PFI - Personal Finance Intelligence

This research work will be published in IJSER (International Journal of Sceince and Engineering Research), 8 August Edition 2012. Part of the research paper wil be posted here:<br /><br />ELegant Analytics - ELA presents<br /><br /><strong>Personal Finance Intelligence</strong><br /><br />(First part)<br /><br />Introduction<br /><br />Medical doctors always say that the best medicine is the preventive one and research shows that humans work very little on this direction. The subject of this research is not Medicine, but not less important, Economy.<br />Financial crisis happened before, is happening now and will happen in future if we do not create a preventive plan. One of the solutions that aim to be part of a “preventive medicine” for financial crises is produced in the data laboratories of ELA (ELegant Analytics) and its name is PFI.<br /><br /><br />What is PFI?<br /><br />Personal Finance Intelligence (PFI) represents the name of the Business Intelligence solution for personal finance and planning of your budget. Inspired by the TV Show “Luksusfellen” (A show broadcasted in Norway about people struggling with their economy and living luxurious live-“Luxurious buddy”.), this Business Intelligence approach may be a solution for all these who fail to maintain well their own economy, for those who want to perform their economy and last but not least the bank itself. <br />The purpose of this project is to create a Customer Analytical Cube that would process data for each bank costumer using his/her history for its own benefit and then queries back with the most important answers that customers and the bank itself need.<br />This solution will include also benchmarking against an Imaginary subject that can be Min, Max or Avg of the customer’s values in a set that can be certain region, for a period of time, age group, sex, income ranges etc. <br />For having more control and planning your own economy, targeting will be an option when users (bank customers) can put their targets for costs or income a month, a quarter or a year ahead and always will be warned when they are about to achieve the costs amount targeted.<br />Project is also meant to be use for the bank itself in cases when they want to evaluate a customer and his/her behave regarding his/her finance stability, because today Credit scoring system lack for some important data that can make decision more accurate. The customer behave will be same important for the bank, so the bank will know what type of customer is and how he/she handle his/her economy.<br /><br /><br />Focus and goals<br /><br />The main focus of this project is the customer, his/her history and his/her behave. <br />Our first goal is to make possible data collection for customers in the smallest transaction granularity as possible by not impersonating data. This way, bank operates with the whole data diving into details secure and lawfully. Our second goal is by doing Business Intelligence with his historical data to give alerts and advices where he/she is performing bad or giving support where he/she is doing well.<br />Our third goal is to see where the customer stands, comparing with the region where he/she lives, comparing with his age group, sex and income. This is going to help him improve savings and cut costs by showing how people around him can do with same budget.<br />Our fourth, but not less important goal is related to the bank itself, where the bank can have clear financial picture for its customer and can decide much better than credit scoring system.<br />This system lowers the risk and improves the loyalty with customers.<br /><br /><br /><br />Project Highlights:<br /><br />Data center that has the capacity to <br />• Data transfer once a day or live-data (for the bank side)<br />• Centralized Customer Intelligence for the Entire Bank<br />• Live Data transfer and access<br />• Separate service for each client<br />• Client vs. Average, Max or Min of a set of clients (Benchmarking)<br />• Other Intelligence analysis (Geography, age, sex etc…)<br /><br />Processes on the fly (Administration and Maintenance): <br />• Optimizing ETL<br />• Optimizing DB and DWH<br />• Optimizing Indexing and Data Volume<br />• Query Performance regarding MDX calculated measures<br /><br /><br />Project Closure Recommendations<br /><br />It is very recommended that privacy and security issues regarding credential information about customers to be distributed in a high consideration.<br />Also users’ impersonation with data source and data reported is highly recommended to be solved in the best possible way, including data source security till Cube role group’s security.<br />Other recommendation is regarding planning the data volume and performance upon queries requests in a large volume of data in production environment.<br /><br /><br />Data Architecture of the PFI Solution<br /><br /><div style="border: currentColor;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhbKEhaTvdirl9Zt677nCkf5wXOhgrUaTeqskEEoq2Kj2prr8lKVlcR7qV8YNNwPSO7YsJTwnFjx9xIc9uRadEIfXaJZpAzb8xRpfvLEpaBHPdY_KvbNBdvTOYoMlW4QomZRLf53nsHPBEM/s1600/BI+Stack.gif" imageanchor="1" style="clear: left; cssfloat: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" height="226" sda="true" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhbKEhaTvdirl9Zt677nCkf5wXOhgrUaTeqskEEoq2Kj2prr8lKVlcR7qV8YNNwPSO7YsJTwnFjx9xIc9uRadEIfXaJZpAzb8xRpfvLEpaBHPdY_KvbNBdvTOYoMlW4QomZRLf53nsHPBEM/s320/BI+Stack.gif" width="320" /></a>Database is the main source of data and is usually an accumulator of data entry and daily transactions (manually or automatized). In our case, this Customer DB is the main data source for bank costumer data and for the solution itself. Usually is made by tables that have different information and transaction data. The problem with it is that DB has raw data and is not organized, calibrated and optimized for the need of business. So, from the database we create or transform a Data warehouse.</div><br /><br /><br />* If you want to download the full research just click <a href="http://www.ijser.org/onlineResearchPaperViewer.aspx?Elegant-Solutions-Personal-Finance-Intelligence.pdf" rel="nofollow" target="_blank">here</a>.<br /><br /><br />

PFI - Personal Finance Intelligence

This research work will be published in IJSER (International Journal of Sceince and Engineering Research), 8 August Edition 2012. Part of th...

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The Future of Decision Making: Less Intuition, More Evidence

<br /><br />A fantastic post by <strong>Andrew McAfee </strong><br /><br />Human intuition can be astonishingly good, especially after it's improved by experience. Savvy poker players are so good at reading their opponents' cards and bluffs that they seem to have x-ray vision. Firefighters can, under extreme duress, anticipate how flames will spread through a building. And nurses in neonatal ICUs can tell if a baby has a dangerous infection even before blood test results come back from the lab.<br /><br />The lexicon to describe this phenomenon is mostly mystical in nature. Poker players have a sixth sense; firefighters feel the blaze's intentions; Nurses just know what seems like an infection. They can't even tell us what data and cues they use to make their excellent judgments; their intuition springs from a deep place that can't be easily examined. . Examples like these give many people the impression that human intuition is generally reliable, and that we should rely more on the decisions and predictions that come to us in the blink of an eye.<br /><br />This is deeply misguided advice. We should rely less, not more, on intuition.<br /><br />A huge body of research has clarified much about how intuition works, and how it doesn't. Here's some of what we've learned:<br /><br />•It takes a long time to build good intuition. Chess players, for example, need 10 years of dedicated study and competition to assemble a sufficient mental repertoire of board patterns.<br /><br />•Intuition only works well in specific environments, ones that provide a person with good cues and rapid feedback . Cues are accurate indications about what's going to happen next. They exist in poker and firefighting, but not in, say, stock markets. Despite what chartists think, it's impossible to build good intuition about future market moves because no publicly available information provides good cues about later stock movements. Feedback from the environment is information about what worked and what didn't. It exists in neonatal ICUs because babies stay there for a while. It's hard, though, to build medical intuition about conditions that change after the patient has left the care environment, since there's no feedback loop.<br /><br />•We apply intuition inconsistently. Even experts are inconsistent. One study determined what criteria clinical psychologists used to diagnose their patients, and then created simple models based on these criteria. Then, the researchers presented the doctors with new patients to diagnose and also diagnosed those new patients with their models. The models did a better job diagnosing the new cases than did the humans whose knowledge was used to build them. The best explanation for this is that people applied what they knew inconsistently — their intuition varied. Models, though, don't have intuition.<br /><br />•It's easy to make bad judgments quickly. We have a many biases that lead us astray when making assessments. Here's just one example. If I ask a group of people "Is the average price of German cars more or less than $100,000?" and then ask them to estimate the average price of German cars, they'll "anchor" around BMWs and other high-end makes when estimating. If I ask a parallel group the same two questions but say "more or less than $30,000" instead, they'll anchor around VWs and give a much lower estimate. How much lower? About $35,000 on average, or half the difference in the two anchor prices. How information is presented affects what we think.<br /><br />•We can't know tell where our ideas come from. There's no way for even an experienced person to know if a spontaneous idea is the result of legitimate expert intuition or of a pernicious bias. In other words, we have lousy intuition about our intuition.<br /><br />My conclusion from all of this research and much more I've looked at is that intuition is similar to what I think of Tom Cruise's acting ability: real, but vastly overrated and deployed far too often.<br /><br />So can we do better? Do we have an alternative to relying on human intuition, especially in complicated situations where there are a lot of factors at play? Sure. We have a large toolkit of statistical techniques designed to find patterns in masses of data (even big masses of messy data), and to deliver best guesses about cause-and-effect relationships. No responsible statistician would say that these techniques are perfect or guaranteed to work, but they're pretty good.<br /><br />The arsenal of statistical techniques can be applied to almost any setting, including wine evaluation. Princeton economist Orley Ashenfleter predicts Bordeaux wine quality (and hence eventual price) using a model he developed that takes into account winter and harvest rainfall and growing season temperature. Massively influential wine critic Robert Parker has called Ashenfleter an "absolute total sham" and his approach "so absurd as to be laughable." But as Ian Ayres recounts in his great book Supercrunchers, Ashenfelter was right and Parker wrong about the '86 vintage, and the way-out-on-a-limb predictions Ashenfelter made about the sublime quality of the '89 and '90 wines turned out to be spot on.<br /><br />Those of us who aren't wine snobs or speculators probably don't care too much about the prices of first-growth Bordeaux, but most of us would benefit from accurate predictions about such things as academic performance in college; diagnoses of throat infections and gastrointestinal disorders; occupational choice; and whether or not someone is going to stay in a job, become a juvenile delinquent, or commit suicide.<br /><br />I chose those seemingly random topics because they're ones where statistically-based algorithms have demonstrated at least a 17 percent advantage over the judgments of human experts.<br /><br />But aren't there at least as many areas where the humans beat the algorithms? Apparently not. A 2000 paper surveyed 136 studies in which human judgment was compared to algorithmic prediction. Sixty-five of the studies found no real difference between the two, and 63 found that the equation performed significantly better than the person. Only eight of the studies found that people were significantly better predictors of the task at hand. If you're keeping score, that's just under a 6% win rate for the people and their intuition, and a 46% rate of clear losses.<br /><br />So why do we continue to place so much stock in intuition and expert judgment? I ask this question in all seriousness. Overall, we get inferior decisions and outcomes in crucial situations when we rely on human judgment and intuition instead of on hard, cold, boring data and math. This may be an uncomfortable conclusion, especially for today's intuitive experts, but so what? I can't think of a good reason for putting their interests over the interests of patients, customers, shareholders, and others affected by their judgments.<br /><br />So do we just dispense with the human experts altogether, or take away all their discretion and tell them to do whatever the computer says? In a few situations, this is exactly what's been done. For most of us, our credit scores are an excellent predictor of whether we'll pay back a loan, and banks have long relied on them to make automated yes/no decisions about offering credit. (The sub-prime mortgage meltdown stemmed in part from the fact that lenders started ignoring or downplaying credit scores in their desire to keep the money flowing. This wasn't intuition as much as rank greed, but it shows another important aspect of relying on algorithms: They're not greedy, either).<br /><br />In most cases, though, it's not feasible or smart to take people out of the decision-making loop entirely. When this is the case, a wise move is to follow the trail being blazed by practitioners of evidence-based medicine , and to place human decision makers in the middle of a computer-mediated process that presents an initial answer or decision generated from the best available data and knowledge. In many cases, this answer will be computer generated and statistically based. It gives the expert involved the opportunity to override the default decision. It monitors how often overrides occur, and why. it feeds back data on override frequency to both the experts and their bosses. It monitors outcomes/results of the decision (if possible) so that both algorithms and intuition can be improved.<br /><br />Over time, we'll get more data, more powerful computers, and better predictive algorithms. We'll also do better at helping group-level (as opposed to individual) decision making, since many organizations require consensus for important decisions. This means that the 'market share' of computer automated or mediated decisions should go up, and intuition's market share should go down. We can feel sorry for the human experts whose roles will be diminished as this happens. I'm more inclined, however, to feel sorry for the people on the receiving end of today's intuitive decisions and judgments.<br /><br />What do you think? Am I being too hard on intuitive decision making, or not hard enough? Can experts and algorithms learn to get along? Have you seen cases where they're doing so? Leave a comment, please, and let us know.<br /><br /><br /><br />

The Future of Decision Making: Less Intuition, More Evidence

A fantastic post by Andrew McAfee Human intuition can be astonishingly good, especially after it's improved by experience. Savvy poker p...

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Ten steps to predictive success

Follow these best practices to ensure a successful foray into predictive analytics.<br /><br /><br />1. Define the business proposition. What is the business problem you are trying to solve? What is the question you're trying to answer? Think like a business leader first and an analyst or IT expert second. <br /><br />2. Line up a business champion. Having the support of a key executive and a stakeholder is crucial. Whenever possible help the stakeholder to become the initiator and champion of the project. <br /><br />3. Start off with a quick win. Find a well-defined business problem where analytics can bring value by showing measurable results. Start small and use simple models to build credibility.<br /><br />4. Know the data you have. Do you have enough data, enough history and enough granularity in the data to feed your proposed model? Getting it into the right form is the biggest part of any first-time predictive analytics project.<br /><br />5. Get professional help. A statistical background and a little training aren't enough: Creating predictive models is different from traditional descriptive analytics, and is as much an art as it is a science. Get help for that first win before striking out on your own. <br /><br />6. Be sure the decision maker is prepared to act. It's not enough to have a prescribed action plan. The results may dictate actions that are counterintuitive. If the business decision makers won't act or aren't in a position do so, you re wasting your time, so get a strong commitment up front. <br /><br />7. Don't get ahead of yourself. Stay within the scope of the defined project, even if success breeds pressure to expand the use of your current model. Good analytics sells itself, but overextending can result in an unreliable model that will kill credibility.<br /><br />8. Communicate the results in business language. Don't discuss probabilities and variances. Do talk revenue impact and fulfillment of business objectives. Use data visualization tools to hammer home the point.<br /><br />9. Test, revise, repeat. Start small, test, revise and test again. Conduct A/B testing to demonstrate value. Present the results, gain critical mass, then scale out. <br /><br />10. Hire me to implemment above steps with success :)<br /><br />

Ten steps to predictive success

Follow these best practices to ensure a successful foray into predictive analytics. 1. Define the business proposition. What is the business...

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Bankers call for advanced analytics

Technology officials in banking industry are deeply interested in the future of business intelligence, specifically predictive analytics processes that can analyze customer behavior. A recent Computing report found that financial officials are able to draw deeper analysis than retailers. Both bankers and store owners are interested in creating conditions that could leave customers feeling free to spend, with banks eager to drive customer dollars to their own line of payment cards. <br /><br /><br />Targeted offers<br /><br />As Computing pointed out, banks have access to an important and unique data source for analytics - transaction data from customers' credit cards. Each use of a credit card contains a wealth of information - where it was used, what type of merchant made the sale. Companies can combine these data points to create a picture of customer interests and allow them to create an environment the encourages further spending and incentives that cardholders will want.<br />"The data is broader than a retailer would get, so it can go very deep and build meaningful profiles of customers. They can then ask, 'Six months ago, this individual was shopping at John Lewis and now they're shopping in Primark. What does that tell me?'" analytics officer Andrew Jennings told the source. "Banks are not very good at this, but the competitive environment is driving them towards [being good at it]. That's what we're seeing today."<br />According to Computing, Jennings also stated that while banks have depth of data that cannot be matched by individual merchants, the stores are more experienced actually creating analytics models. He mentioned that there is room for alliances between stores and card providers. Banks can agree to give retailers payments for each transaction placed on that institution's payment cards. Financial institutions can also create programs that give rewards directly to customers if they spend at certain allied merchants.<br /><br /><br /><br />Unique skillsets<br /><br />TechTarget recently examined efforts by companies to take predictive information from their data. The source consulted with strategic analytics expert Jennifer Golec, who described the ideal analyst's role as threefold - programmer, data scientist and storyteller. They must have programming know-how to deal with the complex and large data sets needed to make a predictive model. The data science will come in handy when developing processes that employ multiple variables. The storytelling flair will help analytics teams explain their findings in clear, business-focused terms to the rest of the company.<br /><br /><b>P.S.</b><br /><br /><b>Soon is comming post about a Business Intelligence solution focusing bank customers and their behaviour. I applied at the DnBNOR innovation price, but was ignored in 2009, maybe because BI analytics was not that actual then. STAY TUNED!</b><br /><br /><br />

Bankers call for advanced analytics

Technology officials in banking industry are deeply interested in the future of business intelligence, specifically predictive analytics pro...

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Time to Invest: Predicting What’s Next for Technology in Hospitality

Time to Invest: Predicting What’s Next for Technology in Hospitality <br /><br /><br />3/1/2012 <br /><br />Douglas C. Rice <br /><br /><br />One of the biggest challenges for any technology executive is predicting the landscape of toolsets and IT infrastructure that will be available in the future. If you make the right choice, today’s investments may last for 10 or even 20 years. In contrast, the wrong choice could force you to replace core elements of your systems strategy in half that time, or less.<br /><br />The hospitality industry is largely a consumer of these building blocks, which include such things as network protocols (think TCP/IP), materials (silicon, copper, fiber), data protocols (SQL, ODBC), operating systems (Linux, Windows, iOS, Android), and presentation and messaging protocols (HTML, SOAP). These are not developed for hospitality; rather they serve a wide variety of consumer and business needs. The building blocks just referenced are familiar names in the industry now, but how can you determine what the building blocks of the future will be? <br />One of the best lessons I learned from a wise person many years ago was that if you want to predict the future, find out where the big money is being invested. In technology, this means learning where the industry giants are investing their billions in research and development (R&D) – companies like Microsoft, Intel, Apple®, Cisco, Google, Oracle, IBM and AT&T, to name just a few. When many of them invest in the same building blocks, you can count on those building blocks becoming mainstream and supportable for many years to come. If you were watching these barometers, you foresaw the end of the mainframe era. You also saw the Internet coming years before the dot-com boom began, and you anticipated the mobile app revolution.<br /><br /><br /><br />A Window to the Future<br /><br />One of the great privileges I enjoy from the vantage of running on of the hotel technology industry’s largest trade associations is frequent opportunities to see the world from the vantage point of many different industry technology leaders, including those that focus on hospitality, as well as those serving the broader technology space. HTNG’s regular face-to-face meetings of industry technology leaders offer great insights into where technology industry leaders expect to go in coming years, and how hospitality technology providers view those trends. These insights provide clues as to which investments will be future proof and which will be risks.<br /><br />The Cloud <br /><br />Despite that no one really even agrees on the meaning of the word, there is no question that the cloud is by far the biggest area of investment. Microsoft, Amazon, Force.com, Apple, and now even networking companies like Cisco are placing huge bets on moving complexity and cost up the wire, away from the user and into data centers where they can benefit from scalability, shared support resources and load balancing. You can argue that much of the money being spent is on marketing hype rather than technology, and there is undoubtedly some truth to that point of view. But these companies would not spend money on marketing if they didn’t expect sales, which means they expect to deliver product. We are only in the early days of the cloud revolution currently, but the amount of money these companies are spending ensures that it will catch on. <br />One of the most important aspects of this, from a hospitality perspective, is the development of cloud service brokerages. In an industry where the dozens of different systems controlling a hotel must be mashed together from different parties – at a minimum this includes the building owner, the management company and the franchisor – if services are going to be cloud based, there must be cloud-level interoperability. Brokerage services can be thought of as cloud-based middleware that ensure robust and reliable communication between cloud-based systems operating in different clouds. They are what will enable a cloud-based CRS running in the Force.com cloud, for example, to easily connect with a cloud-based PMS running on Microsoft Azure. They can also allow a hotel company to engage a single vendor to manage the aggregation, integration, customization and governance of cloud services. Intel is one of many companies making big investments in the cloud services brokerage arena, which by definition are independent of any single cloud services provider.<br />This is good news for hospitality. It holds the promise of relieving the hotel owner of responsibility for managing the operation and integration of premise-based systems, with associated costs for deployment, equipment and maintenance performed by on-site or locally based staff. There is a healthy debate as to which technology services must remain premise based to avoid major problems in the event of network outages. But the number of hotel technologies that are proving to be robust in cloud deployments – at least in parts of the world with good Internet access – are growing every year as obstacles are overcome. There is a distinct possibility that every aspect of hotel technology except for end-user devices and portions of the network infrastructure may ultimately move to the cloud.<br /><br /><br /><br />Mobility<br /><br />Turning from infrastructure to hardware, it’s hard to deny that the big money is moving to mobility. Apple may have been the first of the megacompanies to figure this out –arguably, they became a megacompany by doing so – but other giants like Samsung, Microsoft and Amazon have also been leading the charge. Tablets have not yet fully replaced PCs in business travel, but the gap is narrowing rapidly. Indeed, the form factor of notebooks is getting smaller as that of tablets gets larger. We are fast approaching the day when the difference between the two is the presence or absence of a paper-thin keyboard.<br /><br />For hospitality, this creates both opportunity and challenge. Mobility gives us the ability to communicate with our guests and staff in real time. This capability can be used to both define new service models and revenue streams, and to improve existing ones. Today’s challenge is that mobility requires massive investment in wireless infrastructure and bandwidth. (More about that challenge in the third trend.)<br /><br />The key takeaway for hospitality is that when you invest in user interfaces, it will typically be wise to design for mobile devices first, rather than for PCs. Certainly this is true for applications that face guests, but also for staff-facing applications where the staff is or could benefit from being mobile. This includes a large proportion of front-of-house, back-of-house and guest-facing hospitality applications.<br /><br />Don’t bet on a particular operating system, the leadership in this area will change based on competitive dynamics outside the control of anyone in hospitality. Multiplatform toolsets such as HTML5 are widely supported and are becoming de facto standards for deployment of applications across multiple platforms. While not yet perfected in all environments, it’s the clear winner in overall investment by mobile operating system and device manufacturers.<br /><br /><br /><br />Cellular Offload<br /><br />Mobile devices create the need for massive bandwidth. iBAHN collects extensive data on these trends, which it has generously shared with the industry, and the data is downright scary: bandwidth requirements are roughly doubling every year, with mobile devices leading the way. <br /><br />Many hotels have shortchanged the investment in upgrading bandwidth and supporting Wi-Fi infrastructure, believing that the migration of mobile devices to 4G/LTE cellular technologies will solve the problem by ultimately reducing or eliminating Wi-Fi. But a look at where the megacarriers are investing proves this assumption completely false. <br /><br />Carriers such as AT&T, Verizon and Sprint realized in 2007 to 2008 that the data tsunami was coming, and there was simply not enough cellular radio spectrum for them to outrun it, even given future advances in cellular technology through LTE and beyond. Carriers such as these and their counterparts in other countries know they cannot satisfy the demand for mobile data with cellular technologies, at least not in densely populated areas. Their strategies for satisfying the need are based on moving cellular traffic to terrestrial networks – meaning Wi-Fi. Virtually all major carriers in developed countries are aggressively investing in what they call offload, meaning they are building out or gaining access to Wi-Fi networks, and enabling their devices to roam onto these networks automatically. If you have an AT&T smartphone and leave wireless enabled, and walk into a Starbucks, McDonalds, American Airlines Club room or Hilton-branded U.S. hotel, you have probably already experienced this. These few examples exemplify the economics: in congested areas, it is far cheaper for a cellular carrier to build or fund a Wi-Fi network, than to install an additional cell tower and/or buy additional spectrum.<br /><br />This is good news for hotels, because it means that cellular companies have an economic reason to help fund hotel Wi-Fi networks. In New York and San Francisco, where cellular coverage is saturated, some carriers have gone so far as to offer free Wi-Fi networks to certain hotels, because it was the least expensive option for them to satisfy the needs of their customers. Hotels in less congested areas won’t get free Wi-Fi networks anytime soon, but many hotels can now find, at a minimum, willing investment partners to help offset the cost of a Wi-Fi network in return for the ability to route cellular traffic through it. In remote areas, the cellular network may be sufficient to meet consumer needs. Urban and suburban hotels are well positioned to benefit from this trend, but will need to forge appropriate alliances with carriers to do so. Over time, carriers expect roaming models to develop, enabling phones from different carriers to offload to a single Wi-Fi network, with payments to the provider of that network based on traffic volumes or other factors. <br /><br />There are many risky bets in technology, but a few safe ones. When you are making decisions on investments, strive to determine the major trends, and then invest in solutions that align with those trends. If you aren’t looking at the cloud, expecting the user interface to migrate to mobile devices, or thinking about how your hotel can benefit from carrier investments in Wi-Fi, you’re probably missing the boat.<br /><br /><br /><br />Douglas C. Rice is the executive vice president and CEO of Hotel Technology Next Generation. <br /><br /><br /><br /><br /><br /><br /><br />www.htng.org <br /><br />

Time to Invest: Predicting What’s Next for Technology in Hospitality

Time to Invest: Predicting What’s Next for Technology in Hospitality 3/1/2012 Douglas C. Rice One of the biggest challenges for any technolo...

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The future of Technology

After some serious posts it is time to laugh a bit. Parody for Apple technology can make your day:<br /><br /><iframe allowfullscreen="" frameborder="0" height="360" src="http://www.youtube.com/embed/17DPJHNVx2Q" width="640"></iframe>

The future of Technology

After some serious posts it is time to laugh a bit. Parody for Apple technology can make your day:

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<strong><span style="font-size: large;">Top 5 Certifications ranked based on market request</span></strong><br /><br />When the conversation amongst IT professionals turns to IT Certifications, one of their first thoughts is of high salaries – different money signs dancing in their heads. While some certifications do command a six-figure salary, this is not true for all. With the recent completion of our annual IT Skills and Salary report, I thought it would be a great time to look at some of the more popular certifications – and their associated pay.<br /><br />Note: The rankings below are based on certifications that received the minimum 200 responses required to derive a salary figure that is statically accurate. There are certifications that pay more that are not represented due to their exclusive nature. These include CCIE: Cisco Certified Internetworking Expert and VCDX: VMware Certified Design Expert, for example.<br /><br />1. PMP® - Project Management Professional – ($111,209)<br /><br />The Project Management Institute’s (PMI) Project Management Professional (PMP) credential is recognized as the most important certification for project managers and is globally recognized and in heavy demand. The PMP credential demonstrates that you not only have the requisite, real-world experience, but that you also have the education to successfully lead and direct projects. The PMP credential should only be attempted by experiencedproject managers as the qualifications and testing for this certification are very rigorous. In addition, the PMI requires continued validation through required continuing education requirements. All of these factors ensure<br />that the PMP credential is widely respected. The PMP experience and exam requirements focus on five process groups: Initiating, Planning, Executing, Controlling, and Closing.<br /><br />2. CISSP® - Certified Information Systems Security Professional - $110,342<br /><br />The Certified Information Systems Security Professional (CISSP) credential is for security managers and professionals who develop policies and procedures in information security. The CISSP certification has become the gold standard in information security certifications. Earning and maintaining a CISSP certification is required for many governmental, military, and civilian security positions. The CISSP was the first credential in the field of information security, accredited by the ANSI (American National Standards Institute) to ISO (International Organization for Standardization) Standard 17024:2003. Earning your CISSP certification is not only an objective measure of excellence, but it is a globally recognized standard of achievement.<br /><br />3. CCDA® - Cisco Certified Design Associate - $101,915<br /><br />The Cisco Certified Design Associate (CCDA) demonstrates that the individual who has passed the required exams has the requisite knowledge, experience, and understanding required to design a Cisco converged network.<br />A CCDA-certified individual has the skills to design a routed and switched network infrastructure and services involving LAN, WAN, and broadband access for businesses and organizations.<br /><br />4. ITIL® v3 Foundation – ($97,691)<br /><br />What is this ITIL that we hear so much about? The Information Technology Infrastructure Library (ITILv3) is a foundational process that provides for quality IT Service Management. The success of ITIL is through the use of documented and proven processes that cover the entire Service Lifecycle. The ITIL Expert level is the third of four levels. The ITIL Expert level certification is aimed at those individuals who are interested in demonstrating a superior level of knowledge of ITIL Version 3 (v3) in its entirety. Once you have achieved ITIL Expert level, you will also satisfy the pre-requisite entry criteria for the ITIL Master Level. This is the highest level of certification within the ITIL v3 scheme, though the Master level is still under development<br /><br />5. MCSE - Microsoft Certified Systems Engineer - $91,650<br /><br />The Microsoft Certified Systems Engineer (MCSE) certification ended with Server 2003, though you can still earn it (as well as the MCSE on Server 2000, though many of the tests are retired). The continued use of Windows Server 2003 in the market suggests that the demand for related expertise will continue for some time. The MCSE certification demonstrates to clients and employers that you are skilled in designing, implementing, and administering infrastructures for business solutions based on Windows Server 2003 and Microsoft Windows 2000<br />Server. Implementation responsibilities include installing, configuring, and troubleshooting network systems. In order for you to earn your MCSE on Windows Server 2003 certification (or Windows 2000 Server), you must pass seven exams: four exams on networking systems, one exam on client operating systems, one exam on design, and one elective exam. One thing to be aware of is that many of the exams are retired or will be retiring soon. If one of the required exams is retired and you have not passed the exam, then you cannot earn the certification.<br />If you have passed the exam before it retired, than it still can be applied to the certification.

Top 5 Certifications ranked based on market request When the conversation amongst IT professionals turns to IT Certifications, one of their ...

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