Webfocus RStat: Pervasive BI using R

Here is a great reporting and BI tool from Information Builders  and uses the Rattle R GUI ( covered earlier here http://www.decisionstats.com/2009/01/13/interview-dr-graham-williams/).

So if you are looking for generation next reporting solution here is one called WebFocus RStat.



Predict the Future and Make Effective Decisions Today

Traditional reporting solutions provide a clear picture of past occurrences, but have little power to shed light on the future. The ability to anticipate and prepare for upcoming events can greatly impact the decisions that need to be made today.

WebFOCUS RStat is the market’s first fully-integrated business intelligence and data mining environment, seamlessly bridging the gap between backward and forward-facing views of business operations. With WebFOCUS RStat, companies can easily and cost-effectively deploy predictive models as intuitive scoring applications. So business users at all levels can make decisions based on accurate, validated future predictions, instead of relying on gut instinct alone.

WebFOCUS RStat provides a single platform for BI, data modeling, and scoring. This eliminates the need to purchase and maintain multiple tools, and frees analysts and other statisticians from spending countless hours extracting and querying data. At the same time, it reduces costs, simplifies maintenance, and optimizes IT resources.

But, the greatest benefit WebFOCUS RStat offers is significantly increased accuracy. With the R engine – a powerful and flexible open source statistical programming language – as its underlying analysis tool, WebFOCUS RStat can deliver results that are consistent, complete, and correct – every time.

WebFOCUS RStat provides:

  • A single tool, fully integrated with Developer Studio and WebFOCUS Reporting Servers with access to over 300 data sources, for both BI developers and data miners
  • Comprehensive data exploration, descriptive statistics, and interactive graphs
  • In-depth data visualization and transformation
  • Hypothesis testing, clustering, and correlation analysis

Other key WebFOCUS RStat features include:

  • The ability to build and export models for prediction and classification
  • Comprehensive model evaluation

Incidently the parent company which is based in Tennessee has some interesting numbers-


Company At A Glance
  • $300 million in revenue
  • Over 30 years of experience
  • More than 1,400 employees
  • Over 12,000 customers
  • Over 350 business partners
  • 47 offices and 26 worldwide distributors
  • Rapid application creation through easy incorporation of scoring routines into WebFOCUS reports

See Also-



Interview Peter J Thomas -Award Winning BI Expert

Here is an in depth interview with Peter J Thomas, one of Europe’s top Business Intelligence expert and influential thought leaders. Peter talks about BI tools, data quality, science careers, cultural transformation and BI and the key focus areas.

I am a firm believer that the true benefits of BI are only realised when it leads to cultural transformation. -Peter James Thomas


Ajay- Describe about your early career including college to the present.

Peter –I was an all-rounder academically, but at the time that I was taking public exams in the 1980s, if you wanted to pursue a certain subject at University, you had to do related courses between the ages of 16 and 18. Because of this, I dropped things that I enjoyed such as English and ended up studying Mathematics, Further Mathematics, Chemistry and Physics. This was not because I disliked non-scientific subjects, but because I was marginally fonder of the scientific ones. In a way it is nice that my current blogging allows me to use language more.

The culmination of these studies was attending Imperial College in London to study for a BSc in Mathematics. Within the curriculum, I was more drawn to Pure Mathematics and Group Theory in particular, and so went on to take an MSc in these areas. This was an intercollegiate course and I took a unit at each of King’s College and Queen Mary College, but everything else was still based at Imperial. I was invited to stay on to do a PhD. It was even suggested that I might be able to do this in two years, given my MSc work, but I decided that a career in academia was not for me and so started looking at other options.

As sometimes happens a series of coincidences and a slice of luck meant that I joined a technology start-up, then called Cedardata, late in 1988; my first role was as a Trainee Analyst / Programmer. Cedardata was one of the first organisations to offer an Accounting system based on a relational database platform; something that was then rather novel, at least in the commercial arena. The RDBMS in question was Oracle version 5, running on VAX VMS – later DEC Ultrix and a wide variety of other UNIX flavours. Our input screens were written in SQL*Forms 2 – later Oracle Forms – and more complex processing logic and reports were in Pro*C; this was before PL/SQL. Obviously this environment meant that I had to become very conversant with SQL*Plus and C itself.

When I joined Cedardata, they had 10 employees, 3 customers and annual revenue of just £50,000 ($80,000). By the time I left the company eight years later, it had grown dramatically to having a staff of 250, over 300 clients in a wide range of industries and sales in excess of £12 million ($20 million). It had also successfully floatated on the main London Stock Exchange. When a company grows that quickly the same thing tends to happen to its employees.

Cedardata was probably the ideal environment for me at the time; an organisation that grew rapidly, offering new opportunities and challenges to its employees; that was fiercely meritocratic; and where narrow, but deep, technical expertise was encouraged to be rounded out by developing more general business acumen, a customer-focused attitude and people-management skills. I don’t think that I would have learnt as much, or progressed anything like as quickly in any other type of organisation.

It was also at Cedardata that I had my first experience of the class of applications that later became known as Business Intelligence tools. This was using BusinessObjects 3.0 to write reports, cross-tabs and graphs for a prospective client, the UK Foreign and Commonwealth Office (State Department). The approach must have worked as we beat Oracle Financials in a play-off to secure the multi-million pound account.

During my time at Cedardata, I rose to become an executive and filled a number of roles including Head of Development and also Assistant to the MD / Head of Product Strategy. Spending my formative years in an organisation where IT was the business and where the customer was King had a profound impact on me and has influenced my subsequent approach to IT / Business alignment.

Ajay- How would you convince young people to take maths and science more? What advice would you give to policy makers to promote more maths and science students?

Peter- While I have used little of my Mathematics directly in my commercial career, the approach to problem-solving that it inculcated in me has been invaluable. On arriving at University, it was something of a shock to be presented with Mathematical problems where you couldn’t simply look up the method of solution in a textbook and apply it to guarantee success. Even in my first year I had to grapple with challenges where you had no real clue where to start. Instead what worked, at least most of the time, was immersing yourself in the general literature, breaking down the problem into more manageable chunks, trying different techniques – sometimes quite recherché ones – to make progress, occasionally having an insight that provides a short-cut, but more often succeeding through dogged determination. All of that sounds awfully like the approach that has worked for me in a business context.

Having said that, I was not terribly business savvy as a student. I didn’t take Mathematics because I thought that it would lead to a career, I took it because I was fascinated by the subject. As I mentioned earlier, I enjoyed learning about a wide range of things, but Science seemed to relate to the most fundamental issues. Mathematics was both the framework that underpinned all of the Sciences and also offered its own world where astonishing an beautiful results could be found, independent of any applicability; although it has to be said that there are few braches of Mathematics that have not be applied somewhere or other.

I think you either have this appreciation of Science and Mathematics or you don’t and that this happens early on.

Certainly my interest was supported by my parents and a variety of teachers, but a lot of it arose from simply reading about Cosmology, or Vulcanism, or Palaeontology. I watched a YouTube of Steven Jay Gould recently saying that when he was a child in the 1950s all children were “in” to Dinosaurs, but that he actually got to make a career out of it. Maybe all children aren’t “in” to dinosaurs in the same way today, perhaps the mystery and sense of excitement has gone.

In the UK at least there appears to be less and less people taking Science and Mathematics. I am not sure what is behind this trend. I read pieces that suggest that Science and Maths are viewed as being “hard” subjects, and people opt for “easier” alternatives. I think creative writing is one of the hardest things to do, so I’m not sure where this perspective comes from.

Perhaps some things that don’t help are the twin images of the Scientist as a white-coated boffin and the Mathematician as a chalk-covered recluse, neither of whom have much of a grasp on the world beyond their narrow discipline. While of course there is a modicum of truth in these stereotypes, they are far from being wholly accurate in my experience.

Perhaps Science has fallen off of the pedestal that it was placed on in the 1950s and 1960s. Interest in Science had been spurred by a range of inventions that had improved people’s lives and often made the inventors a lot of money. Science was seen as the way to a better tomorrow, a view reinforced by such iconic developments as the discovery of the structure of DNA, our ever deepening insight about sub-atomic physics and the unravelling of many mysteries of the Universe. These advances in pure science were supported by feats of scientific / engineering achievement such as the Apollo space programme. The military importance of Science was also put into sharp relief by the Manhattan Project; something that also maybe sowed the seeds for later disenchantment and even fear of the area.

The inevitable fallibility of some Scientists and some scientific projects burst the bubble. High-profile problems included the Thalidomide tragedy and the outcry, however ill-informed, about genetically modified organisms. Also the poster child of the scientific / engineering community was laid low by the Challenger disaster. On top of this, living with the scientifically-created threat of mutually-assured destruction probably began to change the degree of positivity with which people viewed Science and Scientists. People arrived at the realisation that Science cannot address every problem; how much effort has gone into finding a cure for cancer for example?

In addition, in today’s highly technological world, the actual nuts and bolts of how things work are often both hidden and mysterious. While people could relatively easily understand how a steam engine works, how many have any idea about how their iPod functions? Technology has become invisible and almost unimportant, until it stops working.

I am a little wary of Governments fixing issues such as these, which are the result of major generational and cultural trends. Often state action can have unintended and perverse results. Society as a whole goes through cycles and maybe at some future point Science and Mathematics will again be viewed as interesting areas to study; I certainly hope so. Perhaps the current concerns about climate change will inspire a generation of young people to think more about technological ways to address this and interest them in pertinent Sciences such as Meteorology and Climatology.

Ajay-. How would you rate the various tools within the BI industry like in a SWOT analysis (briefly and individually)?

Peter- I am going to offer a Politician’s reply to this. The really important question in BI is not which tool is best, but how to make BI projects successful. While many an unsuccessful BI manager may blame the tool or its vendor, this is not where the real issues lie.

I firmly believe that successful BI rests on four mutually reinforcing pillars:

  • understand the questions the business needs to answer,
  • understand the data available,
  • transform the data to meet the business needs and
  • embed the use of BI in the organisation’s culture.

If you get these things right then you can be successful with almost any of the excellent BI tools available in the marketplace. If you get any one of them wrong, then using the paragon of BI tools is not going to offer you salvation.

I think about BI tools in the same way as I do the car market. Not so many years ago there were major differences between manufacturers.

The Japanese offered ultimate reliability, but maybe didn’t often engage the spirit.

The Germans prided themselves on engineering excellence, slanted either in the direction of performance or luxury, but were not quite as dependable as the Japanese.

The Italians offered out-and-out romance and theatre, with mechanical integrity an afterthought.

The French seemed to think that bizarrely shaped cars with wheels as thin as dinner plates were the way forward, but at least they were distinctive.

The Swedes majored on a mixture of safety and aerospace cachet, but sometimes struggled to shift their image of being boring.

The Americans were still in the middle of their love affair with the large and the rugged, at the expense of convenience and value-for-money.

Stereotypically, my fellow-countrymen majored on agricultural charm, or wooden-panelled nostalgia, but struggled with the demands of electronics.

Nowadays, the quality and reliability of cars are much closer to each other. Most manufacturers have products with similar features and performance and economy ratings. If we take financial issues to one side, differences are more likely to related to design, or how people perceive a brand. Today the quality of a Ford is not far behind that of a Toyota. The styling of a Honda can be as dramatic as an Alfa Romeo. Lexus and Audi are playing in areas previously the preserve of BMW and Mercedes and so on.

To me this is also where the market for BI tools is at present. It is relatively mature and the differences between product sets are less than before.

Of course this doesn’t mean that the BI field will not be shaken up by some new technology or approach (in-memory BI or SaaS come to mind). This would be the equivalent of the impact that the first hybrid cars had on the auto market.

However, from the point of view of implementations, most BI tools will do at least an adequate job and picking one should not be your primary concern in a BI project.

Ajay- SAS Institute Chief Marketing Officer, Jim Davis (interviewed with this blog) points to the superiority of business analytics rather than business intelligence as an over hyped term. What numbers, statistics and graphs would you quote rather than semantics to help re direct those perceptions?

I myself use SAS,SPSS, R and find the decision management capabilities as James Taylor calls Decision Management much better enabled than by simple ETL tools or reporting and aggregating graphs tools in many BI tools.

Peter- I have expended quite a lot of energy and hundreds of words on this subject. If people are interested in my views, which are rather different to those of Jim Davis, then I’d suggest that they read them in a series of articles starting with Business Analytics vs Business Intelligence [URL http://peterthomas.wordpress.com/2009/03/28/business-analytics-vs-business-intelligence/ ].

I will however offer some further thoughts and to do this I’ll go back to my car industry analogy. In a world where cars are becoming more and more comparable in terms of their reliability, features, safety and economy, things like styling, brand management and marketing become more and more important.

As the true differences between BI vendors narrow, expect more noise to be made by marketing departments about how different their products are.

I have no problem in acknowledging SAS as a leader in Business Analytics, too many people I respect use their tools for me to think otherwise. However, I think a better marketing strategy for them would be to stick to the many positives of their own products. If they insist on continuing to trash competitors, then it would make sense for them to do this in a way that couldn’t be debunked by a high school student after ten seconds’ reflection.

Ajay- In your opinion what is the average RoI that a small, large medium enterprise gets by investing in a business intelligence platform. What advice would you give to such firms (separately) to help them make their minds?

Peter- The question is pretty much analogous to “What are the benefits of opening an office in China?” the answer is going to depend on what the company does; what their overall strategy is and how a China operation might complement this; whether their products and services are suitable for the Chinese market; how their costs, quality and features compare to local competitors; and whether they have cracked markets closer to home already.

To put things even more prosaically, “How long is a piece of string?”

Taking to one side the size and complexity of an organisation, BI projects come in all shapes and sizes.

Personally I have led Enterprise-wide, all-pervasive BI projects which have had a profound impact on the company. I have also seen well-managed and successful BI projects targeted on a very narrow and specific area.

The former obviously cost more than the latter, but the benefits are commensurately greater. In fact I would argue that the wider a BI project is spread, the greater its payback. Maybe lessons can be learnt and confidence built in an initial implementation to a small group, but to me the real benefit of BI is realised when it touches everything that a company does.

This is not based on a self-interested boosting of BI. To me if what we want to do is take better business decisions, then the greater number of such decisions that are impacted, the better that this is for the organisation.

Also there are some substantial up-front investments required for BI. These would include: building the BI team; establishing the warehouse and a physical architecture on which to deliver your application. If these can be leveraged more widely, then costs come down.

The same point can be made about the intellectual property that a successful BI team develops. This is one reason why I am a fan of the concept of BI Competency Centres [URL http://peterthomas.wordpress.com/2009/05/11/business-intelligence-competency-centres/ ].

I have been lucky enough to contribute to an organisation turning round from losing hundreds of millions of dollars to recording profits of twice that magnitude. When business managers cite BI as a major factor behind such a transformation, then this is clearly a technology that can be used to dramatic effect.

Nevertheless both estimating the potential impact of BI and measuring its actual effectiveness are non-trivial activities. A number of different approaches can be taken, some of which I cover in my article:

Measuring the benefits of Business Intelligence [URL http://peterthomas.wordpress.com/2009/02/26/measuring-the-benefits-of-business-intelligence/ ]. As ever there is no single recipe for success.

Ajay-. Which BI tool/ code are you most comfortable with and what are its salient points?

Peter –Although I have been successful with elements of the IBM-Cognos toolset and think that this has many strong points, not least being relatively user-friendly, I think I’ll go back to my earlier comments about this area being much less important than many others for the success of a BI project.

Ajay -How do you think cloud computing will change BI? What percentage of BI budgets go to data quality and what is eventual impact of data quality on results?

Peter –I think that the jury is still out on cloud computing and BI. By this I do not mean that cloud computing will not have an impact, but rather that it remains unclear what this impact will actually be.

Given the maturity of the market, my suspicion is that the BI equivalent of a Google is not going to emerge from nowhere. There are many excellent BI start-ups in this space and I have been briefed by quite a few of them.

However, I think the future of cloud computing in BI is likely to be determined by how the likes of IBM-Cognos, SAP-BusinessObjects and Oracle-Hyperion embrace the area.

Having said this, one of the interesting things in computing is how easy it is to misjudge the future and perhaps there is a potential titan of cloud BI currently gestating in the garage so beloved of IT mythology.

On data quality, I have never explicitly split out this component of a BI effort. Rather data quality has been an integral part of what we have done. Again I have taken a four-pillared approach:

  • improve how the data is entered;
  • make sure your interfaces aren’t the problem;
  • check how the data has been entered / interfaced;
  • and don’t suppress bad data in your BI.

The first pillar consists of improved validation in front-end systems – something that can be facilitated by the BI team providing master data to them – and also a focus on staff training, stressing the importance to the organisation of accurately recording certain data fields.

The second pillar is more to do with the general IT Architecture and how this relates to the Information Architecture, again master data has a role to play, but so does ensuring that the IT culture is one in which different teams collaborate well and are concerned about what happens to data when it leaves “their” systems.

The third pillar is the familiar world of after-the-fact data quality reports and auditing, something that is necessary, but not sufficient, for success in data quality.

Finally there is what I think can be one of the most important pillars; ensuring that the BI system takes a warts-and-all approach to data. This means that bad data is highlighted, rather than being suppressed. In turn this creates pressure for the problems to be addressed where they arise and creates a virtuous circle.

For those who might be interested in this area, I expand on it more in Using BI to drive improvements in data quality [URL http://peterthomas.wordpress.com/2009/02/11/using-bi-to-drive-improvements-in-data-quality/ ].

Ajay- You are well known with England’s rock climbing and boulder climbing community. A fun question- what is the similarity between a BI implementation/project and climbing a big boulder.

Peter –I would have to offer two minor clarifications.

First it is probably my partner who is better known in climbing circles, via here blog [URL http://77jenn.blogspot.com/ ] and articles and reviews that she has written for the climbing press; though I guess I can take credit for most of the photos and videos.

Second, particularly given the fact that a lot of our climbing takes place in Wales, I should acknowledge the broader UK climbing community and also mention our most mountainous region of Scotland.

Despite what many inhabitants of Sheffield might think to the contrary, there is life beyond Stanage Edge [URL http://en.wikipedia.org/wiki/Stanage ].

I have written about the determination and perseverance that are required to get to the top of a boulder, or indeed to the top of any type of climb [URL http://peterthomas.wordpress.com/2009/03/31/perseverance/ ].

I think those same qualities are necessary for any lengthy, complex project. I am a firm believer that the true benefits of BI are only realised when it leads to cultural transformation. Certainly the discipline of change management has many parallels with rock climbing. You need a positive attitude and a strong belief in your ultimate success, despite the inevitable setbacks. If one approach doesn’t yield fruit then you need to either fine-tune or try something radically different.

I suppose a final similarity is the feeling that you get having completed a climb, particularly if it is at the limit of your ability and has taken a long time to achieve. This is one of both elation and deep satisfaction, but is quickly displaced by a desire to find the next challenge.

This is something that I have certainly experienced in business life and I think the feelings will be familiar to many readers.



Peter Thomas has led all-pervasive, Business Intelligence and Cultural Transformation projects serving the needs of 500+ users in multiple business units and service departments across 13 European and 5 Latin American countries. He has also developed Business Intelligence strategies for operations spanning four continents. His BI work has won two industry awards including “Best Enterprise BI Implementation”, from Cognos in 2006 and “Best use of IT in Insurance”, from Financial Sector Technology in 2005. Peter speaks about success factors in both Business Intelligence and the associated Change Management at seminars across both Europe and North America and writes about these areas and many other aspects of business, technology and change on his blog [URL http://peterthomas.wordpress.com ].

Interview Jim Davis SAS Institute

Here is an interview with Jim Davis, SAS Institute SVP and Chief Marketing Officer.

Traditional business intelligence (BI) as we know it is outdated and insufficient-


Jim Davis, SAS Institute..

Ajay -Please describe your career in science to your present position. What advice would you give to young science graduates in this recession? What advice would you give to entrepreneurs in these challenging economic times?
Jim – After earning a degree in computer science from North Carolina State University, I embarked on a career path that ultimately brought me to SAS and my role as senior VP and CMO. Along the way I’ve worked in software development, newspaper and magazine publishing and IT operations. In 1994, I joined SAS, where I worked my way up the ranks from enterprise computing strategist focused on IT issues to program manager for data warehousing to director of product strategy, VP of marketing and now CMO. It’s been an interesting path.

My advice to new graduates embarking on a career is to leave no stone unturned in your search, particularly in this economy, but also consider adding to your skill set. A local example here in the Research Triangle area is at N.C. State University’s Institute for Advanced Analytics, which offers a master’s degree that combines business and analytical skills. These skills are very much in demand. SAS CEO Jim Goodnight helped establish this 10-month degree program where the first 23 graduating all found solid jobs within four months at an average salary of $81,000. Many of this year’s class, facing the worst economy since the Great Depression, have already found jobs. For entrepreneurs today, my advice is simple: make absolutely sure you’re creating a product or service that people want. And especially given the challenging economic environment, resolve to improve your decision making. Regardless of industry or company size, business decisions need to be based on facts, on data, on science. Not on hunches and guesswork. Business analytics can help here.

Ajay – What are some of the biggest challenges that you have faced and tackled as a marketing person for software? What continues to your biggest focus area for this year?

Jim – Among the biggest challenges that the SAS marketing team has worked to overcome is the perception that analytical software – advanced forecasting, optimization and data mining technologies – are way too complex, difficult to use, and only useful to a small band of highly trained statisticians and other quantitative experts, or “quants.” With lots of hard work, we’ve been able to show the marketplace that powerful tools are available in business solutions designed to solve industry issues.

The biggest marketing challenge now is showing the market how SAS offers unique value with its broad and integrated technologies. The industry terminology is confusing with some companies selling Business Intelligence tools that when you scratch the surface are limited to reporting and query operations. Other SAS competitors only provide data integration software, and still others offer analytics. SAS is the only vendor offering an integrated portfolio of these three very important technologies, as well as cross-industry and industry-specific intelligent applications. This combination, which we and others are calling Business Analytics, is a very powerful set of capabilities. Our challenge is to demonstrate the real value of our comprehensive portfolio. We’ll get there but we have some work to do.

Ajay -It is rare to find a major software company that has zero involvement with open source movement (or as I call it with peer-reviewed code). Could you name some of SAS Institute’s contribution to open source? What could be further plans to enhance this position with the global community of scientists?

Jim – SAS does support open source and open standards too. Open standards typically guide open source implementations (e.g., the OASIS work is guiding some of the work in Eclipse Cosmos, some of the JCP standards guide the Tomcat implementation, etc.).

Some examples of SAS’s contributions to open source and open standards include:

Apache Software Foundation – a senior SAS developer has been a committer on multiple releases of the Apache Tomcat project, and has also acted as Release Coordinator.

Eclipse Foundation — SAS developers were among the early adopters of Eclipse. One senior SAS developer wrote a tutorial whitepaper on using Eclipse RCP, and was named “Top Ambassador” in the 2006 Eclipse Community Awards. Another is a committer on the Eclipse Web Tools project. A third proposed and led Eclipse’s Albireo project. SAS is a participant in the Eclipse Cosmos project, with three R&D employees as committers. Finally, SAS’ Rich Main served on the board of directors of the Eclipse Foundation from 2003 to 2006, helping write the Eclipse Bylaws, Development Process, Membership Agreement, Intellectual Property Policy and Public License.

Java Community Process — SAS has been a Java licensee partner since 1997 and has been active in the Java Community Process. SAS has participated in approximately 25 Java Specification Requests spanning both J2SE and J2EE technology. Rich Main of SAS also served on the JCP Executive Committee from 2005 through 2008.

OASIS — A senior SAS developer serves as secretary of the OASIS Solution Deployment Descriptor (SDD) Technical Committee. In total, six SAS employees serve on this committee.

XML for Analysis — SAS co-sponsored XML for Analysis standard with Microsoft and Hyperion.

Others — A small SAS team developed Cobertura, an open source coverage analysis tool for Java. SAS (through our database access team) is one of the top corporate contributors to Firebird, an open source relational database. Another developer contributes to Slide WebDav. We’ve had people work on HtmlUnit (another testing framework) and FreeBSD.

In addition, there are dozens if not hundreds of contributed bug reports, fixes/patches from SAS developers using open source software. SAS will continue to expand our work with and contribute to open-source tools and communities.

For example, we know a number of our customers use R as well as SAS. So we decided to make it easier for them to access R by making it available in the SAS environment. Our first interface to R, which enables users to integrate R functionality with IML or SAS programs, will be in an upcoming version of SAS/IML Studio later this summer. We’re also working on an R interface that can be surfaced in the SAS server or via other SAS clients.

Ajay – What is business intelligence, and business analytics as per you? SAS is the first IT vendor that comes in the non sponsored link when I search for “business intelligence’ in Google. How well do you think the SAS Business Intelligence Platform rates across platforms from SAP, Oracle , IBM and Microsoft.

Jim – Traditional business intelligence (BI) as we know it is outdated and insufficient.

The term BI has been stretched and widened to encapsulate a lot of different techniques, tools and technologies since it was first coined decades ago. Essentially, BI has always been about information delivery, be it in static rows and columns, graphical representations of information, or the modern and hyper-interactive dashboard with dials and widgets.

BI technologies have also evolved to include intuitive ad-hoc query and analysis with the ability to drill down into the details within context. All of these capabilities are great for reacting to business problems after they have occurred. But businesses face diverse and complex problems, global competition grows exponentially, and increasingly restrictive regulations are just around the corner. They need to anticipate and manage change, drive sustainable growth and track performance.

Now they also have to operate in the midst of a ruinous global credit and liquidity crisis. Reactionary decision making is just not working. Now more than ever, progressive organizations are looking to leverage the power of analytics, specifically business analytics. Why? Real business value comes from capitalizing on all available information assets and selecting the best outcome based on every possible scenario.

Proactive evidence-based decisions – not just information delivery – should drive informed decisions. That is business analytics and that is what SAS provides its customers.

Businesses require robust data integration, data quality, data and text mining, predictive modeling, forecasting and optimization technologies to anticipate what might happen, avoid undesired outcomes and course correct.

These capabilities need to be in synch and integrated from the ground up rather than cobbled together through acquisitions. More importantly, they cannot be part of a monolithic platform that requires 2-3 years before any real value is derived.

They must be part of an agile framework that enables an organization to address its most critical business issues now and then add new functionality over time. A business analytics framework — like the one SAS provides — enables strategic business decisions that optimize performance across an organization.

Ajay – For 4 decades SAS Institute created, nurtured and sustained the SAS language, often paying from its pocket for conferences, papers. Till today SAS Language code on your website is free and accessible to all without a registration unlike other software companies. What do you have to say about third party SAS language compilers like “Carolina” and “WPS”

Jim – There is no doubt that much of the power and flexibility behind our framework for business analytics is derived from our SAS language. At its core, the Base SAS language offers an easy-to-learn syntax and hundreds of language elements, pre-built SAS procedures and re-usable functions. Our focus on listening and adapting to customer’s changing needs has helped us, over the years, to sustain and continuously improve the SAS language and the SAS products that leverage it.

Competition comes in many forms and it pushes us to innovate and keep delivering value for our customers. Language compilers or code interpreters like Carolina and WPS are no exception.

One thing that sets SAS apart from other vendors is that we care so deeply about the quality of results.Our Technical Support, Education and consulting services organizations really do partner with customers to help them achieve the best results.

As Anne Milley, SAS’ director of technology product marketing, told DecisionStats this March, customers have varied and specific requirements for their analytics infrastructure. Desired attributes include speed, quality, support, backward and forward compatibility, and others. Certain customers only care about one or two of these attributes, other customers care about more. With our broad and deep analytics portfolio, SAS can uniquely provide the analytics infrastructure that meets a customer’s specific requirements, whether for one or many key attributes. Because of this, an overwhelming majority vote with their pocketbooks to select or retain SAS.

For example, as Anne noted, for some customers with tight batch-processing windows, speed trumps everything. In tests conducted by Merrill Consultants, an MXG program running on WPS runs significantly longer, consumes more CPU time and requires more memory than the same MXG program hosted on its native SAS platform.

At SAS, we provide a complete environment for analytics — from data collection, manipulation, exploration and analysis to the deployment of results. One example of our continuous innovation, and where we are devoting R&D and sales resources, is the SAS In-Database Processing Initiative. Through in-database analytics, customers can move computational tasks (e.g., SAS code, SQL) to execute inside a database. This streamlines the analytic data preparation, model development and scoring processes. Customers needing to leverage their investments in mixed workload relational database platforms will benefit from this SAS initiative. It will help them accelerate their business processes and drive decisions with greater confidence and efficiency.

Ajay – Are you going to move closer for an acquisition? Or be acquired? Which among the existing BI vendors are you most comfortable with in synergy of products and philosophy?

Jim –SAS is in an enviable position as the largest independent provider of business intelligence (BI) software, and the leader in the rapidly emerging field of business analytics, which combines BI with data integration and advanced analytics. We have no plans, nor have had any talks regarding SAS being acquired.

As for SAS acquiring another company, we continuously look for technologies complementary to our wide and deep lineup of business analytics solutions, many of which are targeted at the specific needs of industries ranging from banking, insurance and pharma to healthcare, telecom, manufacturing and government.

Last year, SAS made two acquisitions, IDeaS Revenue Optimization, the premier provider of advanced revenue-management and optimization software for the hospitality industry, and Teragram, a leader in natural language processing and advanced linguistic technology. IDeaS delivers to SAS and our hotel and hospitality customers software sold as a service that meets a critical need in this industry. Teragram’s exciting technology has enhanced SAS’ own robust text mining offerings.

Ajay – Jim Goodnight is a legend in philanthropy, inventions, and as a business leader (obviously he has a fine team supporting him). Who will be the next Jim         Goodnight ?

Jim – I think Jim Goodnight best addressed the question of succession plans at SAS best a few years ago when he noted that the business world often places undue emphasis on the CEO and forgets about the CTO, CMO, CFO and other senior leaders who play a key role in any company’s success. SAS has a very strong executive management team that runs a two billion-dollar software company very effectively. If a “next Jim Goodnight” is needed in the future, SAS will be ready and will continue to provide our customers with the business analytics software they need.


Jim Davis, Senior Vice President and Chief Marketing Officer for SAS, is responsible for providing strategic direction for SAS products, solutions and services and presenting the SAS brand worldwide. He helped develop the Information Evolution Model and co-authored “Information Revolution: Using the information Evolution Model to Grow your Business.” By outlining how information is managed and used as a corporate asset, the model enables organizations to evaluate their management of information objectively, providing a framework for making improvements necessary to compete in today’s global arena.

s285_sas100k_130w SAS (www.sas.com) is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. Through innovative solutions delivered within an integrated framework, SAS helps customers at more than 45,000 sites improve performance and deliver value by making better decisions faster. Since 1976 SAS has been giving customers around the world The Power to Know®.

iBi – Business Intelligence Applications on the iPhone

From the press release at QlikTech at http://www.qlikview.com/Contents.aspx?id=9836

They actually end up promoting Oracle’s mobile BI app even though they are trying to bash it up.

QlikTech, the worlds fastest-growing Business Intelligence (BI) company, today announced the immediate availability of QlikView for iPhone, the very first truly interactive mobile BI app built specifically for the iPhone. Unlike Oracles mobile BI offering that features a rigid interface and limited functionality, QlikView for iPhone fully leverages iPhones multitouch and GPS features to deliver QlikViews renowned, industry-defining interactive capabilities. The result is a groundbreaking app that puts the power of sophisticated, real-time business answers in the hands of mobile users worldwide. It can be downloaded for free from Apples Mobile App Store on iTunes.

Product Highlights:

  • Interactive click through line items on a list box or chart to get to answers, going deep into regional or product data.
  • Coverflow flip through relevant business analysis, make a new selection and those changes are instantly reflected throughout.
  • GPS-enabled automatically delivers local customer sales, service or inventory data as reps approach a customer or supplier facility.
  • Feature-rich use Search, Bookmark and Shake to Erase

Smarter, Faster, Real-Time Interactive Analysis
Mobile professionals need access to comprehensive, real-time information, not static reports that lack detail from offerings like Oracles mobile BI tool. With QlikView for iPhone, salespeople can drill deep into accounts and get granular, up-to-the minute answers and analysis that help them do their job better. From specific customer or product data, down to a single SKU or employee name, QlikView for iPhone gets users what they need, the moment they need it.

We comprehensively surveyed the BI mobile landscape and it was clear all previous attempts at addressing user needs failed miserably, said Anthony Deighton, SVP Product, QlikTech. Just posting a static report on a mobile screen, as Oracles solution does, may be marginally helpful, but creates a tremendously frustrating user experience, leaving no opportunity to interact with the data. With QlikView for iPhone, users get a mobile view of a relevant data subset, as well as access to the specific answers they seek. This interactive dynamic is the only way to truly fulfill the promise of mobile BI.

The Only Mobile BI Tool with Multitouch, Coverflow and GPS Integration
QlikView for iPhone takes full advantage of the iPhones native interface. The entire application is multitouch driven with complete implementation of the iPhone finger gestures users are accustomed to. Simple finger-swipes and finger-pinches enable users to select, interact and drill down into data. And to clear selections, all users have to do is shake the device. Apples popular 3-D Coverflow feature is also enabled, allowing users to flip through analyses in the same way they would through album covers and artists in iTunes. Real-time data changes are also instantly reflected in every Coverflow chart.

And here is the actual Oracle application


Enhance Productivity for Mobile Business Users
Oracle Business Indicators is the first in a series of business applications for delivering Oracle business information to the Apple iPhone. The application provides mobile business users with real-time, secure access to business performance information on one of the industry’s most exciting and engaging mobile devices – Apple iPhone.

Oracle Business Indicators allows users to view and interact with Oracle Business Intelligence (BI) Applications that include financial, human resources, supply chain, and customer relationship management analytics, as well as analytical alerts generated by Oracle Delivers, an integrated component of Oracle Business Intelligence Enterprise Edition Plus (OBIEE). Leveraging full advantage of the Apple iPhone mobile platform, Oracle Business Indicators is built as a native application to offer highly intuitive and flexible features including browse, search, and favorites for a superior overall end user experience.

* Pre-defined business indicators-Pre-built metrics and reports include financial, human resources, supply chain, and customer relationship management analytics.
* Timely alerts on exception conditions-Enables the mobile user to review alerts generated by conditions pre-defined in Oracle Delivers. A user can select an alert entry and immediately review an associated analytic report.
* Superior user experience-Offers a highly intuitive user interface for browsing, searching, and locating business performance metrics.
* Robust security-Based on the same user security model as Oracle BI Applications. Also supports Secure Sockets Layer (SSL) encryption technology.

Use BI to say BYE to the recession

While the failure of predictive analytics models in the mortgage industry and financial services industry to PREDICT default rates started the recession,

here is something which may just ensure-

Why 2009 wont be like 1929.

Business Intelligence for better Decision Management.

Bad news on coming demand mismatch enabled faster decision making in cutting interest rates, coordinated global action. Inventories fell faster than expected, as companies aligned supply chains faster.



 A webinar coming up on April 16 on using Technology to beat the recession back.

Is this the beginning of the end of the recession? As Winston Churchill said- This may be the end of the beginning.

How are you using 2009 technology to align decision management in the current economic downturn? How much training are you giving yourself for these interesting times.

The divided world of Business Intelligence

The world of business intelligence is divided between the haves and have not the want to be and the could bees.

Divided between camps of open Source and closed source

.Microsoft alliances versus IBM alliances with SAP alliances and Oracle alliances. Jostling like knights at King Arthurs tables. Writers in the BI blogosphere are trapped in exclusive arrangements, their own quest for intellectual satisfaction and the inherent frenzy at which technology changes faster than you can say the word Cloud manifesto. There are BeYe network, Intelligent Enterprise ,CIO world , Company Blogs at SUN, IBM and SAS, superbly written individual blogs , blog aggregators -some of whom do share their knowledge out.But some dont.

And the customer is confused- where is the intelligence in a divided business intelligence world.


BI Customers in a Recession


A customer is the most important visitor on our premises,

he is not dependent on us.

We are dependent on him.

He is not an interruption in our work. He is the purpose of it.

He is not an outsider in our business. He is part of it.

We are not doing him a favor by serving him. He is doing us a favor by giving us an opportunity to do so.
Mahatma Gandhi

And why do 1/3 rd of BI installs go wrong and what customer protection is there in an industry that allows 1/3 rd of installs to give negative ROI.

Divided we bill is better than united we serve.


Author- These are my Personal Views only.

Business Intelligence and The Heisenberg Principle

The Heisenberg Principle states that for certain things accuracy and certainty in knowing one quality ( say position of an atom) has to be a trade off with certainty of another quality (like momentum). I was drawn towards the application of this while in an email interaction with Edith Ohri , who is a leading data mining person in Israel and has her own customized GT solution.Edith said that it seems it is impossible to have data that is both accurate (data quality) and easy to view across organizations (data transparency). More often than not the metrics that we measure are the metrics we are forced to measure due to data adequacy and data quality issues.

Now there exists a tradeoff in the price of perfect information in managerial economics , but is it really true that the Business Intelligence we deploy is more often than not constrained by simple things like input data and historic database tables.And that more often than not Data quality is the critical constraint that determines speed and efficacy of deployment.

I personally find that much more of the time in database projects goes in data measurement,aggregation, massaging outliers, missing value assumptions than in the high value activities like insight generation and business issue resolution.

Is it really true ? Analysis is easy but the data which is tough ?

What do you think in terms of the uncertainty inherent in data quality and data transparency-