Tag: cloud computing

Statistical Theory for High Performance Analytics

A thing that strikes me when I was a student of statistics is that most theories of sampling, testing of hypothesis and modeling were built in an age where data was predominantly insufficient, computation was inherently manual and results of tests aimed at large enough differences.

I look now at the explosion of data, at the cloud computing enabled processing power on demand, and competitive dynamics of businesses to venture out my opinion-

1) We now have large , even excess data than we had before for statisticians a generation ago.

2) We now have extremely powerful computing devices, provided we can process our algorithms in parallel.

3) Even a slight uptick in modeling efficiency or mild uptick in business insight can provide huge monetary savings.

Call it High Performance Analytics or Big Data or Cloud Computing- are we sure statisticians are creating enough mathematical theory or are we just taking it easy in our statistics classrooms only to be subjected to something completely different when we hit the analytics workplace.

Do we  need more theorists as well? Is there ANY incentive for corporations with private R and D research teams to share their latest cutting edge theoretical work outside their corporate silo.

 

Related-

“a mathematician is a machine for turning coffee into theorems”

Amazon gives away 750 hours /month of Windows based computing

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

But it is only for new users.

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

WS Free Usage Tier now Includes Microsoft Windows on EC2

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

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

You can launch your instance from the AWS Management Console:

We have lots of helpful resources to get you started:

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

 

Jim Kobielus on 2012

Jim Kobielus revisits the predictions he made in 2011 (and a summary of 2010) , and makes some fresh ones for 2012. For technology watchers, this is an article by one of the gurus of enterprise software.

 

All of those trends predictions (at http://www.decisionstats.com/brief-interview-with-james-g-kobielus/ ) came true in 2011, and are in full force in 2012 as well.Here are my predictions for 2012, and the links to the 3 blogposts in which I made them last month:

 

The Year Ahead in Next Best Action? Here’s the Next Best Thing to a Crystal Ball!

  • The next-best-action market will continue to coalesce around core solution capabilities.
  • Data scientists will become the principal application developers for next best action.
  • Real-world experiments will become the new development paradigm in next best action.

The Year Ahead in Advanced Analytics? Advances on All Fronts!

  • Open-source platforms will expand their footprint in advanced analytics.
  • Data science centers of excellence will spring up everywhere.
  • Predictive analytics and interactive exploration will enter the mainstream BI user experience:

The Year Ahead In Big Data? Big, Cool, New Stuff Looms Large!

  • Enterprise Hadoop deployments will expand at a rapid clip.
  • In-memory analytics platforms will grow their footprint.
  • Graph databases will come into vogue.

 

And in an exclusive and generous favor for DecisionStats, Jim does some crystal gazing for the cloud computing field in 2012-

Cloud/SaaS EDWs will cross the enterprise-adoption inflection point. In 2012, cloud and software-as-a-service (SaaS) enterprise data warehouses (EDWs), offered on a public subscription basis, will gain greater enterprise adoption as a complement or outright replacement for appliance- and software-based EDWs. A growing number of established and startup EDW vendors will roll out cloud/SaaS “Big Data” offerings. Many of these will supplement and extend RDBMS and columnar technologies with Hadoop, key-value, graph, document, and other new database architectures.

About-

http://www.forrester.com/rb/analyst/james_kobielus

James G. Kobielus James G. Kobielus
Senior Analyst

RESEARCH FOCUS

 

James serves Business Process & Application Development & Delivery Professionals. He is a leading expert on data warehousing, predictive analytics, data mining, and complex event processing. In addition to his core coverage areas, James contributes to Forrester’s research in business intelligence, data integration, data quality, and master data management.

 

PREVIOUS WORK EXPERIENCE

 

James has a long history in IT research and consulting and has worked for both vendors and research firms. Most recently, he was at Current Analysis, an IT research firm, where he was a principal analyst covering topics ranging from data warehousing to data integration and the Semantic Web. Prior to that position, James was a senior technical systems analyst at Exostar (a hosted supply chain management and eBusiness hub for the aerospace and defense industry). In this capacity, James was responsible for identifying and specifying product/service requirements for federated identity, PKI, and other products. He also worked as an analyst for the Burton Group and was previously employed by LCC International, DynCorp, ADEENA, International Center for Information Technologies, and the North American Telecommunications Association. He is both well versed and experienced in product and market assessments. James is a widely published business/technology author and has spoken at many industry events.

Contact –

Twitter: http://twitter.com/jameskobielus

Opera Unite- the future of cloud computing browsers

The boys (and ladies) at opera have been busy writing code , while the rest of the coders on the cloud were issuing press releases, attending meetings or just sky diving from the cloud. Judging by the language of apps and extensions, it seems that the  engineers de Vikings et Slavs were busy coding while the Anglo Saxons were busy preparing for IPOs.

I really like the complete anonymity offered by Opera and especially Opera Unite

1) The Adblock option blocks all ads (same as other extensions)

2) The lovely Opera Unite has incredible apps for peer to peer sharing. You can create your own spotify, host your own chat application, transfer files, remote manage your computer. C’est magnifique!

Some really awesome apps on Opera Unite

All these apps can make your own desktop into a remotely managed website- so SOPA is irrelevant even if passed without any protest or non violent protests

(SOPA- an acronym for STOP OBAMA or STOP A (?) , since OBAMA is the one the internet really supports , and he is dependent on that goodwill for fundraising or A is the acronym of a legendary media myth of an imaginary web based organization (imaginary as in iota)

QUOTE–

I think it would be a good idea.

 Mahatma Gandhi, when asked what he thought of Western civilization

Some Ways Anonymous Could Disrupt the Internet if SOPA is passed

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

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

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

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

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

 

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

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

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

or maybe embed bit torrents within a browser.

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

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

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

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

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

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

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

 

2011 Analytics Recap

Events in the field of data that impacted us in 2011

1) Oracle unveiled plans for R Enterprise. This is one of the strongest statements of its focus on in-database analytics. Oracle also unveiled plans for a Public Cloud

2) SAS Institute released version 9.3 , a major analytics software in industry use.

3) IBM acquired many companies in analytics and high tech. Again.However the expected benefits from Cognos-SPSS integration are yet to show a spectacular change in market share.

2011 Selected acquisitions

Emptoris Inc. December 2011

Cúram Software Ltd. December 2011

DemandTec December 2011

Platform Computing October 2011

 Q1 Labs October 2011

Algorithmics September 2011

 i2 August 2011

Tririga March 2011

 

4) SAP promised a lot with SAP HANA- again no major oohs and ahs in terms of market share fluctuations within analytics.

http://www.sap.com/india/news-reader/index.epx?articleID=17619

5) Amazon continued to lower prices of cloud computing and offer more options.

http://aws.amazon.com/about-aws/whats-new/2011/12/21/amazon-elastic-mapreduce-announces-support-for-cc2-8xlarge-instances/

6) Google continues to dilly -dally with its analytics and cloud based APIs. I do not expect all the APIs in the Google APIs suit to survive and be viable in the enterprise software space.  This includes Google Cloud Storage, Cloud SQL, Prediction API at https://code.google.com/apis/console/b/0/ Some of the location based , translation based APIs may have interesting spin offs that may be very very commercially lucrative.

7) Microsoft -did- hmm- I forgot. Except for its investment in Revolution Analytics round 1 many seasons ago- very little excitement has come from MS plans in data mining- The plugins for cloud based data mining from Excel remain promising yet , while Azure remains a stealth mode starter.

8) Revolution Analytics promised us a GUI and didnt deliver (till yet 🙂 ) . But it did reveal a much better Enterprise software Revolution R 5.0 is one of the strongest enterprise software in the R /Stat Computing space and R’s memory handling problem is now an issue of perception than actual stuff thanks to newer advances in how it is used.

9) More conferences, more books and more news on analytics startups in 2011. Big Data analytics remained a strong buzzword. Expect more from this space including creative uses of Hadoop based infrastructure.

10) Data privacy issues continue to hamper and impede effective analytics usage. So does rational and balanced regulation in some of the most advanced economies. We expect more regulation and better guidelines in 2012.

Interview Zach Goldberg, Google Prediction API

Here is an interview with Zach Goldberg, who is the product manager of Google Prediction API, the next generation machine learning analytics-as-an-api service state of the art cloud computing model building browser app.
Ajay- Describe your journey in science and technology from high school to your current job at Google.

Zach- First, thanks so much for the opportunity to do this interview Ajay!  My personal journey started in college where I worked at a startup named Invite Media.   From there I transferred to the Associate Product Manager (APM) program at Google.  The APM program is a two year rotational program.  I did my first year working in display advertising.  After that I rotated to work on the Prediction API.

Ajay- How does the Google Prediction API help an average business analytics customer who is already using enterprise software , servers to generate his business forecasts. How does Google Prediction API fit in or complement other APIs in the Google API suite.

Zach- The Google Prediction API is a cloud based machine learning API.  We offer the ability for anybody to sign up and within a few minutes have their data uploaded to the cloud, a model built and an API to make predictions from anywhere. Traditionally the task of implementing predictive analytics inside an application required a fair amount of domain knowledge; you had to know a fair bit about machine learning to make it work.  With the Google Prediction API you only need to know how to use an online REST API to get started.

You can learn more about how we help businesses by watching our video and going to our project website.

Ajay-  What are the additional use cases of Google Prediction API that you think traditional enterprise software in business analytics ignore, or are not so strong on.  What use cases would you suggest NOT using Google Prediction API for an enterprise.

Zach- We are living in a world that is changing rapidly thanks to technology.  Storing, accessing, and managing information is much easier and more affordable than it was even a few years ago.  That creates exciting opportunities for companies, and we hope the Prediction API will help them derive value from their data.

The Prediction API focuses on providing predictive solutions to two types of problems: regression and classification. Businesses facing problems where there is sufficient data to describe an underlying pattern in either of these two areas can expect to derive value from using the Prediction API.

Ajay- What are your separate incentives to teach about Google APIs  to academic or researchers in universities globally.

Zach- I’d refer you to our university relations page–

Google thrives on academic curiosity. While we do significant in-house research and engineering, we also maintain strong relations with leading academic institutions world-wide pursuing research in areas of common interest. As part of our mission to build the most advanced and usable methods for information access, we support university research, technological innovation and the teaching and learning experience through a variety of programs.

Ajay- What is the biggest challenge you face while communicating about Google Prediction API to traditional users of enterprise software.

Zach- Businesses often expect that implementing predictive analytics is going to be very expensive and require a lot of resources.  Many have already begun investing heavily in this area.  Quite often we’re faced with surprise, and even skepticism, when they see the simplicity of the Google Prediction API.  We work really hard to provide a very powerful solution and take care of the complexity of building high quality models behind the scenes so businesses can focus more on building their business and less on machine learning.