics, OpenBI brings the realm of open source to this forum. |
| Unsexy Graphics for Business Intelligence | Steve Miller | Utilizing Tufte’s philosophy of maximizing the data to ink ratio of graphics, Steve demonstrates the value in dot plot diagramming. The R open source statistical/analytics software is showcased. |
I think that the report generation package Brew would also qualify as a BI package, but large scale implementation remains to be seen in
a commercial business environment
- brew: Creating Repetitive Reports
brew: Templating Framework for Report Generation brew implements a templating framework for mixing text and R code for report generation. brew template syntax is similar to PHP, Ruby's erb module, Java Server Pages, and Python's psp module. http://bit.ly/jINmaI
- Yarr- creating reports in R
- the formidable Dirk with awesome stock reports
http://dirk.eddelbuettel.com/blog/2011/01/16/#overbought_oversold_plot
to be continued ( when I have more time and the temperature goes down from 110F in Delhi, India)
Related articles
- Jaspersoft 4.1 launched (decisionstats.com)
- rstat.us – a rival to Twitter? (i-programmer.info)
Protected: Happy Labour Day to American Stats-ical Association
High Performance Analytics
Marry Big Data Analytics to High Performance Computing, and you get the buzzword of this season- High Performance Analytics.
It basically consists of Parallelized code to run in parallel on custom hardware, in -database analytics for speed, and cloud computing /high performance computing environments. On an operational level, it consists of software (as in analytics) partnering with software (as in databases, Map reduce, Hadoop) plus some hardware (HP or IBM mostly). It is considered a high margin , highly profitable, business with small number of deals compared to say desktop licenses.
As per HPC Wire- which is a great tool/newsletter to keep updated on HPC , SAS Institute has been busy on this front partnering with EMC Greenplum and TeraData (who also acquired SAS Partner AsterData to gain a much needed foot in the MR/SQL space) Continue reading “High Performance Analytics”
DECISION STATS 
