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About Aisha Javed

Blogger & Online Community Manager at Xorlogics with an excellent familiarity with various Internet resources, expresses a keen desire to learn/excel on Web Marketing for the benefit of the organization.

#DigitalTransformation: No Future Without a Functional Website

From the butcher around the corner to the largest multinationals in the world, about every company is actively present on the internet via a website and that has become absolutely necessary. It’s just logical reasoning as the customers spend more and more time on the internet, via multiple devices, it’s normal to be online as a business.

And only being present is not enough. A site is a lot more than just a business card today. It has become a full communication channel. And consumers expect you to be as accessible via the site as via the phone. And of course, it is also a graphic and semantic reflection of your company. The kind of site you have, the pictures that are on it and the language already tells others very much about the type of business you are.

 

Customers are more and more on the internet, it’s only logical that you should be there as a business

 

 

Daily task

As an online business, you don’t want to confuse quality with quantity. Don’t spend your time on easy and low impact tasks instead of strategic one’s, especially when your website is your only sales channel. Even if you opt to work with a specialized IT company, keeping the site running is a full day job. In some cases, only the deep adaptations to the site and the performance take specialists into account. But keeping up-to-date with information, uploading photos of products, keeping track of payments, ensure that all descriptions and prices are correct and the overall look is an in-house task.

 

Basic conditions

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Handling a running website isn’t as easy as counting one-two-three. Because of the requirements of a good website, there are some basic conditions. You need to make sure that your website’s graphic don’t confuse visitor and make him leave your page. That means finding immediately what customers looking for and not losing too much time with pop-ups and such notifications. Even the language selection must be automate as much as possible based on user history. Also, a call to action (“call us” or “push here for a chat conversation”.) must be functional. All deeper content may be further in the site.

 

Classic

Just like in clothing, there are trends and modes in website design. Long scrolling home pages are the best example. Be sure that if a visitor has to scroll a lot, it must be for a good reason.

At the top of the page a functional basic menu and at the bottom of it user must get credentials or customer testimonials. Be very economical with too many colors, striking fonts or bold layouts. And there are good reasons why you do not often see that kind of thing: it draws attention to the essence, it makes reading the site just harder and it looks very unprofessional. As far as reading is concerned, too long text on a webpage are too heavy. You limit yourself to a handful of paragraphs per page. If you have to explain difficult things, for example, if you want to propose a particular policy as an insurance company, you can make a synthesis on the homepage and click your visitors to the full text. Whether you provide a separate PDF that they can download and print.

There is nothing above a classic, quiet layout. May be in 1998 you could get away with all those flashy conditions, not any more.

 

Responsive design

ResponsiveDesign

Another thing to keep in mind is that more internet surfers are not only using a PC to use your website but they use multiple devices such as tablet or phone to visit your site. Therefore, responsive design has been invented to facilitate the navigation via multiple devices formats. That is another important trend of today: sites adapt themselves to the device they are viewed on. This way you offer an optimal navigation and all information is easily readable on a large screen PC, tablets and on smartphone. Studies shows that more and more customers use a mobile device to consult company’s websites and that’s about 80%.

If you have difficulties or you need advices on technical issues, don’t hesitate to contact-us. We’ll be happy to assist you.

Survey: Is #CloudSecurity Still a Concern in 2017

The need to run Business more efficiently, improve time-to-market and enhance user experience is driving more and more enterprises to embrace the cloud as part of their IT strategy. You must note that “Cloud” still has many different meanings; IaaS, SaaS, PaaS and so on. Equally interesting is the fact that enterprises today deploy a variety of cloud delivery models to restructure processes and increase agility. IT teams usually have good visibility into and control over their on-premise networks. But when it comes to cloud environments, it’s not as easy to see and react to threats. Regardless of how your organization defines “Cloud”, it’s important to make sure your security can adapt to your organization’s cloud strategies.

 

57% of companies remain skeptical about the security of migration to cloud environments. The loss of “physical control” of data remains a major concern. Companies are still suspicious about the risk of switching from traditional computing to cloud computing environments, reveals a new study by Forbes, which also mentions that the massive trend is towards migration to the cloud.

Cloud Security

The survey reveals that even if the cloud is not a new technology, this market still has a strong growth potential, if security is strong. Forbes says that 65% of companies remain skeptical about the security of migration to cloud environments. Specifically, 40% of companies are concerned about the loss of “physical control” of the data involved in cloud computing.

 

The study also finds that companies seem more comfortable with hybrid cloud deployments in this period of migration to the cloud. 44% of organizations prefer this method. In addition to that, Hybrid cloud adoption grew 3X in the last year, increasing from 19% to 57% of organizations surveyed. Private clouds also seem to be a safer option for many.

 

Think Security Upstream of Cloud Migration Projects

Security Threat in clouds
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At the top of the cloud migration concerns, unauthorized access ranks first among 61% of respondents in the study. For 52% online piracy is a second fear.

Cloud security risks are on the top of the barriers list of cloud adoption (33%). The most dramatic shift is the lack of staff and expertise to manage cloud security (28%) – moving from #5 to #2 and trading places with legal and regulatory concerns (24%) as key barriers to cloud adoption.

 

Finally, it is noted that companies are increasingly considering enhancing the security upstream of their cloud deployments, with a focus on new internal policies. 56% of respondents said they plan to improve identity management and authentication. 51% of companies use encryption to go to the cloud. Finally, 45% of medium and large companies plan to implement audits as part of a migration to the cloud.

 

Only 13% of companies still reject the idea of ​​moving to cloud computing infrastructures. But 30% admit that if they perceive that security is improving, they may reconsider their point of view. While process efficiencies and network agility are key cloud drivers, enterprises of all sizes continually cite cloud security as their top concern. Despite this, cloud adoption continues to rise.

 

Cloud adoption certainly provides many benefits, but enterprise security needs to adapt to this new environment. The end goal of a cloud security strategy must be to permit organizations to realize the full benefits of the cloud without letting security slow them down.

*For the survey, more than 600 IT professionals worldwide, in various sectors, were selected.

From Data to Knowledge: #BigData and #DataMining

The increasing digitization of our activities, the constantly accumulating capacity to store digital data, the accumulation of data of all kind resulting therefrom, generates a new sector of activity whose purpose is the analysis of large quantities of data. New approaches, new methods, new knowledge are emerging, and ultimately no doubt new ways of thinking and working. Thus, this very large amount of data, (=big data), and its processing, (=data mining), affect different sectors such as the economy, marketing, but also research and knowledge.

The economic, scientific and ethical implications of this data are quite significant. The fact that we are in a constantly evolving sector, where changes are frequent and rapid doesn’t make the analysis easy … However, a deep knowledge of data is necessary in order to better understand what data mining is.

 

1 – What is data mining?             

 

Explore very large amounts of data. The purpose of data mining is to extract knowledge from large quantities of data by automatic or semiautomatic methods. Data mining, data drilling, knowledge Discovery from Data (KDD), are also referred as data mining.

 

  • How and why are such quantities of new data generated? Every minute 149519 e-mails are sent worldwide, 3.3 posts are published on Facebook, 3.8 million quarries are booked on Google, 65k photos are loaded on Instagram, 448k tweets are sent, 1400 posts are published via WordPress, 500 videos are uploaded on YouTube and last but not the least 29 million messages are sent via WhatsApp. These numbers can make one’s head go spin around, but important thing to note is that humans aren’t the only producers of data, machines also contribute with their sim cards, their sensors, and so on.
  • What to do with these data? If one understands the contemporary phenomenon of data accumulation, it is perhaps more difficult to perceive in what way these data, are changing the world. Depends how one is able to treat them. Science, IT, Medical sector relies heavily on statistics, on counting, and so on. From the moment when a set of data can be dealt with exhaustively, where cross-breeding and sorting can be carried out on a scale scarcely imaginable a few decades ago, these are analysis of our environment that are changing and being multiplied. In short, data is a tool for management and decision support and evaluation every sector and the raw material of the information is allowing the understanding of a phenomenon, a reality.

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2 – Value of Data

 

While IT organizations are best able to grasp the market potential of data accumulation and processing, this is not the case everywhere, where the idea that data is new oil is making its way more slowly than one might have imagined.

  • What is the market value of the data? Building data through a variety of IT operations is a valuable potential that companies are not always aware of or using it. Even if they do not necessarily know how to exploit data themselves, they have resources that aren’t profitable for them yet. These gathered data and their use is a key issue for companies. The Big Data is a real source of marketing opportunities.
  • Data to be protect that is complex to exploit: Personal data poses many problems for researchers specialized in their analysis. First, they point to the need to better protect them and ensure their conservation. Moreover, it requires very specialized skills to be treated in order to produce interesting results.

 

3 – Data mining and targeted marketing 

 

One of the most significant applications of data mining is undoubtedly in the regeneration of marketing, because data mining allows companies to reach consumers very precisely by establishing precise and reliable profiles of their interest, purchasing methods, their standard of living, etc. Moreover, there is no need to go through a complicated process of search, each of the Internet users leaves enough traces when surfing, tweeting, publishing on Facebook, so that his profiling is possible, without his knowledge most of the time…

  • A new space for social science research: Viewed from another angle, this accumulated data is a gold mine for researchers. Some behavioral researchers have looked at the attitudes of Internet users using dating sites. In addition to finding that the data they use is more reliable than that obtained by meeting individuals (they are easier to lie to an investigator than to a machine …), they can make analyzes that are not politically correct but very informative!

 

4 – The data mining forecast tool

Data mining is also a tool that allows to multiply the properties related to the calculation of probability. Indeed, because it makes it possible to cross a volume of data, but above all, because it makes it possible to apply these calculations to many different fields, it appears today as able to make Forecasts. Plus, Data mining for forecasting offers the opportunity to leverage the numerous sources of time-series data, both internal and external, available to the business decision-maker, into actionable strategies that can directly impact profitability. Deciding what to make, when to make it and for whom is a complex process. Understanding what factors drive demand and how these factors interact with production processes or demand and change over time are keys to deriving value in this context.  Today scientists do not hesitate to announce that they will soon be able to predict the future. All this, thanks to the Data!

  • Probabilities and predictions: Today, predictive statistics tackle all sorts of issues: natural disasters, health, delinquency, climate … Statistical tools are numerous and are combined to improve outcomes, such as when using “random checks”. Even more fascinating, software is capable of improving itself and accumulating ever more data to boost their performance … In the meantime, it is possible to rely on these analyzes to try to avoid the flu or get vaccinated wisely.
  • Anticipating or Preventing Crimes: If the idea that a software would be able to predict crimes and misdemeanors reminds one of Spielberg’s film “Minority report”, reality has now caught up with the fiction: the PredPol (predictive policing) software makes it possible to estimate better than other human technique or analysis, places where crime is likely to occur, and consequently better place police patrols and other preventive measures.
  • Preventing fraud: Other perspectives offered by data mining, improve the fight against fraud and “scams” in insurances sector. Here again, it is a matter of better targeting the controls and apparently it works: This technique gives very clear results. In more than half of cases, when a controller will do a targeted control on the basis of the data mining, he’ll find good results. Insurance companies also apply this type of analysis to detect scams.

Challenges in #MachineLearning Adaptation 

It’s very possible that at the time you read these lines, you’ve already use the result of machine learning algorithms several times today: your favorite social network might have already suggested you a new friend-list, search motor certain pages relevant to your history etc. You’ve dictated a message on your phone, read an article that was in your news feed based on your preferences and that may have been translated automatically. And even without using a computer, you may have been listening to news or just heard the weather forecast.

 

We are living in a world where most transactions and stock decisions that make and undo an economy, and more and even medical diagnoses are based on the qualities of the algorithm than on those of human experts, incapable of treating the mountain of information necessary for a relevant decision-making.

 

Such algorithms learn from data in order to issue predictions and make data based decisions and are called machine learning. These automated learning algorithms and systems have undergone significant advances in recent years thanks to the availability of large volumes of data and intensive computing, as well as interesting advances in optimization. A major feature of deep learning is its ability to learn descriptors while clustering the data. However, there are, many limitations and challenges that we have classified as: Data sources; Symbolic representations vs continuous representations; Continuous and endless learning; Learning under constraints; Computing architectures; Unsupervised learning; Learning process with human intervention, explanations …

 

Data Sources

There are many challenges in this area such as, learning from heterogeneous data available on multiple channels; manage uncertain information; identify and process with rare events beyond the purely statistical approaches; work by combining sources of knowledge and data sources; integrating models and ontologies into the learning process; and finally get good learning performance with little data, when massive data sources are not available.

 

Symbolic Representations vs Continuous Representations

Continuous representations allow the machine learning (ML) algorithm to approach complex functions, while symbolic representations are used to learn rules and symbolic models. The most significant recent advances concern continuous representations. These, however, leave out the reasoning while it would be desirable to integrate it in the continuous representation to be able to make inferences on the numerical data. Moreover, in order to exploit the power of deep learning, it may be useful to define continuous representations of symbolic data, as has been done for example for text with word2vec and text2vec representations.

 

Continuous and endless learning

Some AI systems are expected to be resilient, in order to be able to operate 24/7 without interruption. Interesting advances have been made in lifelong learning systems that will continually build new knowledge while they are operating. The challenge here is the ability of AI systems to operate online in real time, while being able to revise existing beliefs, learned from previous cases, independently. Self-priming is an option for these systems because it allows the use of elementary knowledge acquired at the beginning of the operation to guide future learning tasks, as in the NELL (NeverEnding Langage Learning) system developed at the Carnegie-Mellon University.

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Learning under constraints

Privacy Protection is undoubtedly the most important constraint to be taken into account. Researchers specializing in Machine learning recently recognized the need to protect privacy while continuing to learn from personal data (from records about individuals). To fulfill this purpose, privacy-oriented learning systems are being developed by researchers. Generally, machine learning must take into account other external constraints such as decentralized data or energy limitations. Researches on the general problem of machine learning with external constraints is therefore necessary.

 

Computing architectures

Modern machine learning systems require intensive computing performances and efficient data storage to scale up data size and problem dimensions. Algorithms will be run on GPUs and other powerful architectures; Data and processes must be distributed across multiple processors. New research needs to focus on improving machine learning algorithms and problem formulation to make the most of these computing architectures.

 

Unsupervised Learning

The most remarkable results obtained in the field of machine learning are based on supervised learning, that is, learning from examples in which the expected result is provided with the input data. This involves prior labeling of data with the corresponding expected results, a process that requires large-scale data. The Amazon’s Mechanical Turk (www.mturk.com) is a perfect example of how large companies mobilize human resources to annotate data. But the vast majority of data exists with no expected result, ie without desired annotation or class name. It is therefore necessary to develop unsupervised learning algorithms to manage this enormous amount of unlabeled data. In some cases, a minimal amount of human supervision can be used to guide the unsupervised algorithm.

 

Learning process with human intervention, explanations

The challenges relate to the establishment of a natural collaboration between the machine learning algorithms and the users in order to improve the learning process. To do this, machine learning systems must be able to show their progress in a form that is understandable to humans. Moreover, it should be possible for the human user to obtain explanations from the system on any result obtained. These explanations would be provided during the learning process and could be linked to input data or intermediate representations. They could also indicate levels of confidence, as appropriate.

 

Transfer Learning

Transfer learning is useful when little data is available for learning a task. It consists in using for a new task knowledge that has been acquired from another task and for which more data is available. This is a rather old idea (1993), but the results remain modest because it is difficult to implement. Indeed, it implies being able to extract the knowledge that the system has acquired in the first place, but there is no general solution to this problem (how, how to reuse them …). Another approach to transfer learning is “shaping”. It involves learning a simple task and then gradually becoming more complex until it reaches the target task. There are some examples of this procedure in the literature, but no general theory.

Challenges of #ArtificialIntelligence

 

Until few years ago, #ArtificialIntelligence (#AI) was similar to nuclear fusion in unfulfilled promise. It had been around a long time but had not reached the spectacular heights foreseen in its initial stages. However now, Artificial intelligence (AI) is no longer the future. It is here and now. It’s realizing its potential in achieving man-like capabilities, so it’s the right time to ask: How can business leaders adapt AI to take advantage of the specific strengths of man and machine?

 

AI is swiftly becoming the foundational technology in areas as diverse as self-driving cars, financial trading, connected houses etc. Self-learning algorithms are now routinely embedded in mobile and online services. Researchers have leveraged massive gains in processing power and the data streaming from digital devices and connected sensors to improve AI performance. Therefore, the progress in robotics, self driving cars, speech processing, natural language understanding is quite impressive.

 

But with all the advantages AI can offer, there are still some challenges for the companies who wants to adapt #AI. As AI is a vast domain, lisitng all challenges is quite impossible, yet we’ve listed few generic challenges of Artificial Intelligence here below, such as: AI situated approach in the real-world; Learning process with human intervention; Access to other disciplines; Multitasking; Validation and certification of AI systems.

 

Artificial Intelligence’s Situated Approach:

Artificial Intelligence systems must operate and interact with the real world and their environment, receiving sensor data, determining the environment in which they operate, act on the real world, are such examples. Artificial Intelligence systems must behave autonomously and maintain their integrity under various conditions. To meet these requirements, AI systems must manage unstructured data as well as semantic data.

 

AL system and Human Intervention:

AI systems are programmed to interact with human users: they must therefore be able to explain their behavior, justify in a certain way the decisions they make so that human users can understand their actions and motivations. If this understanding is not forthcoming, human users will have little or no confidence in the AI’s systems, which isn’t acceptable. In addition to that, AI systems need some flexibility and adaptability in order to manage different users and different expectations. It is important to develop interaction mechanisms that promote good communication and interoperation between humans and AI systems.

 

AI, Opening to other disciplines:

An AI will often be integrated into a larger system of many other elements. Openness therefore means that AI scientists and developers will have to collaborate with specialists in other computer science disciplines (ex, modelling and predicting, verification and validation, networks, visualization, human-machine interaction, etc.) to compose a competitive and wider system of AI. The second aspect to consider is the impact of AI systems on many facets of our lives, our economy and our society, and therefore the collaboration with non-computer specialists such as psychologists, biologists, mathematicians, economists, environmentalists and lawyers is a must.

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Multitasking: 

Many AI systems are excellent-competent in a specific area, but turn out incompetent outside of their specific areas. However, systems operating in a real environment, such as robots, must be able to perform several parallel actions, such as memorizing facts, assimilating new concepts, acting on the real world and interacting with humans.

 

Validation and certification: 

The essential element of AI’s critical systems, the certification of AI systems or their validation by appropriate means, are real challenges, especially if they meet the expectations mentioned above (adaptation, multitasking, learning processes with human intervention). The verification, validation and certification of conventional systems (which are therefore not part of the AI) is already a difficult task – even if there are already exploitable technologies. The application of these tools to complex AI systems is a daunting task that needs to be addressed in order to be able to use these systems in environments such as airplanes, nuclear power plants, hospitals, and so on.

 

Other Generic Challenges: 

In addition to the previous challenges, the following requirements for AI systems should lead to new research activities: some are extremely complex and cannot be satisfied in the short term, but worth attention.
Implanting norms and values ​​into AI systems goes far beyond existing science and technology: for example, should a robot that will buy milk for its owner stop on the way to help a person whose life is in danger? Could a powerful AI technology be used by artificial terrorists? At present, AI research is far from being able to meet these requirements.
The privacy requirement is particularly important for AI systems confronted with personal data, such as intelligent assistants / companions or data mining systems. This requirement was already valid for conventional systems, but AI systems have the particularity that they will generate new knowledge from private data and will probably make them public if there are no technical means capable of imposing restrictions.

Final challenge concerns the scaling-up. AI systems must be able to manage large amounts of data and situations. We’ve seen learning algorithms that absorb millions of data points (signals, images, videos, etc.) and large-scale reasoning systems, such as the IBM Watson system, using encyclopedic knowledge. However, the question of scaling for the many V’s (variety, volume, speed, vocabularies, etc.) remains unanswered.

 

AI Applications: 

This is not strictly a challenge for AI, but it is important to highlight that AI systems contribute to resolve societal problems: AI applications cover the entire range of human activities, such as environment and energy, health and assisting living and home maintenance, transportation and smart cities, etc. They can be beneficial to mankind and the economy, but they can also pose threats if they are not controlled as planned.

Benefits of a User-Centric Information Systems

Continuous improvements in technological applications have allowed more and more organizations to develop systems with user-focused designs. Not only they get higher success in day-to-day usage, but it helps to increases the overall probability of technology adoption. With a User-Centric Information Systems, organizations have a comprehensive examination of the latest strategies and methods for creating technological systems with end users as the central point of the design process.

Here below is a checklist that lets you decide whether including user experience in IT project development worth the time and resources?

 

01: Integrate the End-User’s Perspective

 

Focusing on the backbone of the IS system, the IT production teams must ensure that the infrastructure works: servers, switches, storage, etc. Even if the gathered information is a good indicator of the end user’s experience, it remains insufficient.

Imagine a strategic application deployed in an organization, which is taking enormous time to start, while in data center, all signals are green. In the absence of an end user-centric information system, you need to rely on help desk calls to acknowledge the problem – and we all know that all problems aren’t carried forward.

With the right tools, you can detect real time problems and take better preventive measures before the user can be affected.

 

02: Prevention is better than cure

 

Anticipating and resolving problems proactively before they affect end-users reduces the financial impact on the IT Team and the entire organization. But how can one be proactive while concentrating all their efforts to correct problems posteriori? Well, with an IS analysis solution, centered on the end-user, organizations are able to detect and interpret any event related to each application and connection within their environment. This high level of visibility allows them to understand what’s happening and why, but also to proactively solve problems before they affect user productivity.

If a new business application requires the use of a specific version of an Internet browser, users of previous versions may be blocked. Once the problem has been solved for a given user, a final user-centric information system immediately identifies all the stations and users in a similar configuration and therefore potentially at risk. IT support can solve the problem proactively, without waiting for other users to remount the problem.

 

03: Optimize the IT Investment’s ROI on business

 

Optimizing the operating costs of informatics system does not simply mean reducing IT costs. It’s only for the ISD to better target its investments by privileging the projects and resources likely to increase the competitiveness of the company.

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End-user centric information system analysis solution helps to better identify the IT resources and services used within the organization. Equipped with contextual analytical data, the ISD can better focus its priorities and reassign existing assets in order to perpetuate IT investments.

The consumerization of IT and the ever-increasing expectations of executives expect a perfect cohesion in the relationship between ISD and users. An efficient analytical solution for monitoring the information system is therefore a real asset to optimize the ISD’s efficiency.

 

04: Do not be overwhelmed by the complexity of your infrastructure

 

In the era of consumerization of IT, the increasing diversity of systems, applications and generated data increases the complexity of the information system every day.

Confronted with ever more complex and difficult to manage environments, IT teams need to have a clear and accurate view of past, current and future events.

A workstation-centric information system analysis solution is the missing link to ensure full visibility into the effective use of IT resources and services from the end-user’s point of view. A perfect understanding of the user context is just as important as the quality of the applications. For example, many users connect to the information system outside of office hours. What would happen if some of them sent a large print to a central printer before disconnecting? It could be a potential internal threat. Data about this type of behavior exist, but do you really know where to look for them?

The detection and reporting of this type of behavior is only one example of how the analytical data gathered from end-user can be used. More and more companies are adopting a user-centric information analysis system to make sense of the enormous volumes of data related to the connectivity and IS performance to solve problems proactively.

 

05: Plan, organize and measure results more precisely

 

As a cornerstone of the IT Infrastructure Library framework(ITIL), change management is designed to ensure that all IT infrastructure modifications requests are processed efficiently through the use of standardized methods and procedures. It’s important to limit service disruptions and to position themselves from the perspective of the end-user before, during and after the modification/change.

Take an example of Microsoft office update: The simple information available about the installed Office application doesn’t allow to develop an action plan guaranteeing a transparent update for the users.

The IT team must be fully aware of the context in which the application is used, as well as the network connections established by the application, to ensure that they remain available after the new version is deployed. Thus, IT must ensure that all workstations are compatible with the new version, both in terms of configuration and the state of integrity required. In fact, some applications running on MS Office 2003 might not support an upgrade to MS Office 2013 for CPU, RAM, or other reasons.

 

Public, Private or Hybrid Cloud – How to make the right choice?

Cloud computing is a booming industry and has significant economic benefits, including better efficacy of IT and computing needs scalability. Cloud computing concept has clearly shifted from buzz to business and in so doing, has transformed the nature of IT service delivery. Just look at the numbers, according to Gartner, the cloud software market reached $209.2 billion by 2016 and is projected to grow to total $246.88 billion, not to mention the billions of dollars that will be invested in infrastructure to support private and hybrid clouds.

Cloud Service Forecast Fartner

The three types of cloud – private, public and hybrid – are generally grouped under the banner of cloud computing, but they are actually different. Choosing the right cloud can be a challenge to outsource applications, data and services. For the organizations, the decision to use -private, public or hybrid- cloud depends on the services they use and their ability to integrate the chosen model.  But before moving their critical systems within the cloud, a question always comes up within the IT and management team, “What option do we have to opt for Public, Private or Hybrid Cloud?”

 

Each type of cloud has its advantages and disadvantages, which make it the best or the worst solution for a given company, situation or application. Similarly, each has an impact on application and network performance, which must be taken into account before implementation. So, let’s examine each type of cloud.

 

Public Cloud

In a public cloud, services and infrastructure are provided off-site, over the Internet. This means that companies are not looking for a very specific kind of infrastructure and can subscribe and start using storage, processing and other services immediately, via an online portal.

Therefore, the public cloud flexibility and ease-of-use, make it an ideal solution for companies that need to rapidly launch a service in the marketplace, have few regulatory constraints and use data that does not require a close integration with other parts of the company.

However, concerns remain about security, the protection of confidential information and the control of data in a public cloud. Another major problem is performance. Transferring services to a public cloud means accepting that business applications are run from anywhere in the world, regardless of where the service provider’s data center is located.

Most public cloud service providers do not indicate the location of their data center in their general terms and conditions, which gives them blank card to move workloads to reduce their operating costs. In short, the distance to be covered and the time needed to access applications can increase significantly for all users of the company. More surprisingly, these distances can change in an unpredictable way.

 

Advantages of Public cloud:
• It can be used instantly and accessible to all budgets.
• It is suitable for development and experimentation.
• The public cloud is perfectly “elastic” in order to adapt to the increasing needs of a company.

 

Limits of Public cloud:
• The public cloud, although flexible, is not necessarily adapted to all the needs of a company, not being tailored like the private cloud.
• The more you use the public cloud, the more expensive it is;

 

 

Private Cloud

With a private cloud, organizations own and operate internal IT services that host critical internal applications and data within the firewall. However, they can transfer workloads from one server to another in case of peak usage or when deploying new applications. It can be preferable solution for those organizations who have not embraced the public cloud as quickly for critical applications and data due to security requirements, integration issues, and concerns about availability. It can also be a very attractive proposition for companies in sensitive and highly regulated sectors, such as pharmaceutical or financial services. Similarly, many companies still prefer the private cloud for their critical data because it provides total control over data and applications. This eliminates concerns about data security and control, but it is more difficult to adapt to changing needs.

Private clouds also enable IT departments to better leverage their existing infrastructure. Typically, when deploying a private cloud, companies consolidate distributed computing resources and virtualize them in the data center. The IT department can manage them more cost-effectively while providing services faster.

However, it is a double-edged sword, because deploying a private cloud can put a strain on existing resources and work processes. When IT departments consolidate resources, applications and data generally move away from many users. Employees need to travel a longer distance on the WAN to get the information they need. The resulting latency can often radically reduce the performance and productivity of the enterprise.

 

Advantages of Private Cloud:
• It is tailored to your needs and your infrastructure
This potent solution has been invented as a cure to cardiovascular activities since it improves the blood flow in the appalachianmagazine.com order cheap levitra local area of the body. The corner that there is no noise from, that we walk into to hide from the people who can appalachianmagazine.com viagra viagra sildenafil harm it. Sexual Health assumes a generic soft viagra vital part in life of individuals. If that cheap levitra india happens then you should not be taking these pills. • Its cost is fixed (determined by the size of the infrastructure).

 

Limits of Private cloud:
• This is a costly investment, and depreciation must be expected.
• The time required to adapt the size of the infrastructure to the needs of the company may be too long compared to the speed of the infrastructure.

 

Hybrid Cloud

In many cases, the hybrid cloud offers the best of both technologies. It becomes the norm because it allows companies to alternate between the two models depending on the conjuncture.

By splitting elements into a hybrid cloud, companies can keep every aspect of their business in the right environment. However, the merging of the public cloud and the private cloud poses an additional problem: the integration of services becomes more difficult because there is a loss of data consistency. This results in additional management, as well as potential differences in the interface, security, processing and reporting systems that need to be addressed.

As a composite architecture, the hybrid cloud has a dual implication, exposing networks to the potential impacts of deploying a public cloud and deploying a private cloud: applications delivered via a Public service are still likely to be located anywhere in the world, while private cloud applications are still consolidated in a small cluster of data centers, resulting in a potential blockage affecting network operation.

 

Advantages of Hybrid cloud:
• Each data item is naturally stored in the most appropriate Cloud environment.
• This solution combines the major advantages of the public cloud (flexibility, speed of implementation, development and experimentation) and those of the private cloud (security and total control of data).
Limits of the Hybrid cloud:
• This solution is however exposed to the disadvantages of the different types of Cloud and the risks during the deployment of each Cloud solution.
• The use of two different cloud types increases the management required

 

Accelerating cloud services

 

Whether a company choose a private, public cloud service or (most likely) hybrid cloud approach, WAN optimization allows it to take advantage of cloud computing offerings in terms of cost, economies of scale and ease of management while attaining the levels of performance and visibility needed to ensure the productivity of its staff.
Given the take-off speed of cloud computing, sooner or later, more companies will have to consider the benefits it can bring. Companies need to evaluate the cloud model that suits them best, but whatever model is chosen, a thorough understanding of the impact of each cloud service type on their IT infrastructure and topology is essential to ensure that it will result in no degradation of performance for users.

 

Do you have a Cloud project? Contact-us and we will support you to evolve your IT architecture by integrating a Cloud component.

#SaaS and European Legislation on #DataProtection

This article presents a summary of the legislative and regulatory aspects that European companies must take into account when choosing a SaaS provider. Particularly in terms of #DataProtection. When choosing a SaaS provider, companies must implement a checklist with controls and negotiations that they would apply if they work with a relocated service provider for their IT operations.

EU-Data-Protection-Regulation

The main features of Software as a Service are as follows:

 

– The user accesses the application via the Internet.

– The cost depends on the actual consumption of the service (software).

– The supplier of the application (software) is responsible for its maintenance and availability.

 

Typically, when a European company adopts a cloud service, it’s responsible for how the SaaS provider processes its data, not the other way around. Due to some uncertainty, as to how and where the SaaS provider will store the data, there is a risk that it may overstep on its customers national or European regulations, which impose strict controls on the processing data of outside the European Union.

 

In SaaS solutions, the client company data is stored on the servers of the provider. This may include personal data or sensitive data such as health data. This relocation of the data implies respecting their confidentiality and ensuring their safety. The contract must frame the risks and remind everyone of their obligations.

 

In accordance with the 1995 European Data Protection Directive, which was transposed into the national law of 27 EU Member States, the transfer of personal data outside the European Economic Area (EEA), including the countries of the European Union (plus Iceland, Liechtenstein and Norway) is prohibited unless certain conditions are met. By transfer, the Directive implies that the data will be processed in one way or another in a non-EEA country; On the other hand, the transit of data via these countries is authorized.

 

For Directive, personal data is equal to any information concerning an identified or identifiable natural person. This broad definition may include various information about a person, such as name, address, IP address, or credit card information.

 

Cloud Computing = Outsourcing?

 

Outsourcing is the well-known method whereby a third party supports one or more company functions, which often lack resources (time, expertise or both). It is common, for example, to outsource a project that requires an increase in resources or a function that will no longer be useful once the project is completed (one-time need for development, software integration, etc.).

 

With cloud computing, companies do not realize that they need to take the same precautions as outsourcing. Personal data may be transferred outside the EEA if they are processed in a country on the European Commission’s list of countries or territories which provide adequate protection for personal data. (Visit the European Commission website to check countries list ).

 

The United States is not on the list of countries approved by the Commission, but data can be transferred to US companies that have signed the Safe Harbor agreement requiring them to apply seven principles for the processing of information under the supervision of the Federal Trade Commission.

 

If a country is not on the European Commission’s list of approved non-EEA countries, companies or service providers may take other measures to provide suitable protective policies for personal data and enable their transfer.

 

The security of the SaaS provider must be evaluated by the companies

 

In addition to these measures, companies considering SaaS and wanting to avoid the failure to comply with #DataProtection laws generally have to prove that they have evaluated the safety of the supplier and specified measures to protect personal or other sensitive data processed by the supplier.

 

These measures may include asking the supplier a security evaluation from a third party, requesting that the data must be encrypted during transit, checking the provider’s data retention and destruction policies, setting up audit trails or the data and obtain information about any third-party company with which the supplier could share data.

 

With that being said, companies should not just look at data protection legislation when they want to adopt SaaS. Thus, national laws on financial legislation in EU countries limit the places where companies can store financial information. For example, European companies must keep electronic invoices for five to ten years. In addition, amendments to the European Council Directive 2010/45 / EU stipulate that this information must be stored on servers located either in the country of establishment of the undertaking or in a neighboring country providing access to the relevant tax authorities.

 

Confidentiality of Data

 

The confidentiality of data hosted in Cloud is today the most important of the brakes for the companies wanting to use this service. The standard of confidentiality becomes very important when the hosted data presents a strategic content for the company or when it can be considered as personal data.

 

The confidentiality of the data may be called into question by members of the service provider or the client company, as well as by a person totally outside these services. It is therefore necessary to put in place, a high level of security, for access to these data, especially if they are accessible via the Internet. The confidentiality of data can also be undermined by regulations applicable to the claimant, especially if the applicant is domiciled in the United States.

 

As the SaaS market matures, it is becoming increasingly simple to use these services without fear of breaking the law. Over the years, we have seen the evolution, the contracts have grown and different models have been set up on both the customer and the service provider’s side.

 

Source: 

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Discover 10 tips for Cybercrime Prevention

As a business holder, you are aware that it is important to be well insured. Your building, your equipment, and possibly your staff: each one has an adapted insurance. There is, however, one area that small-medium companies do not always think about: protecting their company’s information, knowledge and data. Yet, their importance is crucial.

You are most probably aware of the computer threat that is hanging around today. You may even think that only multinationals are concerned and have to take action in this area. This is not the case: every company, whatever its size or its activity, must guard against cybercrime.

Cybercrime Prevention

The tips below, developed by Belgian Cyber Security, are a good starting point to know how to protect yourself easily, as well as your business.

 

  1. Cyber threat awareness education

It is crucial for your company that your employees are aware of the various IT threats and the security measures to be taken. In the interest of your business, you should encourage them to use passwords correctly, to communicate and to store digital files in a secure manner.

If your employees only have access to the information they need to fulfill their function, the security risks are automatically reduced.

 

  1. Install antivirus and perform regular scanning

Antivirus is a must in your business! You may think that it is not necessary to install an antivirus because your PC has never been infected before? If you do not have an antivirus scan, you cannot say for sure. Your computer or that of one of your collaborators could indeed be infected with a virus for some time, without you being aware of it. Do you know that a free antivirus protects you from 5% to 10% of cyber-threats? A risk that you should avoid if you want your business to be secure.

 

What if you receive a virus warning?

 

  • Via your own antivirus: follow the steps suggested by your antivirus to solve the problem. You can certainly take this warning seriously.
  • Via a pop-up screen on the Internet: While you surf, never click on a pop-up screen that says your computer is infected. There is a good chance that this warning is false. Instead, close your Internet browser.
  • Via a program, you do not know: never click on warnings from programs you do not know. Close the screen and restart your computer.
  • Via e-mail or phone: Never trust companies, organizations or bodies that call you or send an e-mail to ask you to perform certain manipulations on your computer. Delete the e-mail or hang up

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  1. Keep your system up to date

Use automatic updates as much as possible. A series of programs and various browsers offer automatic updates. If you are using a paid antivirus software (also called security suite), then do not worry! The latter performs its updates automatically.

 

  1. Regularly perform a backup copy

Regularly back-up important data and information. Determine which data should be backed up, how often it should be backed up and where the copy will be saved. Keep this backup in a safe place and make sure it is always disconnected from the network. Also, if you notice that you have been infected, immediately disconnect from the network.

Also, keep information on your computer that is not connected to the network or on paper, such as important e-mail addresses and phone numbers, or information about your Internet service provider.

 

  1. Protect Data

The internal network of your company should in principle give access only to the websites necessary for the execution of your professional activity. This does not mean, however, that all websites for private purposes must be blocked. A good alignment with the members of the company is therefore important.
Nevertheless, a single visit to an unknown or falsified site can be enough to infect your computer. If the web address starts with “https: //”, you can surf safely.

 

  1. Use strong passwords

The longer your password, the more secure it is: numbers, capital letters and symbols make your password more difficult to hack. Plus, reusing the same password several times is not a good idea: if your data is hacked on a site, authors will generally try to use your password on other sites to hack your accounts. For smaller accounts where no banking or personal data is included, it is sufficient to use variants of the same password. Some examples of “less important” accounts: mailbox, social networks and web shops.

Changing your private account passwords once a year is a good idea. In the professional context, we recommend changing passwords even more often, given the sensitive information that circulates there.

 

  1. Secure your mobile devices and wireless Internet

The increasing use of mobile devices is a challenge in the field of security. It’s better to never make online payments or introduce important account passwords when working on an unsecured wireless network.

The BYOD (Bring You Own Device) concept is an increasingly popular approach, which nevertheless creates an additional cyber risk. Indeed, information specific to the company is thus disseminated and consulted on private devices. Draw the attention of your colleagues to the fact that the use of mobile devices entails additional responsibility. Always keep a watch on your mobile devices, check your environment before using them and immediately report theft or loss of a device.

An additional benefit of using a paid antivirus software: you can adapt the number of licenses to the number of users.

 

  1. Do not click any link, image, or video

You receive an e-mail from someone you do not know? Above all, check the sender. Do not open any links or attachments in your emails, even if they look genuine. Criminals use phishing to try to get your personal data for later use.

Some clues to verify the authenticity of an e-mail

  • Unexpected: You have no reason to receive a message from this sender
  • Urgent: a second request for payment, a friend in distress: phishing messages often ask you to act immediately.
  • Spelling errors: check the e-mail address of the sender. In general, it contains misspellings, but this is not always the case. In short, stay alert!
  • Title of civility vague: the title of greeting is very general and does not mention your name? In this case, it may be a falsified message.
  • Payment method: Phishing messages often require unusual forms of payment.

 

  1. Separate private and professional accounts

Do you use the same password for your private and business accounts? Very bad idea! For smaller accounts where there are no bank or personal data, it may be sufficient to use variants of the same password.

Also, give as little personal information as possible if you subscribe to newsletters, forums, etc. The less personal information you have on the Internet, the less likely it will be for you to use it.

 

  1. Delete accounts you do not use

Do you no longer use certain accounts or software? Delete them simply. The more opportunities for cybercriminals, the greater the likelihood of an attack.

 

It’s important to be aware of cybercrime threats, whether it’s on personal or company level, in order to react on them in an appropriate manner. If we ignore them, these security incidents can have a great impact on us, either as individuals or companies.

Attention: Do Not click on the ‘new feature’ messages from #WhatsApp!

Since a week now, WhatsApp users, across the globe, are receiving a message containing a special link that promise a new functionality. It’s supposed to be a feature that lets you use other colors, but in reality, it’s an open invitation to install a malicious software.
Here below you can visualize the screenshots of the link. It appears from WhatsApp itself, but is a virus.

WhatsApp Virus

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WhatsApp Virus

To prevent any data loss, it’s better to stay away from such spam texts and confirm about functionalities before clicking and sharing such messages.

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