These are in accordance with Google’s Policies http://www.google.com/intl/en/+/policy/pagesterm.html Continue reading “Creating Pages on Google Plus for some languages”
These are in accordance with Google’s Policies http://www.google.com/intl/en/+/policy/pagesterm.html Continue reading “Creating Pages on Google Plus for some languages”
I was just blown away by the price and functionality of the Kindle, including the browser and in built Wi-Fi- ( though the 40$ leather bag was a bit sneaky as an accessory, I mean seriously, dude)
And unlike some media technology companies (like Hulu,Spotify , even some Youtube channels)
who offer products to Asia only after a delayed lag, it is just as easy to order Kindle sitting from India.
Thank you Amazon!
and lastly some art to help prod those people who offer beta sites for limited countries even in this age.
Credit- Paul Mutant
One of the most frightening possibilities of cyber warfare is to use remotely deployed , or timed intrusion malware to disturb, distort, deny health care services.
A doctor in an Emergency Room depends on critical information that may save lives if it is electronic and comes on time. However this electronic information can be distorted (which is more severe than deleting it)
The electronic system of a Hospital can also be overwhelmed. If there can be built Stuxnet worms on nuclear centrifuge systems (like those by Siemens), then the widespread availability of health care systems means these can be reverse engineered for particularly vicious cyber worms.
An example of prime area for targeting is Veterans Administration for veterans of armed forces, but also cyber attacks against electronic health records.
Consider the following data points-
May 16, 2012, 9:03AM
DHS’s National Cybersecurity and Communications Integration Center (NCCIC) issued the unclassfied bulletin, “Attack Surface: Healthcare and Public Health Sector” on May 4. In it, DHS warns of a wide range of security risks, including that could expose patient data to malicious attackers, or make hospital networks and first responders subject to disruptive cyber attack
The Healthcare and Public Health (HPH) sector is a multi-trillion dollar industry employing over 13 million personnel, including approximately five million first-responders with at least some emergency medical training, three million registered nurses, and more than 800,000 physicians.
(U) A significant portion of products used in patient care and management including diagnosis and treatment are Medical Devices (MD). These MDs are designed to monitor changes to a patient’s health and may be implanted or external. The Food and Drug Administration (FDA) regulates devices from design to sale and some aspects of the relationship between manufacturers and the MDs after sale. However, the FDA cannot regulate MD use or users, which includes how they are linked to or configured within networks. Typically, modern MDs are not designed to be accessed remotely; instead they are intended to be networked at their point of use. However, the flexibility and scalability of wireless networking makes wireless access a convenient option for organizations deploying MDs within their facilities. This robust sector has led the way with medical based technology options for both patient care and data handling.
(U) The expanded use of wireless technology on the enterprise network of medical facilities and the wireless utilization of MDs opens up both new opportunities and new vulnerabilities to patients and medical facilities. Since wireless MDs are now connected to Medical information technology (IT) networks, IT networks are now remotely accessible through the MD. This may be a desirable development, but the communications security of MDs to protect against theft of medical information and malicious intrusion is now becoming a major concern. In addition, many HPH organizations are leveraging mobile technologies to enhance operations. The storage capacity, fast computing speeds, ease of use, and portability render mobile devices an optimal solution.
(U) This Bulletin highlights how the portability and remote connectivity of MDs introduce additional risk into Medical IT networks and failure to implement a robust security program will impact the organization’s ability to protect patients and their medical information from intentional and unintentional loss or damage.
(U) According to Health and Human Services (HHS), a major concern to the Healthcare and Public Health (HPH) Sector is exploitation of potential vulnerabilities of medical devices on Medical IT networks (public, private and domestic). These vulnerabilities may result in possible risks to patient safety and theft or loss of medical information due to the inadequate incorporation of IT products, patient management products and medical devices onto Medical IT Networks. Misconfigured networks or poor security practices may increase the risk of compromised medical devices. HHS states there are four factors which further complicate security resilience within a medical organization.
1. (U) There are legacy medical devices deployed prior to enactment of the Medical Device Law in 1976, that are still in use today.
2. (U) Many newer devices have undergone rigorous FDA testing procedures and come equipped with design features which facilitate their safe incorporation onto Medical IT networks. However, these secure design features may not be implemented during the deployment phase due to complexity of the technology or the lack of knowledge about the capabilities. Because the technology is so new, there may not be an authoritative understanding of how to properly secure it, leaving open the possibilities for exploitation through zero-day vulnerabilities or insecure deployment configurations. In addition, new or robust features, such as custom applications, may also mean an increased amount of third party code development which may create vulnerabilities, if not evaluated properly. Prior to enactment of the law, the FDA required minimal testing before placing on the market. It is challenging to localize and mitigate threats within this group of legacy equipment.
3. (U) In an era of budgetary restraints, healthcare facilities frequently prioritize more traditional programs and operational considerations over network security.
4. (U) Because these medical devices may contain sensitive or privacy information, system owners may be reluctant to allow manufactures access for upgrades or updates. Failure to install updates lays a foundation for increasingly ineffective threat mitigation as time passes.
(U) Implantable Medical Devices (IMD): Some medical computing devices are designed to be implanted within the body to collect, store, analyze and then act on large amounts of information. These IMDs have incorporated network communications capabilities to increase their usefulness. Legacy implanted medical devices still in use today were manufactured when security was not yet a priority. Some of these devices have older proprietary operating systems that are not vulnerable to common malware and so are not supported by newer antivirus software. However, many are vulnerable to cyber attacks by a malicious actor who can take advantage of routine software update capabilities to gain access and, thereafter, manipulate the implant.
(U) During an August 2011 Black Hat conference, a security researcher demonstrated how an outside actor can shut off or alter the settings of an insulin pump without the user’s knowledge. The demonstration was given to show the audience that the pump’s cyber vulnerabilities could lead to severe consequences. The researcher that provided the demonstration is a diabetic and personally aware of the implications of this activity. The researcher also found that a malicious actor can eavesdrop on a continuous glucose monitor’s (CGM) transmission by using an oscilloscope, but device settings could not be reprogrammed. The researcher acknowledged that he was not able to completely assume remote control or modify the programming of the CGM, but he was able to disrupt and jam the device.
February 7, 2012
February 16 2011
One high-profile healthcare system that regularly experiences such attacks is the Veterans Administration (VA). For two years, the VA has been fighting a cyber battle against illegal and unwanted intrusions into their medical devices
The computer infection started to cause problems at the Gwinnett Medical Center last Wednesday and continued to spread, until the hospital was forced to send all non-emergency admissions to other hospitals.
More doctors and nurses than ever are using mobile devices in healthcare, and hospitals are making patient records computerized for easier, convenient access over piles of paperwork.
As one of the busiest public hospitals in the western United States, LAC+USC Medical Center records nearly 39,000 inpatient discharges, 150,000 emergency department visits, and 1 million ambulatory care visits each year.
If one jumbo jet crashed in the US each day for a week, we’d expect the FAA to shut down the industry until the problem was figured out. But in our health care system, roughly 250 people die each day due to preventable error
Feb 28, 2008
“There is definitely an uptick in attacks,” says Dr. John Halamka, CIO at both Beth Israel Deaconess Medical Center and Harvard Medical School in the Boston area. “Privacy is the foundation of everything we do. We don’t want to be the TJX of healthcare.” TJX is the Framingham, Mass-based retailer which last year disclosed a massive data breach involving customer records.
Dr. Halamka, who this week announced a project in electronic health records as an online service to the 300 doctors in the Beth Israel Deaconess Physicians Organization,
Here is an interview with Dan Steinberg, Founder and President of Salford Systems (http://www.salford-systems.com/ )
Ajay- Describe your journey from academia to technology entrepreneurship. What are the key milestones or turning points that you remember.
Dan- When I was in graduate school studying econometrics at Harvard, a number of distinguished professors at Harvard (and MIT) were actively involved in substantial real world activities. Professors that I interacted with, or studied with, or whose software I used became involved in the creation of such companies as Sun Microsystems, Data Resources, Inc. or were heavily involved in business consulting through their own companies or other influential consultants. Some not involved in private sector consulting took on substantial roles in government such as membership on the President’s Council of Economic Advisors. The atmosphere was one that encouraged free movement between academia and the private sector so the idea of forming a consulting and software company was quite natural and did not seem in any way inconsistent with being devoted to the advancement of science.
Ajay- What are the latest products by Salford Systems? Any future product plans or modification to work on Big Data analytics, mobile computing and cloud computing.
Dan- Our central set of data mining technologies are CART, MARS, TreeNet, RandomForests, and PRIM, and we have always maintained feature rich logistic regression and linear regression modules. In our latest release scheduled for January 2012 we will be including a new data mining approach to linear and logistic regression allowing for the rapid processing of massive numbers of predictors (e.g., one million columns), with powerful predictor selection and coefficient shrinkage. The new methods allow not only classic techniques such as ridge and lasso regression, but also sub-lasso model sizes. Clear tradeoff diagrams between model complexity (number of predictors) and predictive accuracy allow the modeler to select an ideal balance suitable for their requirements.
The new version of our data mining suite, Salford Predictive Modeler (SPM), also includes two important extensions to the boosted tree technology at the heart of TreeNet. The first, Importance Sampled learning Ensembles (ISLE), is used for the compression of TreeNet tree ensembles. Starting with, say, a 1,000 tree ensemble, the ISLE compression might well reduce this down to 200 reweighted trees. Such compression will be valuable when models need to be executed in real time. The compression rate is always under the modeler’s control, meaning that if a deployed model may only contain, say, 30 trees, then the compression will deliver an optimal 30-tree weighted ensemble. Needless to say, compression of tree ensembles should be expected to be lossy and how much accuracy is lost when extreme compression is desired will vary from case to case. Prior to ISLE, practitioners have simply truncated the ensemble to the maximum allowable size. The new methodology will substantially outperform truncation.
The second major advance is RULEFIT, a rule extraction engine that starts with a TreeNet model and decomposes it into the most interesting and predictive rules. RULEFIT is also a tree ensemble post-processor and offers the possibility of improving on the original TreeNet predictive performance. One can think of the rule extraction as an alternative way to explain and interpret an otherwise complex multi-tree model. The rules extracted are similar conceptually to the terminal nodes of a CART tree but the various rules will not refer to mutually exclusive regions of the data.
Ajay- You have led teams that have won multiple data mining competitions. What are some of your favorite techniques or approaches to a data mining problem.
Dan- We only enter competitions involving problems for which our technology is suitable, generally, classification and regression. In these areas, we are partial to TreeNet because it is such a capable and robust learning machine. However, we always find great value in analyzing many aspects of a data set with CART, especially when we require a compact and easy to understand story about the data. CART is exceptionally well suited to the discovery of errors in data, often revealing errors created by the competition organizers themselves. More than once, our reports of data problems have been responsible for the competition organizer’s decision to issue a corrected version of the data and we have been the only group to discover the problem.
In general, tackling a data mining competition is no different than tackling any analytical challenge. You must start with a solid conceptual grasp of the problem and the actual objectives, and the nature and limitations of the data. Following that comes feature extraction, the selection of a modeling strategy (or strategies), and then extensive experimentation to learn what works best.
Ajay- I know you have created your own software. But are there other software that you use or liked to use?
Dan- For analytics we frequently test open source software to make sure that our tools will in fact deliver the superior performance we advertise. In general, if a problem clearly requires technology other than that offered by Salford, we advise clients to seek other consultants expert in that other technology.
Ajay- Your software is installed at 3500 sites including 400 universities as per http://www.salford-systems.com/company/aboutus/index.html What is the key to managing and keeping so many customers happy?
Dan- First, we have taken great pains to make our software reliable and we make every effort to avoid problems related to bugs. Our testing procedures are extensive and we have experts dedicated to stress-testing software . Second, our interface is designed to be natural, intuitive, and easy to use, so the challenges to the new user are minimized. Also, clear documentation, help files, and training videos round out how we allow the user to look after themselves. Should a client need to contact us we try to achieve 24-hour turn around on tech support issues and monitor all tech support activity to ensure timeliness, accuracy, and helpfulness of our responses. WebEx/GotoMeeting and other internet based contact permit real time interaction.
Ajay- What do you do to relax and unwind?
Dan- I am in the gym almost every day combining weight and cardio training. No matter how tired I am before the workout I always come out energized so locating a good gym during my extensive travels is a must. I am also actively learning Portuguese so I look to watch a Brazilian TV show or Portuguese dubbed movie when I have time; I almost never watch any form of video unless it is available in Portuguese.
Dan Steinberg, President and Founder of Salford Systems, is a well-respected member of the statistics and econometrics communities. In 1992, he developed the first PC-based implementation of the original CART procedure, working in concert with Leo Breiman, Richard Olshen, Charles Stone and Jerome Friedman. In addition, he has provided consulting services on a number of biomedical and market research projects, which have sparked further innovations in the CART program and methodology.
Dr. Steinberg received his Ph.D. in Economics from Harvard University, and has given full day presentations on data mining for the American Marketing Association, the Direct Marketing Association and the American Statistical Association. After earning a PhD in Econometrics at Harvard Steinberg began his professional career as a Member of the Technical Staff at Bell Labs, Murray Hill, and then as Assistant Professor of Economics at the University of California, San Diego. A book he co-authored on Classification and Regression Trees was awarded the 1999 Nikkei Quality Control Literature Prize in Japan for excellence in statistical literature promoting the improvement of industrial quality control and management.
His consulting experience at Salford Systems has included complex modeling projects for major banks worldwide, including Citibank, Chase, American Express, Credit Suisse, and has included projects in Europe, Australia, New Zealand, Malaysia, Korea, Japan and Brazil. Steinberg led the teams that won first place awards in the KDDCup 2000, and the 2002 Duke/TeraData Churn modeling competition, and the teams that won awards in the PAKDD competitions of 2006 and 2007. He has published papers in economics, econometrics, computer science journals, and contributes actively to the ongoing research and development at Salford.
Here is an interview with Eberhard Miethke and Dr. Mamdouh Refaat, of Angoss Software. Angoss is a global leader in delivering business intelligence software and predictive analytics solutions that help businesses capitalize on their data by uncovering new opportunities to increase sales and profitability and to reduce risk.
Ajay- Describe your personal journey in software. How can we guide young students to pursue more useful software development than just gaming applications.
Mamdouh- I started using computers long time ago when they were programmed using punched cards! First in Fortran, then C, later C++, and then the rest. Computers and software were viewed as technical/engineering tools, and that’s why we can still see the heavy technical orientation of command languages such as Unix shells and even in the windows Command shell. However, with the introduction of database systems and Microsoft office apps, it was clear that business will be the primary user and field of application for software. My personal trip in software started with scientific applications, then business and database systems, and finally statistical software – which you can think of it as returning to the more scientific orientation. However, with the wide acceptance of businesses of the application of statistical methods in different fields such as marketing and risk management, it is a fast growing field that in need of a lot of innovation.
Ajay – Angoss makes multiple data mining and analytics products. could you please introduce us to your product portfolio and what specific data analytics need they serve.
a- Attached please find our main product flyers for KnowledgeSTUDIO and KnowledgeSEEKER. We have a 3rd product called “strategy builder” which is an add-on to the decision tree modules. This is also described in the flyer.
Ajay- The trend in analytics is for big data and cloud computing- with hadoop enabling processing of massive data sets on scalable infrastructure. What are your plans for cloud computing, tablet based as well as mobile based computing.
a- This is an area where the plan is still being figured out in all organizations. The current explosion of data collected from mobile phones, text messages, and social websites will need radically new applications that can utilize the data from these sources. Current applications are based on the relational database paradigm designed in the 70’s through the 90’s of the 20th century.
But data sources are generating data in volumes and formats that are challenging this paradigm and will need a set of new tools and possibly programming languages to fit these needs. The cloud computing, tablet based and mobile computing (which are the same thing in my opinion, just different sizes of the device) are also two technologies that have not been explored in analytics yet.
The approach taken so far by most companies, including Angoss, is to rely on new xml-based standards to represent data structures for the particular models. In this case, it is the PMML (predictive modelling mark-up language) standard, in order to allow the interoperability between analytics applications. Standardizing on the representation of models is viewed as the first step in order to allow the implementation of these models to emerging platforms, being that the cloud or mobile, or social networking websites.
The second challenge cited above is the rapidly increasing size of the data to be analyzed. Angoss has already identified this challenge early on and is currently offering in-database analytics drivers for several database engines: Netezza, Teradata and SQL Server.
These drivers allow our analytics products to translate their routines into efficient SQL-based scripts that run in the database engine to exploit its performance as well as the powerful hardware on which it runs. Thus, instead of copying the data to a staging format for analytics, these drivers allow the data to be analyzed “in-place” within the database without moving it.
Thus offering performance, security and integrity. The performance is improved because of the use of the well tuned database engines running on powerful hardware.
Extra security is achieved by not copying the data to other platforms, which could be less secure. And finally, the integrity of the results are vastly improved by making sure that the results are always obtained by analyzing the up-to-date data residing in the database rather than an older copy of the data which could be obsolete by the time the analysis is concluded.
Ajay- What are the principal competing products to your offerings, and what makes your products special or differentiated in value to them (for each customer segment).
a- There are two major players in today’s market that we usually encounter as competitors, they are: SAS and IBM.
SAS offers a data mining workbench in the form of SAS Enterprise Miner, which is closely tied to SAS data mining methodology known as SEMMA.
On the other hand, IBM has recently acquired SPSS, which offered its Clementine data mining software. IBM has now rebranded Clementine as IBM SPSS Modeller.
In comparison to these products, our KnowledgeSTUDIO and KnowledgeSEEKER offer three main advantages: ease of use; affordability; and ease of integration into existing BI environments.
Angoss products were designed to look-and-feel-like popular Microsoft office applications. This makes the learning curve indeed very steep. Typically, an intermediate level analyst needs only 2-3 days of training to become proficient in the use of the software with all its advanced features.
Another important feature of Angoss software products is their integration with SAS/base product, and SQL-based database engines. All predictive models generated by Angoss can be automatically translated to SAS and SQL scripts. This allows the generation of scoring code for these common platforms. While the software interface simplifies all the tasks to allow business users to take advantage of the value added by predictive models, the software includes advanced options to allow experienced statisticians to fine-tune their models by adjusting all model parameters as needed.
In addition, Angoss offers a unique product called StrategyBuilder, which allows the analyst to add key performance indicators (KPI’s) to predictive models. KPI’s such as profitability, market share, and loyalty are usually required to be calculated in conjunction with any sales and marketing campaign. Therefore, StrategyBuilder was designed to integrate such KPI’s with the results of a predictive model in order to render the appropriate treatment for each customer segment. These results are all integrated into a deployment strategy that can also be translated into an execution code in SQL or SAS.
The above competitive features offered by the software products of Angoss is behind its success in serving over 4000 users from over 500 clients worldwide.
Ajay -Describe a major case study where using Angoss software helped save a big amount of revenue/costs by innovative data mining.
a-Rogers Telecommunications Inc. is one of the largest Canadian telecommunications providers, serving over 8.5 million customers and a revenue of 11.1 Billion Canadian Dollars (2009). In 2008, Rogers engaged Angoss in order to help with the problem of ballooning accounts receivable for a period of 18 months.
The problem was approached by improving the efficiency of the call centre serving the collections process by a set of predictive models. The first set of models were designed to find accounts likely to default ahead of time in order to take preventative measures. A second set of models were designed to optimize the call centre resources to focus on delinquent accounts likely to pay back most of the outstanding balance. Accounts that were identified as not likely to pack quickly were good candidates for “Early-out” treatment, by forwarding them directly to collection agencies. Angoss hosted Rogers’ data and provided on a regular interval the lists of accounts for each treatment to be deployed by the call centre dialler. As a result of this Rogers estimated an improvement of 10% of the collected sums.
Mamdouh has been active in consulting, research, and training in various areas of information technology and software development for the last 20 years. He has worked on numerous projects with major organizations in North America and Europe in the areas of data mining, business analytics, business analysis, and engineering analysis. He has held several consulting positions for solution providers including Predict AG in Basel, Switzerland, and as ANGOSS Corp. Mamdouh is the Director of Professional services for EMEA region of ANGOSS Software. Mamdouh received his PhD in engineering from the University of Toronto and his MBA from the University of Leeds, UK.
Mamdouh is the author of:
"Credit Risk Scorecards: Development and Implmentation using SAS" "Data Preparation for Data Mining Using SAS", (The Morgan Kaufmann Series in Data Management Systems) (Paperback) and co-author of "Data Mining: Know it all",Morgan Kaufmann Eberhard Miethke works as a senior sales executive for Angoss
Angoss is a global leader in delivering business intelligence software and predictive analytics to businesses looking to improve performance across sales, marketing and risk. With a suite of desktop, client-server and in-database software products and Software-as-a-Service solutions, Angoss delivers powerful approaches to turn information into actionable business decisions and competitive advantage.
Angoss software products and solutions are user-friendly and agile, making predictive analytics accessible and easy to use.
Here is an interview with Scott Gidley, CTO and co-founder of leading data quality ccompany DataFlux . DataFlux is a part of SAS Institute and in 2011 acquired Baseline Consulting besides launching the latest version of their Master Data Management product. Continue reading “Interview Scott Gidley CTO and Founder, DataFlux”
Here is an interview with Dr Ingo Mierswa , CEO of Rapid -I and Dr Simon Fischer, Head R&D. Rapid-I makes the very popular software Rapid Miner – perhaps one of the earliest leading open source software in business analytics and business intelligence. It is quite easy to use, deploy and with it’s extensions and innovations (including compatibility with R )has continued to grow tremendously through the years.
In an extensive interview Ingo and Simon talk about algorithms marketplace, extensions , big data analytics, hadoop, mobile computing and use of the graphical user interface in analytics.
Special Thanks to Nadja from Rapid I communication team for helping coordinate this interview.( Statuary Blogging Disclosure- Rapid I is a marketing partner with Decisionstats as per the terms in https://decisionstats.com/privacy-3/)
Ajay- Describe your background in science. What are the key lessons that you have learnt while as scientific researcher and what advice would you give to new students today.
Ingo: My time as researcher really was a great experience which has influenced me a lot. I have worked at the AI lab of Prof. Dr. Katharina Morik, one of the persons who brought machine learning and data mining to Europe. Katharina always believed in what we are doing, encouraged us and gave us the space for trying out new things. Funnily enough, I never managed to use my own scientific results in any real-life project so far but I consider this as a quite common gap between science and the “real world”. At Rapid-I, however, we are still heavily connected to the scientific world and try to combine the best of both worlds: solving existing problems with leading-edge technologies.
Simon: In fact, during my academic career I have not worked in the field of data mining at all. I worked on a field some of my colleagues would probably even consider boring, and that is theoretical computer science. To be precise, my research was in the intersection of game theory and network theory. During that time, I have learnt a lot of exciting things, none of which had any business use. Still, I consider that a very valuable experience. When we at Rapid-I hire people coming to us right after graduating, I don’t care whether they know the latest technology with a fancy three-letter acronym – that will be forgotten more quickly than it came. What matters is the way you approach new problems and challenges. And that is also my recommendation to new students: work on whatever you like, as long as you are passionate about it and it brings you forward.
Ajay- How is the Rapid Miner Extensions marketplace moving along. Do you think there is a scope for people to say create algorithms in a platform like R , and then offer that algorithm as an app for sale just like iTunes or Android apps.
Simon: Well, of course it is not going to be exactly like iTunes or Android apps are, because of the more business-orientated character. But in fact there is a scope for that, yes. We have talked to several developers, e.g., at our user conference RCOMM, and several people would be interested in such an opportunity. Companies using data mining software need supported software packages, not just something they downloaded from some anonymous server, and that is only possible through a platform like the new Marketplace. Besides that, the marketplace will not only host commercial extensions. It is also meant to be a platform for all the developers that want to publish their extensions to a broader community and make them accessible in a comfortable way. Of course they could just place them on their personal Web pages, but who would find them there? From the Marketplace, they are installable with a single click.
Ingo: What I like most about the new Rapid-I Marketplace is the fact that people can now get something back for their efforts. Developing a new algorithm is a lot of work, in some cases even more that developing a nice app for your mobile phone. It is completely accepted that people buy apps from a store for a couple of Dollars and I foresee the same for sharing and selling algorithms instead of apps. Right now, people can already share algorithms and extensions for free, one of the next versions will also support selling of those contributions. Let’s see what’s happening next, maybe we will add the option to sell complete RapidMiner workflows or even some data pools…
Ajay- What are the recent features in Rapid Miner that support cloud computing, mobile computing and tablets. How do you think the landscape for Big Data (over 1 Tb ) is changing and how is Rapid Miner adapting to it.
Simon: These are areas we are very active in. For instance, we have an In-Database-Mining Extension that allows the user to run their modelling algorithms directly inside the database, without ever loading the data into memory. Using analytic databases like Vectorwise or Infobright, this technology can really boost performance. Our data mining server, RapidAnalytics, already offers functionality to send analysis processes into the cloud. In addition to that, we are currently preparing a research project dealing with data mining in the cloud. A second project is targeted towards the other aspect you mention: the use of mobile devices. This is certainly a growing market, of course not for designing and running analyses, but for inspecting reports and results. But even that is tricky: When you have a large screen you can display fancy and comprehensive interactive dashboards with drill downs and the like. On a mobile device, that does not work, so you must bring your reports and visualizations very much to the point. And this is precisely what data mining can do – and what is hard to do for classical BI.
Ingo: Then there is Radoop, which you may have heard of. It uses the Apache Hadoop framework for large-scale distributed computing to execute RapidMiner processes in the cloud. Radoop has been presented at this year’s RCOMM and people are really excited about the combination of RapidMiner with Hadoop and the scalability this brings.
Ajay- Describe the Rapid Miner analytics certification program and what steps are you taking to partner with academic universities.
Ingo: The Rapid-I Certification Program was created to recognize professional users of RapidMiner or RapidAnalytics. The idea is that certified users have demonstrated a deep understanding of the data analysis software solutions provided by Rapid-I and how they are used in data analysis projects. Taking part in the Rapid-I Certification Program offers a lot of benefits for IT professionals as well as for employers: professionals can demonstrate their skills and employers can make sure that they hire qualified professionals. We started our certification program only about 6 months ago and until now about 100 professionals have been certified so far.
Simon: During our annual user conference, the RCOMM, we have plenty of opportunities to talk to people from academia. We’re also present at other conferences, e.g. at ECML/PKDD, and we are sponsoring data mining challenges and grants. We maintain strong ties with several universities all over Europe and the world, which is something that I would not want to miss. We are also cooperating with institutes like the ITB in Dublin during their training programmes, e.g. by giving lectures, etc. Also, we are leading or participating in several national or EU-funded research projects, so we are still close to academia. And we offer an academic discount on all our products 🙂
Ajay- Describe the global efforts in making Rapid Miner a truly international software including spread of developers, clients and employees.
Simon: Our clients already are very international. We have a partner network in America, Asia, and Australia, and, while I am responding to these questions, we have a training course in the US. Developers working on the core of RapidMiner and RapidAnalytics, however, are likely to stay in Germany for the foreseeable future. We need specialists for that, and it would be pointless to spread the development team over the globe. That is also owed to the agile philosophy that we are following.
Ingo: Simon is right, Rapid-I already is acting on an international level. Rapid-I now has more than 300 customers from 39 countries in the world which is a great result for a young company like ours. We are of course very strong in Germany and also the rest of Europe, but also concentrate on more countries by means of our very successful partner network. Rapid-I continues to build this partner network and to recruit dynamic and knowledgeable partners and in the future. However, extending and acting globally is definitely part of our strategic roadmap.
Dr. Ingo Mierswa is working as Chief Executive Officer (CEO) of Rapid-I. He has several years of experience in project management, human resources management, consulting, and leadership including eight years of coordinating and leading the multi-national RapidMiner developer team with about 30 developers and contributors world-wide. He wrote his Phd titled “Non-Convex and Multi-Objective Optimization for Numerical Feature Engineering and Data Mining” at the University of Dortmund under the supervision of Prof. Morik.
Dr. Simon Fischer is heading the research & development at Rapid-I. His interests include game theory and networks, the theory of evolutionary algorithms (e.g. on the Ising model), and theoretical and practical aspects of data mining. He wrote his PhD in Aachen where he worked in the project “Design and Analysis of Self-Regulating Protocols for Spectrum Assignment” within the excellence cluster UMIC. Before, he was working on the vtraffic project within the DFG Programme 1126 “Algorithms for large and complex networks”.
http://rapid-i.com/content/view/181/190/ tells you more on the various types of Rapid Miner licensing for enterprise, individual and developer versions.
(Note from Ajay- to receive an early edition invite to Radoop, click here http://radoop.eu/z1sxe)