Using Red R- R with a Visual Interface

For people complaining about the GUI on R, here is the ah Enterprise Version of R called Red R.

It is available at the website at http://www.red-r.org/

 

You can read more there or just go through the short video created by them at

Basically it is a click and point method of using R with the ability to store schemas and thus very good for repeatable operations as well.


Not bad for epic software, huh?

Aster Analytics and MapReduce.org

From the Press Release,

Aster Data Announces New Analytics Center and Launches http://www.mapreduce.org to Ease and Accelerate Adoption of MapReduce-Based Analytics

All-Star Team of Analytics Experts and MapReduce.org to Help Companies Build Next Generation Analytic Applications Using SQL-MapReduce and MapReduce Breakthroughs

Las Vegas, NV – April 12, 2010 – Gartner Business Intelligence Summit – Aster Data, a proven leader dedicated to providing the best data management and processing platform for big data volumes and analytics-intensive applications, today unveiled the Aster Analytics Center to help customers accelerate development of advanced analytic applications. Simultaneously, Aster Data also launched the first multi-author destination site for enterprise and government organizations, systems integrators, ISVs, and developers who want to build competency on the MapReduce analytics processing framework and related MapReduce frameworks.http://www.mapreduce.org offers research, education, analysis, customer use cases, key learnings, and tips for anyone interested in understanding the analytical value of MapReduce and related frameworks such as SQL-MapReduce. The new Aster Analytics Center provides product offerings, services, a world-class team, and an elite ecosystem of partners to develop and deliver data-driven applications that use SQL and MapReduce.

www.mapreduce.org is designed to be a key destination for companies who want to understand and build skills around MapReduce, SQL-MapReduce, and related MapReduce technologies. It includes content from those developing data-intensive applications with MapReduce and related MapReduce frameworks such as SQL-MapReduce, as well as insights from industry analysts, customers, and vendors who are leveraging this technology popularized by Google to build next-generation analytic applications. Any industry, enterprise organization, government agency, or expert can contribute content to this site.

Wayne Eckerson, director for TDWI Research and author of the recent article titled Launching an Analytics Practice: 10 Steps to Success, said, “Companies today need experts who can help them accelerate delivery of next-generation, data-driven applications. To run deep analytics on big data requires understanding the analytical capabilities of new database technology, including knowledge of MapReduce and parallel processing requirements.”

Today’s news includes key additions to the Aster Data team. Jonathan Goldman, director of analytics for Aster Data, is responsible for the new Aster Analytics Center, which includes product offerings such as the recently announced Aster Analytics Foundation—a suite of ready-to-use analytics functions and best practices for building advanced analytic applications that involve large data volumes and many diverse data sources. Prior to joining Aster Data he was a principal scientist at LinkedIn, where he led a team of analytics researchers to build cutting-edge products with the rich data sets LinkedIn collected. He created the popular “People You May Know” product for LinkedIn, and developed and supported computationally-intensive and targeted content throughout the site including “Who Viewed My Profile,” the “Similar Jobs” function, and “Similar Members” function, among others. Goldman earned a PhD in physics from Stanford University and a bachelors of science in physics from MIT.

These are interesting developments given the increasing focus on handling complex, unstructured and larger datasets involved in predictive as well as descriptive analytics and data driven strategies.

A Software Called Rattle

One of my favorite software GUI’s- here is a paper talking of it, it was published in R Journal and describes Dr Graham William’s work in it. If you are software user or creator it is worth a dekko in terms of adding analytical extensions for your platform of business.

Interview Jeanne Harris Co-Author -Analytics at Work and Competing with Analytics

Here is an interview with Jeanne Harris, Executive Research Fellow and a Senior Executive at the Accenture Institute for High Performance and co-author of “Analytics at Work.”


Ajay- Describe your background in analytics and strategy

Jeanne- I’ve been involved in strategy and analytics since the mid 1980s, when I worked as part of a project that resulted in a Harvard Business Review article with Michael Porter entitled Information for Competitive Advantage. Since that time, I have led Accenture’s business intelligence, analytics, performance management, knowledge management, and data warehousing consulting practices. I have worked extensively with clients seeking to improve their managerial information, decision-making, analytical and knowledge management capabilities.

I am currently an Executive Research Fellow and a Senior Executive at the Accenture Institute for High Performance in Chicago. I lead the Institute’s global research agenda in the areas of information, technology, analytics and talent.

My research into building an enterprise analytical capability began in 1999, which led to an article called Data to Knowledge to Results: Building an Analytical Capability in California Management Review the following year.

In 2007, I co-authored “Competing on Analytics” with Tom Davenport, which argued that successful businesses must start making decisions based on data, not instinct.

Ajay- How is “Analytics at Work an extension of your previous work? How is it different and distinct?

Jeanne- In Competing on Analytics we argued that there are big rewards for organizations that embrace fact-based decision-making. High performers are 5 times as likely to view analytical capabilities as a key element of their strategy. Across the board, high performance is associated with more extensive and sophisticated use of analytical capabilities. Companies like USbased Progressive Insurance which build their corporate culture around analytics have a real and sustainable competitive advantage.

As I spoke to clients, I realized that for every company that viewed analytics as their new core competitive strategy, there were many more who just wanted pragmatic advice on how to use analytics to make smarter business decisions and achieve better results.

If an analytical organization could be established by executive fiat we would not have needed to write another book. But like anything worthwhile, putting analytics to work takes effort and thought.

Fortunately, every organization, regardless of its current analytical capability, can benefit by becoming more analytical, gaining better insights, making better decisions and translating that into improved business performance. In Analytics at Work, we describe the elements an organization needs to establish a sustainable, robust, enterprise-wide analytical capability. This book contains a lot of pragmatic “how to” advice gleaned from our research and Accenture’s many client experiences.

Ajay- Do you see Analytics as a tool for cost cutting especially in the present economic scenario?

Jeanne- Certainly, analytics are an important tool for cutting costs and improving efficiency. Optimization techniques and predictive models can anticipate market shifts, enable companies to move quickly to slash costs and eliminate waste. But there are other reasons analytics are more important than ever:

Manage risk. More precise metrics and risk management models will enable managers to make better decisions, reduce risk and monitor changing business conditions more effectively.

Know what is really working. Rigorous testing and monitoring of metrics can establish whether your actions are really making desired changes in your business or not.

Leverage existing investments (in IT and information) to get more insight, faster execution and more business value in business processes.

Invest to emerge stronger as business conditions improve. High performers take advantage of downturns to retool, gain insights into new market dynamics and invest so that they are prepared for the upturn. Analytics give executives insight into the dynamics of their business and how shifts influence business performance.

Identify and seize new opportunities for competitive advantage and differentiation.

Ajay- What are some analytics vendors and what do you think are their various differentiating points among each other?

Jeanne- Certain tools are ideally suited for some situations and not others.  It’s the same with analytics vendors.  At Accenture, we focus on matching the right tool with the demands of the situation, regardless of the vendor.

Ajay- What areas in an organization do you see Analytics applied the most and where do you think it is currently applied the least?

Jeanne- According to new Accenture research, two-thirds of senior managers in all areas of organizations the US and UK say their top long-term objective is to develop the ability to model and predict behavior, actions and decisions to the point where individual decisions and offers can be made in real time based on the analysis at hand[1]. Analytics is most frequently used in customer facing applications to generate customer insights, although in certain industries such as transportation it is also commonly used for logistics and yield management.  Right now, analytics is probably most infrequently used in HR, although talent management analytics is a very hot topic.

Ajay- What is the best case study you can think where Analytics made a difference? And name a case study where it back fired.

Jeanne- It is hard to pick one favorite case study, when we wrote a whole book full of them!  Harrahs is a great case study of a company that uses analytics for competitive differentiation.  Netflix is another company that has built its entire business model around an algorithm. Of course Google is essentially an analytical company too. What is of note is that during previous downturns, companies that thrived used data-derived insights made by informed decision makers to produce lasting competitive advantage.

In the book, we discuss the use and misuse of analytics as it relates to the global financial crisis, which we found to be a fascinating case study.

Ajay- Universities now offer Master in Analytics? What are your thoughts for an Ideal MS (Analytics) curriculum?

Jeanne- Yes, there are several universities around the world with degrees such as:

· Applied Analytics

· Applied Mathematics

· Econometrics

· Statistics

· Informatics

· Operations Research

Examples of universities in the US offering these programs include:

· Kellogg School of Management, Northwestern University

· Miami University (in Ohio)

· Central Michigan University,

· Villanova University

· North Carolina State University


Obviously analysts require extensive expertise in quantitative methods and modeling technology. But this is just the starting point. To be effective in business they also require industry and business process knowledge. They need to understand enough about IT to understand how analytics fit into the overall IT infrastructure. They need excellent written and verbal communications skills so their insights are understood.  Analysts must also have collaboration skills to work with business managers to apply insights and achieve better business performance. So relationship and consultative skills are critical. As analytics become more central to the organization, more analysts need to know how to lead, coach and develop other professional analysts.  They also will need to help coach and develop the analytical acumen of other information workers in the organizations.

Leading academic institutions are building more analytics into their business curriculums.  And the best analytics degree programs are adding more training to develop industry & business process acumen, as well as relationship, communication & consultative skills.

Biography-

Jeanne G. Harris has worked with analytics, decision support and business intelligence at Accenture for over 23 years and headed the consulting practice in that area for the firm for several years. She is now Executive Research Fellow and Director of Research for the Accenture Institute for High Performance Business. She has been co Author with Tom Davenport for the seminal path breaking book Competing with Analytics and now on Analytics at Work.

Here is a link to the new book-having read some of it (and still reading it) I recommend it highly as a practical actionable guide.






The declining market for Telecommunication Churn Models

[tweetmeme=”decisionstats”]

Users of Predictive Analytics within telecom sector can look into an interesting side effect of the iPhone – AT &T agreement. With Google also jumping into the market with it’s Droid – the new norms in Telecom agreements is lockedin contracts for consumers. While this is permitted by the telecom regulators as fair to competition- this also means that there is very little churn within these locked in contracts. This leads to further savings for the telecom provider allowing them to have higher profits and even share the profits by price decreases-

and thus the traditional bug bear of telecom analytics churn modeling is slowly losing importance to plain vanilla reporting or better data mining dashboard like solutions. Lower Churn , means also lower costs on analytics softwares to predict churn.

As competition within the 3G Mobile market ramps up due to Google’s entry and licensing with partners exclusively- the trend will likely increase for reduced churn due to locked in customers.Even existing mobile providers can offer discounts to lock in customers for not switching ( especially in Mobile Markets like India- where I have personally interacted with large players like Bharti) and China which has even bigger mobile market.

Ergo Lower need to buy softwares that predict churn-

See Below Image from TeraData’s Churn Model.

Analytics and BI for small biz

I saw a story on Warren B and Goldman S creating a 500$ million pool for small business owners.

  • The program will contribute $200 million to community colleges, universities and other institutions to provide small- business owners with practical business education.

  • Goldman Sachs repaid the $10 billion it was given last year under the taxpayer-funded Troubled Asset Relief Program, plus dividends. The firm continues to benefit from federal guarantees on about $21 billion of long-term debt.

  • Buffett, known as the “Oracle of Omaha” for his investing prowess, is the second-richest American. Berkshire, which invests in companies ranging from retailers to insurers, paid $5 billion in September 2008 to acquire preferred stock in Goldman Sachs that pays a 10 percent dividend. Berkshire, based in Omaha, Nebraska, also gained five-year warrants to buy $5 billion of common stock at $115 per share.

  • ( NOTE Curent Price of GS shares is 172$ – thats a 50% profit on 5 Billion~ 2.5 Billion for Mr Buffett but he is probably waiting for long term capital gains ax rates to kick in before encashing his patriotic  “Buy American. I am” warrants (see NYT op ed by him  http://www.nytimes.com/2008/10/17/opinion/17buffett.html )
  • A better analysis of the above Bloomberg story was given on Bloomberg itself at http://www.bloomberg.com/apps/news?pid=20601039&sid=asjp51YPDwJU
  • A small thought- could smaller businesses gain from efficiencies of programs like SPSS, SAS and R. Or would they be better off with customized GUI’s linked to their POS data.

Anyways a need for analytics for small businesses in inventory management, and sales planning could help. Joe the Plumber could do with some ETS and Regression Models as well.

However apart for Salesforce.com applications this field seems to be totally vacant for analytics. What are IBM SPSS, SAS, or even other stats packages doing for small businesses. or even developing Salesforce.com applications for their own equivalent software

The market could be an interesting one to atleast do a test in. Unless you don’t believe in test and control.

See below the IBM Cognos by IBM itself and the third party app by Pervasive for SAP Integration-

Citation-

http://sites.force.com/appexchange/listingDetail?listingId=a0N300000016YGYEA2

and

http://sites.force.com/appexchange/listingDetail?listingId=a0N300000016am1EAA

Curt Monash on Analytics with MapReduce

mon1In AsterData’s continued webcast series on MapReduce enabled analytics, here is the next in line, Curt Monash on Analytics for Data with MapReduce.

http://www.asterdata.com/wc_091203_masteringmapreduce/