Business Objects aims to predict the future with business intelligence

This is a powerful move for Business Objects and SAP. Business Objects have had for years the click-and-drag reporting capabilities, the functionality of standard deviation, and with the predictive analytics capabilities this will become a powerful force in business analytics. I have always been impressed by the products of these companies. The combination of these two companies, their technical functionalities and worldwide market reach put us closer to unleash the power of the mind by putting business analytics at the fingertip of every employee in a company.

Tools During Economic Recession: Forecasting & Business Analytics

The economic recession in the U.S., the housing and credit crisis, and the high oil prices are bringing business analytics to the forefront of companies. See Preparing your Company for a Recession at http://atomai.blogspot.com/2008/02/preparing-your-company-for-recession.html. In good economic times business analytics is important. In challenging economic times it may be the difference between success and surviving.

These are the best of times and the worst of time. Business, technology, and science have leap hundreds of years in the last couple of years. Risk and reward are closely intertwined with the vision of our business leaders and their ability to be at the forefront of change. See Evidence-based Enterprise Business Analytics Model: Turning Around in a Quarter. Companies must use all the resources available to become better at forecasting risk. See Bernanke: Banks must get better at foreseeing risk....

Those of us in business analytics have the ability and knowledge to incorporate forecasting and data mining techniques that separates the clusters of data and clarify the driving factors. See Business Case for Analytics: Explaining Cluster Analysis; and Explaining the Value of Business Analytics: Clarifying driving factors in a decision support system. Those of us in business analytics, data mining, and forecasting must do better in explaining the business value to our companies. See Enterprise Analytics: A Business Decision.

We must be specific and present a complete strategy to executive management whether is a workplace reorganization of restructuring, a marketing plan, an investment strategy, or an operational strategy. We cannot just give "the numbers" and not look at the big picture. See Best-laid plans . . .at http://www.app.com/apps/pbcs.dll/article?AID=/20080606/SPORTS06/806060350/1002/SPORTS

We have the ability and responsibility to present solutions. We can make a difference. The future is now. See Intersection of Business, Science, and Technology: Business Analytics.

Unleashing the Power of the Mind™

Real-Time Business Analytics

A new discovery about the human brain gives us a good insight in how to improve real-time business analytics and predictive modeling. The discovery is that the brain compensates the neural lag that everyone experiences by giving us a glimpse of events one-tenth of a second before they occur. See Key to All Optical Illusions Discovered. The brain predicts what is going to occur based on available data and experience. See The Attention System of the Human Brain. Imagine the implication for the financial services industry. Banks, investment banks, and brokerage houses could profit or lose billions during stocks and commodities trading, if they had a one-tenth advantage over their competitors. See Financial Services Business Analytics: Evidence-Based Model. Envision a system that reminds customers about an item that they may have forgotten before leaving the store in the retail industry. Also, picture a system that reminds network administrators to check a specific system, server, or pathway. Depict a system that reminds physicians to check for the symptoms of a specific disease, recommend a particular test, or reminds a surgeon to check a particular area of the body.

In an interdependent and continuously changing global economy, companies need to accurately forecast and anticipate trends. Companies must use the latest advances in science, technology, and business to gain leverage and improve profitability. See Intersection of Business, Science, and Technology: Business Analytics; and Business Analytics Technique: Borrowing From Medical Imaging at http://atomai.blogspot.com/2008/05/new-business-analytics-technique.html.

The advances in technology and sciences allow these tools to be implemented rapidly and in a cost efficient manner. See High Performance Computing (HPC) is Changing the World; HP Delivers Real-time Business Information with Enhanced Neoview Capabilities; and Business Competency Model: Turning Around in a Quarter.

Business Analytics: Unleashing the Power of the Mind™

Analytic Culture – Does It Matter?

This is a good article that explains a difficult issue in change management in the area of business intelligence and change management: the importance of understanding the culture within a company if you want to achieve change. Dave Wells has done an excellent job at explaining how to identify different cultures. The key for change is to adapt our product and services to the existing culture. This is one reason that Microsoft BI stack, or the iGoogle predictive analytics tool could become the products of the future. See, The New ADAPA iGoogle gadget: Google Predictive Analytics; Microsoft SQL 2005 Analysis Services: Ten Best Practices© at http://atomai.blogspot.com/2007/03/data-mining-and-microsoft-sql-2005_23.html. These products appeal to the broader cultures: people who already use Excel, or people who want to limit their cost by using Software-as-a-Service. See, Software as a Service overview . It is important to remember that it is not just the algorithm but the amount of data that makes business analytics a reality today. See, More data usually beats better algorithms . SAS and KXEN have powerful algorithms and business models, but I think that those products do not take into account the culture within a company as well Google and Microsoft.

High Performance Computing (HPC) is Changing the World

This short video is a powerful tool to explain how science and technology are interacting for advacements beyond our imagination, and the concept of HCP. "Powerful Beyond Imagination". The International Conference on High Performance Computing, Networks, Storage, and Analysis will take place on November 15-21, 2008, in Austin, Texas. http://sc08.supercomputing.org/ This is the 20 years celebration of the super computing conference!

These two events may be fun:

• a Music Room, conveniently located in the convention center lobby, where conference attendees can sit and listen to other attendees play during scheduled times throughout the conference. Basic orchestral and woodwind instruments will be available, including a Baby Grand piano, but you are encouraged to bring your own. (A reservation must be made in order to secure a time for you to play in the music room. More about signing up will be provided later).
• Digital Vibrations: Is it Real?, where attendees will visit a kiosk, listen to a series of songs, and identify ones they think are computer generated versus those they think are produced with actual instruments. A prize will be awarded to the person who correctly identifies all songs.

HP Delivers Real-time Business Information with Enhanced Neoview Capabilities

These are the type of advances in technology that makes business analytics a reality today, by imitating the capabilities of the human brain. The enhanced Neoview capabilities for business intelligence are:

1. It efficiently processes large and small transactions simultaneously
2. Forecast traffic to avoid delays and improve performance (i.e., it avoids those instances when you see a person but forget their name, or
3. Make sure that real-time information is up-to-date (i.e., avoid those moments when you go to a room to do something and ask yourself, "why am I here?")
   

Intersection of Business, Science, and Technology: Business Analytics

We are living in the future. Some time ago business, science, and technology were three distinct and separate disciplines. The advancements in these three disciplines during the last five years have created a quantum leap in how each directly affects the others. Businesses, large and small, make global transactions on a daily basis. Technology allows people from around the world to communicate internationally and storage large volumes of digital data. Science allows accurate predictions using large databases around the world.

What is business analytics? Business analytics is the intersection of business, science, and technology that allow us to unleash the power of the brain. Historically, mankind has attempted to replicate the decision-making prowess of the brain in order to progress. The financial services industry has transformed from local lenders and borrowers, to complex international financial transactions involving international and local banks, investment bankers and insurance companies. The healthcare industry has worldwide specialty surgeries, and the pharmaceutical industry cooperative bio-molecular research and genome research, facilities. The chemical and energy industries have found new ways to find and convert raw materials. The media industry has gone from the books to the internet.

The common characteristics of these advances are the way that business, technology, and science have cooperatively intersected to promote common objectives. The next frontier of business analytics is to tap into the collective power of the individual and unleash the power of the human brain. Companies like GE, Microsoft, Hewlett-Packard, IBM, SAS Institute, Exxon, and Google are among the thousand of companies around the world that are working to unleash the power of the mind by intersecting business, technology, and science. Business analytics is the future, and the future is now.

Business Analytics Technique: Borrowing From Medical Imaging

A study published in the journal Nature shows a scanning technique developed by GE Healthcare to detect cancer that can be adapted to business analytics in any industry. This technique involves the concept of separating the clusters in the data and clarifying the driving factors. See, Explaining the Value of Business Analytics: Clarifying driving factors in a decision support system.

The technique involves:
1. Cluster analysis to separate the data. See, Business Case for Analytics: Explaining Cluster Analysis.
2. Vector analysis using regression to clarify the driving factors. See, Three-Dimensional Business Analytics: How Deep is the Ocean?
3. A Human-Interaction Computer Visualization tool. See, Human Factors In Visualization Research; Visualization Projects for Data Mining; Information Visualization and Visual Data Mining.

Business analytics can adapt some of the state-of-the-art solutions from medical imaging techniques and use them for business forecasting, as well as to determine whether strategies are working well at an earlier stage. This would allow businesses to be flexible and adapt to changing an ever changing economic environment. See, Preparing Your Company For Recession; and Evidence-based Enterprise Business Analytics Model: Turning Around in a Quarter.

I envision in the future that business analytics techniques will be at the same level than medical imaging. See, NIH-NSF Visualization Research Challenges Report; and Kaizen and Analytics: The Power of Each Employee to See Data.

Unleashing the Power of the Mind!

iGoogle Predictive Analytics Gadget: Feedback

This is the feedback that I have gotten so far on this new predictive analytics tool

E. Harris - “I think the gadget is a boost to marketing campaign managers, small business website owners and SEO professionals. It gives an immediate ability to test and analyze content and campaigns real-time. I think there is a high degree of value here as the wait time for results will be Google dependent. There is also independence to the subscriber, if you will, to become less reliant on the high costs associated with statistic and ranking providers. We may also see an increase in the length of time remains on a website as it is evaluated predictively for value.”

D. Padmanabhan - “I tried a demo NN model and found it interesting. It will be interesting if the models can be shared among different users. I would also like to see additional outputs such as prediction errors or maybe even error charts.”

You can see my comments and Mike Zeller (CEO of Zementis that developed this iGoogle tool) response at: The New ADAPA iGoogle gadget: Google Predictive Analytics

The competition between Microsoft and Google in the area of analytics is unfolding. See, The Future of Business Analytics: Microsoft vs. Google. Microsoft SQL 2005 Server Analysis Services and the Excel 2007 add-in offer a proprietary model with the advantages that people are used to Microsoft products. The Google gadget for predictive analytics offers a new model of Software-as-a-Service, which could decrease the cost of predictive modeling in a company. See, Software as a Service overview; and Delivering Software as a Service.

The Attention System of the Human Brain

It is important to understand how the human brain functions in the area attention, at the cognitive and neuronal levels, so we can attempt to replicate these functions in any decision support and business analytics system. The concepts in this article cover the fundamentals that every person in the analytics field should understand. Among the interesting areas for practical application:

1. Data processing and analytics are separate functions that interact – A practical application is that we should not be processing and analyzing data in the same server.
   Orienting – Practical applications include: visualization tools, human-computer interaction (HCI), and the need for size, color and depth (right and left hemispheres) representation of the data. See, Business Case for Analytics: Explaining Cluster Analysis; Explaining the Value of Business Analytics: Clarifying driving factors in a decision support system ; and Three-Dimensional Business Analytics: How Deep is the Ocean?
2. Pattern Recognition – Practical applications include: utilization of colors in the analytics visualization tools; utilization of forecasting vectors to determine complex patterns; and data does not need to be 100% clean since the brain will fill the missing parts.
3. Detection – Practical applications include: the ability to visually represent data in its totality, while having the functionality to dynamically select specific areas of the data for further study; interactivity for further study depends n alertness and this depends on robust and fast system of analytics (i.e., the fastest the report creation the higher our alertness and detection); and speed in the system is directly correlated to lower quality of data and produces a higher error rate.

Knowing the anatomical reasons for decision support and analytics in brain function gives a higher importance to create decision support systems (which include predictive modeling) and make it available to everyone within a company or organization. See, Kaizen and Analytics: The Power of Each Employee to See Data; and Business Analytics: Unleashing the Power from Within .

The New ADAPA iGoogle gadget: Google Predictive Analytics

After talking with Mike Zeller the CEO of Zementis I decided to re post this blog with Mike comments. In the interest of full-disclosure, Mike is a professional colleague and I always enjoy our conversations. In a nutshell, Mike wants to make the point that:
1. This product is for those who are knowledgeable in the field of analytics.
2. Import/Export functionality using "browse" capability is part of the product.
3. Import/Export functionality for Excel files is already part of this product.

The fact that Google is moving toward Software-as-a-Service in analytics is impressive and the correct direction. Also, Mike points out that this is the first step in a journey to put analytics capabilities in the hands of everyone. The future is here and it is exciting! Enjoy the post, and by all means give this product a try and let me know your opinion (I do not post anonymous opinions).

You can install the engine as an iGoogle gadget by following the link below:http://www.google.com/ig/adde?hl=en&moduleurl=hosting.gmodules.com/ig/gadgets/file/115640297026242314759/adapawidget.xml

I was looking at the new ADAPA iGoogle gadget and this is a tool that would mostly be used by people that have technical knowledge about predictive analytics. There are some basic improvements that must be made so that analytics is available to "everyone" (see my post Business Analytics: Unleashing the Power from Within).

Mike's comments: "Yes, you are correct that ADAPA is a tool for people who are somewhat familiar with predictive analytics. The intention of the ADAPA iGoogle gadget is not to teach "everyone" about predictive analytics, but to deliver a tool that makes it easy to deploy and use such models.

ADAPA bridges the gap between the scientists developing the models, the IT folks who have to integrate & deploy the models, and the business who ultimately want to use the results of the models to drive the business process.

Predictive analytics uses mathematical models that assume a certain technical knowledge and for many users that will always remain a black box. Only in the context of a business application, most users will understand the outcome of a particular model, e.g., that a high risk score means that the related credit application is bad for business.

Following your vision, we should strive towards building many of these iGoogle Gadgets in a form that focuses on the business user and "hides" the technical details.

Our ADAPA iGoogle Gadget was just an example to demonstrate that is actually possible to deliver predictive analytics as service and make it available via simple iGoogle gadgets. We wanted to empower the scientists and engineers to easily build business applications that leverage the potential of predictive analytics."

My wish list for this product:

Keep it simple!

1. The Demo is talking about PMML standards, etc. Most users do not care about the technical aspects and standards, they just want to dig in and make it happen. Do not get a technical person to explain how it works, get a sales person to explain how it works. We usually complaint that sales people over simplify technical issues, but this is a case that "sometimes less is better than more". Go back to Google home page and compare it with Yahoo and MSN to understand this concept.
   Mike's comments: "In order to understand the basics about predictive analytics, it is critical to know that there is a standard to represent such models. If you want to represent a web page, you need to know that there is something like HTML. If you want to represent a predictive model, you need to know that the common language is PMML and that there is such a file format.
   Unfortunately, we still have much work to do in order to evangelize the PMML standard. Many people don't know about this standard which allows models to be shared between various software tools from different vendors."
2. The converter should be behind the scenes. Again, just make it happen and do not bore us with the details.
   Mike's comments: "We made a conscious decision to keep the PMML converter a separate product, so users can choose to only convert various PMML versions, but not be locked into using our ADAPA deployment platform. It is our support to the PMML community and will remain a free service."
3. Explanation for models should be simple. For example: "Linear regression takes numerical values only. Numerical means that if you can add those values and it means something. You can represent months in numbers but if you add those numbers it does not mean anything. Numerical representation of months are not a numerical value."
   Mike's comments: "'Explanation' are supposed to explain what the model does, this is an element of the PMML standard (description). Maybe it could be more descriptive, but it is not really the place to explain how a linear regression works."
4. I think that the future of analytics is to allow everyone to see the clusters in the data and clarify the driving factors. See, Kaizen and Analytics: The Power of Each Employee to See Data

Google must overcome the basic rule: People would rather live with a problem they cannot solve than accept a solution they cannot understand . I am sure that the science behind the models are good. On the other hand, the science behind this type of algorithms have been out in the market for a long time. The differentiators are: that is free and that it could be used by a company as a Software-as-a-Service (SaaS). See, Software as a Service overview.
Mike's comments: "We are on the same page here. The goal of this application is to make it easy to deploy, integrate, and execute predictive models.
It is the first step towards a more general adoption of predictive analytics. Now we can work towards the same simplicity in business applications that sit on top of the ADAPA deployment platform and draw their decisions from the predictive power of advanced scientific algorithms."

Predictive Analytics Engine available as an iGoogle gadget

This was a posting in a group that I have at Facebook (Analytics, Data Mining, Predictive Modeling, Artificial Intelligence). As predicted on May 12, 2008, the next battleground between Google and Microsoft is going to be in the realm of business analytics. The science in this Google product is good, as is the science behind Microsoft Analysis Services too.

In my opinion Google is correct in assuming that the future business analytics is in Software-as-a-Service (SaaS). I specifically addressed this topic on blog postings of March 10 and March 26

"If you are interested in executing data mining models such as neural networks, SVMs, logistic and linear regression, ... from your desktop, check out the new ADAPA iGoogle gadget. It allows for the uploading of data mining models expressed in PMML (Predictive Modeling Markup Language) for scoring. Model execution is done through Amazon EC2 and is free. A paid version which will allow for real-time scoring via web-services (as a SaaS - Software as a Service) is going to be launched in May. You can install the engine as an iGoogle gadget by following the link below:http://www.google.com/ig/adde?hl=en&moduleurl=hosting.gmodules.com/ig/gadgets/file/115640297026242314759/adapawidget.xmlAlso available is a converter gadget to convert old PMML to version 3.2:http://www.google.com/ig/adde?hl=en&moduleurl=hosting.gmodules.com/ig/gadgets/file/115640297026242314759/converterwidget.xmlDecision trees is next in the range of mining models that ADAPA supports. Have fun!Alex"

Business Analytics: Unleashing the Power from Within

Every person has the inherent ability to interpret the world around them in a physical and in an intuitive manner. This ability of the human mind to deduce facts and patterns based on both external and internal conditions is one of the main characteristics that separate us from other species. Business analytics have evolved to give every member of a company the ability to interpret known metrics like revenue and income, as well as internal evidence-based multidimensional analysis (like the predict probability for an event to occur) which clarifies the drivers in the data.

In my experience, executives understand the concept that people are the most important asset within an organization. Also, they understand the importance of business analytics to maintain a competitive advantage. Business analytics is an enterprise continuous improvement system that allows every person within an organization to detect patterns in the data that allow for incremental improvements on a regular basis. Companies are like large ships, they are difficult to turn around. The advantage of business analytics is that it allows for regular and incremental changes in a business that allows for change to take place.

Allowing every employee the ability to suggest incremental changes, based on business analytics, which will improve their own performance, is kaizen analytics. Kaizen analytics assumes that employees are the most important asset in an organization. Therefore, analytics and improvement should permeate through out the entire company.

In the last few years some of the best minds in software companies have developed the technology and science to put business analytics at the fingertip of every employee: from the entry-level to the executive suite. Companies have the capacity to unleash the power from within each employee by deploying business analytics. The implementation of business analytics allows companies to separate the cluster of data and clarify the driving factors.

Some companies already have the internal capacity to deploy business analytics, but lack the skills to implement a business analytics system. For example, companies that already have Microsoft SQL 2005 Server and Excel 2007 are in a position to quickly turn around a business analytics system. If you want to unleash the power from within your company contact me at Hewlett-Packard: alberto.roldan@hp.com

BI Enterprise Conceptual Architecture Solutions in the Financial Services Industry and Healthcare Industry: Microsoft SQL 2005 Server and Excel 2007

If you are a Microsoft shop and want to implement a business intelligent (BI) solution using SQL 2005 Server and Excel 2007, these are the high-level conceptual architectures for the financial services and healthcare industries. If you need any assistance in implementing these models please contact me at Hewlett-Packard: alberto.roldan@hp.com

Bernanke: Banks must get better at foreseeing risk

I have been writing about this issue since March. I have proposed a comprehensive forecasting system that can be available to everybody within a financial company, and can be deploy in three months. For more details about the business analytics model that I propose see the following articles that I have published since March 2008.
1. Financial Services Business Analytics: Evidence-Based Model
2. Three-Dimensional Business Analytics: How Deep is the Ocean?
3. Business Case for Analytics: Explaining Cluster Analysis
4. Explaining the Value of Business Analytics: Clarifying driving factors in a decision support system
5. Business Competency Model: Turning Around in a Quarter
6. Default Risk, Asset Pricing and Debt Control
7. DEVELOPING RICH INSIGHTS ON PUBLIC INTERNET FIRM ENTRY AND EXIT BASED ON SURVIVAL ANALYSIS AND DATA VISUALIZATION
8. People would rather live with a problem they cannot solve than accept a solution they cannot understand
9. The Financial Market Crisis and Risks for Latin America
10. Kaizen and Analytics: The Power of Each Employee to See Data

If you need assistance in implementing the financial services evidence-based model please contact me at Hewlett-Packard: alberto.roldan@hp.com

The Future of Business Analytics: Microsoft vs. Google

The battle over dominance of the Internet will be fought in the realm of business analytics. Microsoft and Google understand this and are investing in making their products the flagship of analytics. The reason is that analytics, like the Internet, have the potential to unleash the creative power of billions of minds.

Microsoft is depending on the combination of Excel and Analysis Services. In the business world people are used to Excel as a way explore trends. Adding the capabilities of Analysis Services allow individuals to gain insight into analytics in an incrementing manner. This is Microsoft version of kaizen analytics. Donald Farmer explains Microsoft’s vision in a recent article, Microsoft Sets Sights on Data Mining Dominance.

Google Analytics is been offered as a free software to wean people out of their Excel dependency. Google understand that Microsoft’s monopoly in Excel needs to be counteracted with a free and robust alternative. In the next few months Google will move into different industries using Google Analytics to unleash the power of the mind of billions of people. This is Google version of kaizen analytics. The users of Google product are associating the word “analytics” with Google Analytics.

Interestingly, both Google and Microsoft products have the capacity to separate or partition the data into categories or clusters. The next incremental step would be to add an automated vector analysis to clarify the driving factors in the data. I expect the competition to be head-to-head in the healthcare and Life Sciences industry in the next 12 months.

Kaizen and Analytics: The Power of Each Employee to See Data

Do companies really know how to unleash the power of employees to be the leaders in their industry? Toyota has shown a different approach to innovation, kaizen or continuous improvement approach rather than a technology leap approach. Instead of great technological breakthroughs, this approach goes for involving the entire workforce in a continuous improvement process. Hence, most of the improvements are small and process oriented (like making shelves more easily to reach) but the involvement of the entire workforce rather than a selected few keeps a vibrant and innovative enterprise. The best measurement of how this work is that the Toyota workforce gives managements one hundred times more suggestions for improvement than other auto manufacturers.

Businesses that want to improve their analytics capabilities should follow the kaizen approach and make business analytics available throughout the entire organization. It seems that in some companies analytics is only within the purview of the few like statisticians, physicians, molecular engineers, and actuaries. The concept behind this thinking is that analytics technology is expensive and difficult to interpret. This premise is no longer applicable since in the last three years mathematical science and computer technology have advanced to such a degree that this technology is now inexpensive and available to interpretation to anyone within an organization.

This technology is the work of dedicated professionals and scientist that over many years have worked to make this possible. The issue now has become whether companies want to institute a continuous improvement process that includes enterprise analytics or whether they want to leave business analytics in the hands of the few.

If you want to know how to do kaizen analytics in your company let Hewlett-Packard help you. Our Technology Services Group had over $30 billion in revenues last year, or contact me at alberto.roldan@hp.com

Financial Services Business Analytics: Evidence-Based Model

This diagram is a representation of an universal evidence-based business analytics model for the financial services industry. This model takes into account data from customers, investments, deposits, and compliance issues. It is flexible so it can adapt to any situation. It is important to notice that predictive modeling and data mining is done in a separate server than the enterprise data warehouse (EDW), otherwise it would slow the EDW to a crawl. On the other hand, this model complements business intelligence reports. This models uses regression analysis, vector analysis, and clustering (partition) analysis. It takes into consideration that data is three-dimensional (3D). It is flexible enough to add association rules and time-series analysis. The front end incorporates depth-analysis in order to leverage human-computer interaction (HCI) at the enterprise-level (i.e., anybody within the enterprise should be able to use it. It should take three months to deploy this model. If you want assistance implementing this model please contact me at Hewlett-Packard: alberto.roldan@hp.com

Evidence-based Enterprise Business Analytics Model: Turning Around in a Quarter

Companies can implement in 90 days a fixed cost and evidence-based decision making systems that would allow them to become flexible in this economic climate. Science and technology has improved to such a degree in the last three years that companies can use off-the-shelf software to do business analytics which used to be reserved to a few highly skilled professionals within an organization.

The diagram above represents an example of the architecture for an enterprise business analytics module in the healthcare and biotechnology industries. This same business analytics module can be used in any industry or company. Small and medium sized businesses can implement this business analytics architecture using an analytics-as-a-service model. Large companies can implement the same model in-house.

Three-Dimensional Business Analytics: How Deep is the Ocean?

Business data, like our universe, is three-dimensional. Nevertheless, business analytics tends to be flat or two-dimensional like an Excel table or chart. The difference between a two-dimensional analysis and a three-dimensional analysis is depth. Depth perception allows an individual to accurately determine the distance to an object. It is a characteristic mostly seen in higher species.

In analytics, depth is referred to as dimensional analysis. Dimensional analysis is used in engineering, physics, and chemistry to understand the characteristics of multi-dimensional data. It is used to formulate hypotheses about the data, which are later tested in more detail. In business analytics we can create a three-dimensional variable that allows the end-user to “see the depth” of the data. This variable is called a three-dimensional vector analysis. This variable, when combined with cluster analysis and a visualization tool, answers the proverbial business question: how deep can I go into my data and see patterns in which sound business decisions can be made?