Human Machine Partnership – Is 2018 the year of #MachineLearning?

Human Machine Partnerships2018 is all about the further rapprochement of man and machine. Dell Technologies predicts the key IT trends for 2018. Driven by technologies such as Artificial Intelligence, Virtual and Augmented Reality and the Internet of Things, the deepening of cooperation between man and machine will drive positively the digitization of companies. The following trends will and are shaping 2018:


Companies let AI to do data-driven thinking


In the next few years, companies will increasingly use the opportunity to let artificial intelligence (AI) think for themselves. In the AI systems, they set the parameters for classifying desired business outcomes, define the rules for their business activities, and set the framework for what constitutes an appropriate reward for their actions. Once these sets of rules are in place, the AI systems powered by data can show new business opportunities in near real time.


The “IQ” of objects is increasing exorbitantly


Computing and networking items over the Internet of Things are becoming increasingly cost effective. The embedding of intelligence into objects will therefore make gigantic progress in 2018. Networked device data, combined with the high levels of computing power and artificial intelligence, will enable organizations to orchestrate physical and human resources automatically. Employees are becoming “conductors” of their digital environments and smart objects act as their extension.


IQ of Things


AR headsets ultimate comeback in 2018


Its economic benefits have already been proven by augmented reality (AR). Many teams of designers, engineers or architects are already using AR headsets. Whether to visualize new buildings, to coordinate their activities on the basis of a uniform view of their developments or to instruct new employees “on the job” even if the responsible instructor cannot be physically present at the moment. In the future, AR will be the standard way to maximize employee efficiency and leverage the “swarm intelligence” of the workforce.


AR headsets


Strong bond of customer relationship


Next year, companies will be able to better understand their customers through predictive analytics, machine learning (ML), and artificial intelligence (AI) and use these technologies to improve their customer first strategies. Customer service will perfectly maintain the connection between man and machine. It will not be first-generation chatbots and pre-made messages that address customer concerns in the service, but teams of people and intelligent virtual agents.


Deeper Relationship with Customers


The “Bias Check” will be the new spell checker


Over the next decade, technologies such as AI and Virtual Reality (VR) will enable those responsible to evaluate information without prejudgment and make decisions in an entirely balanced way. In the short term, AI will be used in application and promotion procedures to bring out conscious or unconscious prejudices. VR is increasingly being used as an interviewing tool to cover the identity of applicants with the help of avatars. “Bias checks” – “prejudice checks” – could become the standard procedure in decision-making processes in the future, just as spell-checking is today when it comes to writing texts.


Bias check


The mega-cloud is coming up

In 2018, an overwhelming majority of companies will adopt a multi-cloud approach and combine the different cloud models. To overcome the associated cloud silos, the next step will be the mega-cloud. It will interweave the different public and private clouds of companies in such a way that they behave as a single holistic system. With the help of AI and ML, this IT environment will be fully automated and consistently evaluated.




IT security is becoming more important than ever


In today’s increasingly connected world, IT security companies need more than ever to rely on third parties. They are no longer individual instances, but parts of a bigger whole. Even the smallest errors in any of the connected subsystems can potentiate to fatal failures in the entire ecosystem. In particular, for multinational corporations, it’s a must in 2018 to prioritize the implementation of security technologies. This development is further fueled by new regulations, such as the GDPR regulation of the EU.



E-sports gaming industry ready for mainstream


Not least driven by virtual reality, the phenomenon of e-sports for companies in the media and entertainment industry 2018 finally become a fixture. Millions of other players and viewers are jumping on the bandwagon and making continuity e-sports mainstream for 2018. This phenomenon is representative of a bigger trend: even original physical activities such as sports are digitized. In the future, every business will be a technological business, and people’s free time will be shaped by networked experiences.


“People have been living and working with machines for centuries,” says Dinko Eror, Senior Vice President and Managing Director, Dell EMC Germany. “In 2018, however, this relationship is reaching a whole new level: man and machine will be more intertwined than ever, and that will change everything – from the way we do business to the design of leisure and entertainment.”

2017 Digital Evolution Report – CyberCrime, Digitization, Blockchain and Artificial Intelligence

Cyber-crime, Smart-Cities, Digitization, Blockchain and Artificial Intelligence are those words which really got the hype on the platform of IT in 2017. Cybercriminals have smacked many companies many times. Digitization is progressing despite lame internet connections. Blockchain became Gold Chain and Artificial Intelligence is experiencing an incredible revival.

Key Technologies 2017

Ransomware: The ransom and the cyber blackmailer


Ransomware remains a leader in digital security threats. According to ITRC Data Breach report, in 2015 more than 177,866,236 personal records exposed via 780 data security breaches, and the previous mentioned number lift up to 30% in 2016 with security breaches arising on multiple fronts, companies, healthcare systems, governmental and educational entities, and individuals started to realize how real the threat of cybersecurity attacks was. 2017 so far, was a very highlighted year for cyber-crimes. 519 Cyber-attacks were placed from Jan 2017 until September 2017 affecting financial sectors, health-care sectors, gaming companies, containing information about credit cards, health data of billions of people around the world. With all these attacks phishing, spying on webcams or networked household appliances (IoT) remain risky.


Very popular in this year’s cyber attack list are the #wannacry and Equifax data breach attacks. These attacks unbaled 300000 computer systems for 4 days and affected financial data on more than 800 million customers and 88 million businesses worldwide and more than 45% of all detected ransomware.

Cyber policies are currently very much in vogue, but in which cases of damage do these insurances actually comes in? ABA, American Bankers Association, explains how companies should best go about finding a suitable policy and what makes good cyber insurance.


The General Data Protection Regulation (GDPR): What needs to be changed?


Companies only have a few months left to prepare for the new European #DataProtection Regulation. On 25 May 2018, all companies managing personal data of citizens of the European Union will be required to comply with the new regulations and requirements of the General Data Protection Regulation (GDPR).

This regulation will impose significant new obligations on companies that manage personal data, as well as severe penalties for those who’ll violate these rules, including fines of up to 4% of global turnover or € 20 million highest amount being withheld. But what is to change concretely? Here is a “Guide to compliance with the EU GDPR” and a framework to become step by step GDPR-fit.


Digital Transformation: Slow Internet connections as a brake pad


Digitization is progressing, but most users still complain about slow Internet connections. Despite the 7th place in the worldwide internet ranking, Belgium is still far behind the world’s fastest internet country. Notwithstanding all the shortcomings of the national IT infrastructure, companies are dealing with the technical and organizational challenges that result from the digital IT transformation.


The crazy rise of Bitcoin


In the period of a year the value of bitcoin has been multiplied by ten. A bitcoin was worth “only” 1000 dollars on January 1, 2017 … and 8000 dollars ten days ago. In April 2017 Japan officially recognised bitcoin and virtual currencies as legal methods of payment. You should know that Bitcoin represents less than 50% of the money supply of all cryptocurrencies in circulation. this is partly explained by the network situation and the rise of the Ethereum currency. Even if bitcoin is a legal in the vast majority of countries around the world, only a few governments have recognized the legal status of bitcoin in a particular regulatory manner.


IoT Projects: The 5 Biggest Mistakes and the Five Steps to Success


Closely linked to Digital Change is Internet of Things (IoT) and Industry 4.0 projects. Pioneers already pointed out the four biggest mistakes in IoT projects. If a company wants to exploit the potential of the IOT, it means a lot of work and often frustration – the technical, commercial and cultural challenges are manifold. Until an IoT solution is successfully established on the market, many decisions have to be carefully considered.

But how does an IoT project succeed? Four steps are needed to make an IoT project a success.


Blockchain: The new gold chain

The blockchain is a much-debated technology with disruptive potential and three key characteristics: decentralization, immutability, and transparency. It could help to automate business processes, increase the security of transactions and replace intermediaries such as notaries or banks. Blockchain turns out to be the silent revolution that will change our lives. On top of that, it can turn into a gold chain for early adopters.


Cloud: Companies use public cloud despite security concerns

For years, companies have avoided the public cloud, as it is difficult to get a grip on in terms of security. However, this year, companies in the EMEA region increased their investment in the public cloud despite ongoing security concerns and lack of understanding of who is responsible for data security. However, caution is still needed to provide attacks such as wannacry.


Artificial intelligence

In 2016, Gartner put artificial intelligence and advanced machine learning in first place in its forecast for 2017, stating that this trend was really pronounced during 2017. Briefly 80 % of companies have already invest in Artificial Intelligence (AI). Nevertheless, one out of every 3 deciders believes that their organization needs to spend more on AI technology over the upcoming years if they want to keep pace with their competitors. Artificial intelligence penetrates into all areas of life. But how does it work?

One example is the automated and personalized customer approach to AI. With personalized campaigns and individual customer approach, the marketing of the future wants to win the battle for the buyer. As a rule, the necessary data are already available in companies, but the resources and software tools for their profitable use are not.
In 2018 Businesses will have an availability of AI-supported applications and should therefore focus on the commercial results achieved through these applications that exploit narrow AI technologies and leave the AI in the general sense to researchers and writers of science fiction;


The future of the human worker

AI systems can be used without a doubt. The world is becoming increasingly complex, which requires a thoughtful and wise use of our human resources. This can support high-quality computer systems. This also applies to applications that require intelligence. The flip side of AI is that many people are scared about the possibility of smart machines, arguing that intelligence is something unique, which is what characterizes Homo Sapiens. Not only that but many people still think that Artificial intelligence is the new threat to employment. It will replace the man and steal all the jobs. And they thinks that the future is dark.

Yet technological progress has never caused unemployment. On the contrary, since the industrial revolution, employment has multiplied. But, always, with each progress, fears resurge. Today, it is artificial intelligence that scares, or is used to scare. Economic history, and economic science therefore invites us to remain calm in the face of technological progress in general, and artificial intelligence in particular. By allowing the invention of new things to be exchanged, by stimulating entrepreneurship, it is not a danger but only an opportunity.


DATA based business models

Data Driven Business Model puts data at the center of value creation. This central place of data in the Business Model can be translated in different ways: analysis, observation of customer behaviour, understanding of customer experience, improvement of existing products and services, strategic decision-making, and marketing of data.

These data can be gathered from different sources, generated directly by the company, processed and enriched by various analyses and highlighted by data access and visualization platforms. Once data is collected, It’s essential to manage the multiple sources of data and identify which areas will bring the most benefit. Tracking the right data points within an organization can be profitable during the decision-making process. This allows an organization’s management to make data-driven decisions while amplifying synergy within the day-to-day operations.
As for revenue models, these can be based on a direct sale of data, a license, a lease, a subscription or a free provision financed by advertising.


Smart Cities – Privacy, Security, #CyberAttacks and #DataProtection

Smart city components

“Smart cities” is a buzzword of the moment. There is currently no single accepted definition of a “smart city” and much depends on who is supplying the characteristics: industry, politicians, civil society and citizens/users are four immediately and obviously disparate sets of stakeholders. It is easier perhaps not to define smart cities but to elaborate their key features in orser to better understand this concept. The connecting key infrastructure that is most often mentioned as making cities “smart” includes:


  • networks of sensors attached to real-world objects such as roads, cars, fridge, electricity meters, domestic appliances and human medical implants which connect these objects (=IOT) to digital networks. These IoT networks generate data in particularly huge amounts known as “big data”.
  • networks of digital communications enabling real-time data streams which can be combined with each other and then be mined and repurposed for useful results;
  • high capacity, often cloud-based, infrastructure which can support and provide storage for this interconnection of data, applications, things, and people.


Scanning through numerous smart city projects and initiatives undertook, eight key activities can be identified that often define a smart city, ie: smart governance, smart infrastructure, smart building, smart connectivity, smart healthcare, smart energy, smart mobility and smart citizens.


A European survey shows that the benefits of smart cities are obvious, but IT security and technological challenges are a major barrier to their acceptance. Ruckus, a network connectivity provider, has published the results of its Smart Cities Survey with UK market research firm, Atomik Research. The survey surveyed 380 European IT decision-makers from the public sector.


The aim of the study is to understand the attitudes towards the implementation of smart city concepts and to learn what opportunities they offer to the industry. The majority of respondents (82%) believe that smart city technologies are helping to increase citizens’ security and reduce crime rates, for example via smart lighting or networked surveillance cameras. Although the benefits seem to be well known, fears of cyber attacks are a major barrier to the Smart City. For 58% of the IT decision makers surveyed, the biggest problem is followed by a lack of technology infrastructure and funding.


Benefits of citywide connectivity


The survey results show that the infrastructure and technology platforms created for Smart Cities could be used to add significant value to the public sector and to develop innovative applications that directly address citizens’ needs. Other areas that benefit from the smart city model include local health (81%) and transport (81%), which provide greater access to public services for citizens through extensive networking. According to IT decision-makers, smart city concepts also provide crucial benefits for the security of citizens (72%), public transport (62%) and the health service (60%).

Nick Watson, vice president of EMEA at Ruckus, said: “A basic understanding of the benefits to citizens shows that policymakers are aware of the benefits of this technology. As the return on investment becomes clearer and smart cities become more and more commonplace, targeted advocacy will allow organizations to work together to make the city of the future a reality. Of course, given the amount of sensitive data that could be divulged, it is not surprising that security concerns play a big role. Only a           secure, robust and reliable network will allow to address these concerns and create a secure foundation for smart cities. “


Benefits of smart cities


The survey shows that the public sector is well aware of the added value that smart cities has to offer. Almost two-thirds (65%) of respondents said smart cities bring benefits. 78% of respondents said that they recognize that there are strong economic reasons for investing in smart city concepts. These reasons include firstly the credibility of a smart city (20%) and future infrastructure (19%). On the other hand, there is the related attractiveness, which leads to the resettlement of companies (18%) and suggests that the true value of smart cities lies in generating revenue and boosting the local economy.

These findings are a positive step towards ideal framework conditions in which smart cities can successfully develop. To make smart cities a reality across Europe, it takes an overarching approach involving all departments of a city. However, the Ruckus survey also found that isolated projects (39%) still pose a major barrier to smart cities.

Although lack of funding is seen as the third most obstacles to rapid implementation, 78% of respondents across countries expect to have the budget for smart city solutions by 2019. This should also be facilitated by promotional announcements such as the Wifi4EU program. It gives cities the security that the infrastructure will be available to support smart technologies.


Overcome barriers


To provide these services, a stable public WiFi network is crucial. 76% of respondents agree that this is the most important factor in successfully implementing smart city concepts. 34% agree that Wi-Fi is more important than a wired network. Wi-Fi is probably the preferred infrastructure because people are familiar with it and it gives everyone access to information. If you want to be able to connect with your citizens and use the services you offer more effectively, you need a suitable infrastructure to connect with the public in a way that benefits them.

WLAN is the “glue” for intelligent cities’ network. It makes it easier to distribute the load and reduces connection problems. The access point at the edge of the network is the ideal interface that acts as a message broker by delivering traffic, performing and returning simple data processing, and placing the software through controllers.

However, not all WLAN technologies are the same. Power supply (53%), interference (52%) and backhauls (45%) are the biggest obstacles to setting up a public WLAN infrastructure. 51% of IT decision makers called the consolidation of existing networks as another crucial obstacle. This is particularly important because the number of connected devices is increasing at a time when existing networks are not prepared for the exponential growth of data consumption. IT decision makers have the clear task of choosing the right technology partner to meet the technological needs of their city.

For Ruckus, the findings of this study are an opportunity to engage in dialogue with various public-sector organizations on how smart city technologies and a public Wi-Fi network can add value. The survey shows that WLAN is considered necessary for the creation of smart cities because:

  • It gives access to everyone information (71%);
  • it delivers the necessary infrastructure to offer additional services (70%);
  • it overcomes the digital divide between citizens (67 percent);
  • it is cheaper for governments (61%);
  • it could lead to better service (37%);

The research shows that Wi-Fi is a key contributor to helping smart cities deliver reliably and sustainably, but along the way, European policymakers still have some obstacles to overcome. It is reassuring to see that there is a widespread belief that smart cities add value to society. But if the government and the public sector are not investing in the right technology, then they risk missing the numerous opportunities for cities, citizens and themselves.

#GDPR: Does your Business comply with the new #DataProtection requirements?

Our data is one of our most prized asset. As an organisation, our clients entrust us with this data. In our vision data and its security must be critical for each operations, innovation and competitive position. As an enterprise, you can be more successful in your respective line of business when you manage to get your data security right.


Therefore, the EU’s GDPR brings data protection legislation into line with new, previously unforeseen ways that data is now used. This wide Basic Data Protection Act (EU-GDPR) can be very complex and opaque. IBM Security has developed a five-phase framework to help organizations implement the mandatory regulation from 2018 onwards.


In addition to that, IBM Security has also worked in the past to create a service that will help companies prepare for the upcoming GDPR. Instead of accessing complicated, multi-dimensional matrices or diagrams, a simple framework was compiled.


Step by Step GDPR


Each journey begins with the first step, and so IBM Security has also extracted five separate steps for the journey to GDPR’s expertise. This allows companies to fallow a step by step guidelines through the five, to the point, phase framework. The framework also takes account of the fact that each company will have its own needs during the process. Therefore, it is designed as simply as possible.


Based on the main focus of the GDPR, the five steps within the framework are subdivided into the areas of data protection and security. Since both areas are closely interwoven, IBM Security has selected the following area definitions for us: In the field of data protection everything is about what data is collected and why they are managed, shared, processed and moved around. Security, on the other hand, is much more concerned with how data can be controlled and protected. This also means that within a company, security can be achieved without data protection, but no data protection can be guaranteed without adhering to security standards.


The five-phase framework for the GDPR

IBM’s GDPR Framework


The approach for a basic GDPR expertise in five steps is the fallowing:


Phase 1: this first step is related to company assesses. It is necessary to examine which of the collected and stored data are affected by the GDPR guidelines. A plan is then drawn up to reveal this data.


Phase 2: is about the company’s own approach, a solid plan that governs the collection, use, and storage of data. This approach is based on the architecture and strategy on the basis of which risks and company objectives are exploited. Designing privacy, data management and security management are top priority.


Phase 3: the company’s way of doing are rethought. It is important to understand that the data gathered so far are as valuable to the people as they are to the company. At this point, sustainable data protection guidelines have to be developed. However, it is also about introducing safety controls and administrative controls (also: TOM – Technical and Organizational Measures) and appointing a Data Protection Officer so the GDPR training can be delivered to the right persons for the job.


Phase 4: in this phase, companies are ready to implement their data protection approach. Data streams are continuously checked from this phase, and access to data is monitored. In addition, security checks are performed and unimportant data is deleted.


Phase 5: the company is ready to comply with the GDPR guidelines. From then on, all requests for access, correction, deletion and transmission of data are met. In addition, by documenting all activities, the company is prepared for possible audits and can, in the case of a data lap, inform regulators and affected parties.


Above is the direct approach of IBM Security to make companies fit for GDPR. The way to get there is not always easy, but the framework should at least show it more clearly. Companies are themselves responsible for compliance with the applicable regulations and laws, which are included in the EU-GDPR. Note that IBM does not provide any legal advice and does not warrant that IBM’s services or products comply with applicable laws or regulations.

#Data : An Important Piece To “The #InternetOfThings” Puzzle

Internet of things

Every day, connected objects generate billions of information that must be processed and analyzed to make them usable. Thanks to the development of connectivity on multiple devices, the arrival of inexpensive sensors and the data inflation they transmit, IoT have took irreplaceable place in our daily lives. IDC forecasts worldwide IOT market to grow more than $7,1 trillion by 2020. The number of devices will more than double from the current level, with 40.9 billion forecasted for 2020.


These very serious estimations do not, however, take into account the full extent of this digital revolution. If the design of connected objects is the showcase of the IoT and its vast possibilities, it still requires strong skills on the processing of the exploited data collected from sensors terminals, machines and platforms to interpret it in order to boost productivity and increase performance.


Just as in jewel market, the big winners are gold/diamond dealers. In the IOT domain, this role is played by companies able to manage the mountains of data generated by these connected devices because the collected data is profoundly changing the way businesses used to operate. Almost every day, new applications are imagined, with consequences at all levels of organizations because the real added value of connected objects only comes from the uses and the ability of companies to create new services.


Several studies demonstrate that companies are still facing a gap between the collection of new data and the presentation of the analyzed information so that it can be understood and explored in great detail, whether it is for a connected house, connected car, a portable terminal or an industrial solution.


Here below is the list of tips companies must consider before every IOT project implementation:


  • Sort valuable information among a big volume of data:
    Exploiting IoT means generating a huge amount of data. The challenge for companies is to filter the stray information and find the ones that are really important. This is why many companies integrate a flow analysis and a process analysis. The first provides real-time information from data streams such as navigation paths, logs, measurement data, and the second is to take machine data captures.


  • Set and manage priorities:
    The IoT implies different levels of necessity in terms of urgency and latency. It’s important to take this into account because one expects to interact with the “real world” in real time. For example, sensors in mines must trigger an alert as soon as they detect the presence of toxic gases. Similarly, other IoT information may not be needed “just in time”, such as regularly collected data to further refine and improve the predictive model itself. This data can potentially be collected and processed several times a day, for example.


  • Design considerations for IoT technologies:
    Information security, privacy and data protection should systematically be worked at the design stage. Unfortunately, in many cases, they are added on later once the intended functionality is in place. This not only limits the effectiveness of the added-on information security and privacy measures, but also is less efficient in terms of the cost to implement them. Although industries are actively working to address this, it stays a major IoT problem.


  • Cross the Data:
    In the case of preventive operations, for example, companies want to collect data from objects (such as smart meters) and cross them with relevant relational data, such as maintenance agreements, warranty information and life cycle components. It is therefore essential that companies can rely on the data from which they make important decisions.


  • Tracing the data:
    The increased collection of data may raise issues of authentication and trust in the objects. In addition, it should also be noted that by using information collected about and from multiple objects related to a single person, that person may become more easily identifiable and better known. So in order to fully exploit the potential of IoT, tools must be much more flexible and allow users to shape and adapt data in different ways, depending on their needs or those of their organization.


Collaboration between the IT team and business experts is more critical than ever before in analyzing IoT data. In addition to those who understand the data, it takes experts to analyze gathered data from specific devices or sensors. While any analyst can understand the data in the context of a company’s performance indicators, only a data specialist would be able to explain what kind of hidden data contains a wealth of information, and how with the right tools, companies can unleash that potential.

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.

From Data to Knowledge: #BigData and #DataMining

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.


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.

Physical & Cloud #DataProtection: Best Practices for your #Backup and #RecoveryProcess

Data has become one of the most valuable assets of organizations. Massive data is the new currency. Thanks to advancements in technology and connectivity, data creation is skyrocketing upwards. According to IDC this data is expected to double every two years for the next decade, hitting 45,000 exabytes in 2020. These data are stored in ever-increasing environments and connected devices, therefore backup and restore capability of an information system is a real challenge to ensure business continuity and the availability of associated data.

Data Protection

What must IT departments do to fulfill the data security mission? Well, the data security policy is at the heart of each business concerns and should be a fundamental part of their security strategy. Planned security measures can then create tactical and operational rules through the joint efforts of security and storage teams. To this end, storage must be an integral part of the company’s security strategy.


To achieve these objectives, a company must establish a cluster around the following five essential aspects:
• Allocation of responsibilities;
• Risk Assessment;
• Development of a data protection procedure;
• Communication of data protection procedure;
• Execution and testing of the data protection procedure.


  1. Allocation of responsibilities

The goal is to make storage security a fully-fledged feature of the IT security architecture. Even if the company decides that the responsibility for backup or storage security rests within the storage team, it must nevertheless integrate any safety measures in this area with task to secure the rest of the infrastructure. This integration will contribute to the establishment of in-depth protection. It is also advisable to share responsibility for extremely sensitive data. It’s therefore better to ensure that the person authorizing access is not the same as the person responsible for enforcement.


  1. Assessment of storage risks in the area of ​​IT security

Managers must review each step of their backup methodology to identify security vulnerabilities. Can an administrator secretly make copies of backup tapes? Are they stored in boxes accessible to everyone? Is there a rigorous end-to-end monitoring chain for backup tapes? If critical data is backed up and transported, vulnerabilities of this nature could make it easy prey. If the risk analysis reveals many vulnerabilities, the company must seriously question the encryption of its data.


  1. Development of an information protection program that guarantees the security of company data, at all times, wherever they are

Multi-level protection should be adopted by taking existing best practices for the data network in order to apply to the storage network, while adding specific layers adapted to the characteristics of the archived data, for example:

  • Authentication: application of multi-level authentication techniques and anti-spoofing (anti-identity or address spoofing).
    • Authorizations: access rights according to roles and responsibilities (as opposed to total administrative access).

It is imperative to duplicate backup tapes because it is never good to depend on a single copy of the data. Despite the longevity of the bands, they are still exposed to environmental and physical damage. A common practice is to perform nightly backups and then store these off-site tapes without any verification. Recommended best practices include duplicating backup tapes and then storing offsite copies.

Magnetic tapes remain the preferred storage mode for backups because they are economical and offer sufficient capacity to back up an entire operating system on a single cartridge. When stored properly, archival tapes have a lifetime of more than 30 years, making them an exceptionally reliable storage medium.


  1. Communication of the procedure to be applied with regard to the protection and security of information

Once the procedure for protecting and manipulating sensitive data has been defined, it is important to ensure that those responsible for their safety are informed and trained. Safety rules are the most important aspect of assigning responsibilities. Functional managers need to be aware of risks, countermeasures and costs.

Data loss and intellectual property theft affect the entire enterprise, not just the IT department. As such, the Director of Security must undertake a data security approach by training the different functional frameworks in the risks, threats and potential harms arising from security breaches, as well as the cost of the various possible countermeasures in this area. In this way, company executives can raise awareness about the cost / benefit of investments in data security.


  1. Implementation and testing of Data Protection and Security Plan

Securing data is not about technology but about procedure. This is why it is essential to test the procedure. In addition, as the growth of the company is accompanied by an evolution in security and data protection needs, IT security practices must also evolve.

Once the complete security plan has been developed, defined and communicated to the concerned team, only then it’s the right time to implement it. IT team must ensure the implementation of the tools, technologies and methodologies necessary for the classification of information. New technologies may be required to classify information or label it with metadata so that it is backed up according to appropriate rules and procedures.

Once in place, the procedure must be tested, both concerning backup and restore. The test is to introduce, into the process, any possible and imaginable danger, whether it is the loss of a tape or a server, network problems, equipment or filing of data or any other scenario which could affect the company’s performance.

It is advisable to carry out tests with personnel who are less familiar with the procedure, to ensure that it can nevertheless be applied without difficulty in the absence of the usual supervisor (due to illness, holidays or departure).

How Artificial Intelligence is impacting the Tourism Sector?

Artificial intelligence has existed for several years, yet we witness that it is now reaching another dimension, thanks to more powerful computers and the multiplication of available data. By its capacity to raise all sectors of activity, it is undeniable that it represents a great interest for Tourism. With the wealth of data available to professionals, today there are a multitude of technologies and recommendations applications, real time chatbot and personalized concierge services. The aim is to simplify the work of tourism industry professionals so that they can return to their core business with powerful tools and technologies and make an important difference in terms of profit and customer satisfaction. But the question one must ask is how to use Artificial Intelligence wisely?

Artificial Intelligence and Tourism

The first point: if we think about tourism future, in terms of types of travelers, its certain that we will be dealing with several categories of profiles, which may overlap. Our first category, for example, will be constituted, as is the case today, of travelers wishing to disconnect radically from their “everyday” environment in order to immerse themselves in another culture. And this, by all possible means.

Others, more vigilant, are the second category that will want to practice simple trips, without risks, even without surprises, neither good nor bad. This does not exclude, on the contrary, the survival of an adventure tourism.

For, the last profile, the purpose of a journey will be less the destination than the experience that one can have there. They will travel to learn how to cook a rare product or to learn a new activity based on information provided by our peers. The purpose of their travel will be based on learning.

Whatever the size of the group and the number of establishments it counts, it seems to me that we are moving towards a world where the tourist supply will continue to increase, thanks to two levers: new destinations and new traveler’s profiles. It will be required to be extremely flexible towards the customer’s expectations, to which one must respond with the development of innovative services to accompany them at each stage of their journey before, during and after their stay .


How can AI added value be applied to Tourism?
By Customization. And that is what profoundly changes the ins and outs. Rather than bringing the same experience to the same type of travel, artificial intelligence offers the possibility of matching the desires, habits, preferences of the tourist with the proposed product. “Artificial intelligence makes a data pool meaningful. By learning what the customer is looking for, buying, and loving, it makes it possible to generate customized and targeted offers that are more likely to be converted into a purchase.

Today, cognitive systems are capable of interacting in natural language, they can process a multitude of structured and unstructured data, developed with geo-localized content, and learn from each interaction. These systems will rapidly become essential in the development of strategic topics for the industry, such as “smarter destination”, on the personalization of the customer experience and its loyalty, as well as on the provision of management, analysis and Marketing, all this by using BigData. These services will be an asset to make the whole of the tourism sector more efficient by helping the actors and structures in place.


How far can artificial intelligence push the tourism industry?
Not up to replace the human. Robots are used for certain tasks, but not as a replacement for humans, although, in the long term, this could happen, but the problem of the energy that robots consume must be solved. Referring to artificial intelligence is often trying to compare with human intelligence, it’s important to notice that the aim of cognitive systems is NOT to replace human beings; Robots cannot reason or learn as a human being can do. They serve the needs and imagination of tourism professionals who, with the help of partners, take benefit from them thanks to their knowledge.


Like I’ve mentioned above that AI isn’t a new technology, we have been interested init since the 50/60 years, but if today the subject seems quite new, it is because the data is only available now. Tourism, like all industries, is digitized and gives a potentiality of data where one can apply machine learning. So AI is a revolution in progress, to the extent that it leads to new ways of thinking about the supplier’s offer.

Understanding the #Blockchain Economic Revolution

The Blockchain is a revolution that is undoubtedly leading to a complete overhaul of economic activity. It’s not a simple geek trend but still most people have absolutely no idea what the blockchain stands for. It’s essential to distinguish clearly the differences between bitcoin, crypto-currency and the breakthrough of technology underlying below the nameà the #Blockchain. You must know that there are several types of blockchains on the market, and bitcoin is another version of it which got huge success in recent years.


To be short, #Blockchain is an information storage and transmission technology that is transparent, secure and operates without a central control unit. Transactions between network users are grouped in blocks. Each block is validated by the nodes of the network called “minors”, according to the techniques that depend on the type of block. This process puts everything on trust between the market players without going through a central authority. It’s an open source system where each link in the chain offers autonomous legitimacy. The decentralized nature of the chain, coupled with its security and transparency, suggests a revolution of an unimaginable enigma. The fields of opportunity open far beyond those who have access to the monetary sector.

Understanding the Blockchain Economic Revolution


In fact, it is a revolution, as has been in human history, the advent of commerce. When individuals bought and sold their products face to face, with the handshake, the trust was established. Second, globalization has created new needs. Entities have been set up to protect sellers and buyers. Laws and legal services have developed around financial exchanges. Each market had to have intermediaries at the grass-roots level, without it being possible to assess or quantify a degree of trust between people. What changes with the blockchain is not only its decentralized aspect, but also absence of intermediates. Blockchains could replace most “trusted third parties” centralized by distributed computing systems. More than that, many observers highlight the blockchain as an alternative to any back-office systems in the banking sector. It would also help eradicate corruption in global supply chains.


The boom of the Internet offers some good indications on how the blockchain could develop. The Internet has reduced communication and distribution costs. For ex, the cost of a WhatsApp message is much cheaper than an SMS. Just as the cost of a software or an online platform is cheaper than having to sell its products through a physical store. The marginal operating costs, thanks to the Web, have been reduced to almost zero. This has caused profound changes in the telecommunication, media and software markets. The Blockchains result allowed to limit all marginal transaction costs close to 0.


Blockchains are a low-cost market disruptor for any business that acts as an intermediate in market. They allow things that have never been possible by using existing infrastructure and financial resources. We can exchange things that were not previously considered assets. It can be data, our reputation or unused power. The possibilities are as vast as they are unimaginable, but that does not mean that each type of element will be profitable for a company.


It is preferable not to dwell first on the technological aspect. It is much better to focus on the root of your customer’s problem. Successful businesses know how to identify, what is missing or a concern to their prospects, and know how to solve it. Blockchain technology is valuable in a setting where data has to be shared and edited by many unapproved parties. That is the infrastructure. The added value comes from the services that are built around it, with applications or modules.

Currently we are in the infrastructure market phase, there are still standards or platforms to democratize blockchain technology. In the near future, thanks to the crazy pace of development of this system, it will be easier for developers and entrepreneurs to use the blockchain on a daily basis. As easily as the MySQL or MongoDB databases we use today. Once the infrastructure stage is over, the evolution of blockchains will really become exciting. The infrastructure will be a huge database on which companies will be able to operate all kinds of connected objects or devices. The connected devices will collect data, blockchains will ensure, shear and process data; Artificial intelligence applications will automate activities.


Just imagine these farms where the product is grown and picked up by robots, delivered at home via drones, with a connected refrigerator that alerts us when we need something from there. An artificial intelligence system manages presets objectives to perfectly match the supply and demand. Blockchains are much more than just a bitcoin. They are the real building blocks of our future world.

The Impact and Challenges of Artificial Intelligence for Next-Gen Enterprises

Artificial Intelligence (AI) is not a new phenomenon. It continues to develop and its applications are already very present in our personal daily life (gaming, robotics, connected objects …), arousing as much enthusiasm as fear. This complex concept gained its success in the science fiction world. Although AI is still calling for a more or less fantasized imagination, it is an integral part of reality, and it can be found in many services, systems and applications.


What can be the role of artificial intelligence in the enterprise of the future? Will AI make organizations smarter? These are the main questions that have motivated big companies, with the objective of analyzing and anticipating the impacts of this revolution in progress. In this post, I’ll be discussing organizational, legal and ethical issues related to the governance of artificial intelligence in large enterprises.


A critical factor in adapting the company to the evolutions and challenges of AI environment is to rethink relationship with the company’s stakeholders, and in particular with the customer. It doesn’t mean that one must highlight that “the customer is important” but to emphasize the interaction with the customer. With that being said, client exists only through the interest and interactions developed with them.

So, the question companies should ask is how can they develop a successful interaction with the help of artificial intelligence? What does this mean concretely in terms of channels, content, customer knowledge and, above all, commitment to the customer?


Some companies have “Innovation and prospective” unit to carry out an analysis and a reflection of AI impact within the company. This is to take the step without neglecting the employees who are at the center of the subject. These cells allow the sharing of ideas. As the applications of artificial intelligence within the company are diverse, such as increase of human expertise through virtual assistants; optimization of certain products and services; new perspectives in research and development through the evolution of self-learning programs. The objective of this unit is to exchange in order to make the prospective, in a participatory way, through conferences, roundtables, written reports or scenarios, depending on the choice of the structures.


The Impact of Artificial Intelligence for Enterprises


Artificial intelligence technologies are already anchored in our daily lives. These technological advances intensely question the managerial and organizational practices around innovation in large companies. Many conducted surveys demonstrate that in general, companies do not have a dedicated budget for artificial intelligence. Nevertheless, there are either investment projects or resources that can be allocated to artificial intelligence teams integrated into the wider data teams. Be that as it may, the subject of artificial intelligence is present in large enterprises; It may remain theoretical but may also be the subject of initial experiments, notably concerning the predictive algorithms. Artificial intelligence does not fundamentally change everything in the company, it will rather “increase” performance, automating or perfecting certain processes and / or operations.


Benefits for organizations:


Today, artificial intelligence already generates many benefits for organizations, notably by:

  • Responding to Big Data issues; Artificial intelligence relies in large part of the search and mass analysis of data from which it can learn;
  • Increasing human decision-making expertise, online help assistant: a Hong Kong-based company, Deep Knowledge Venture (DKV), possesses, for example, artificial intelligence at its board of directors. Vital (Validating Investment Tool for Advancing Life Sciences) who makes investment recommendations and is also entitled to vote;
  • Optimizing services and products: improving customer knowledge, decision-making and operational processes;
  • Strengthening systems security: in the area of ​​cybersecurity, artificial intelligence becomes a structuring element of IT infrastructures, in order to secure networks. Automatic recognition is well established for the detection of fraud, and experts are under way to create algorithms that will identify threats that human brains and traditional security mechanisms fail to recognize.
  • Helping to make discoveries: some companies in the field of health analyze all the scientific publications related to a particular area of ​​research, which allows them to look for new properties, new molecules.




The challenges for large companies are numerous. Starting with cultural and organizational changes. As noted in the Telecom Foundation’s Watchbook No. 8: “The craze for artificial intelligences has been accelerated by the availability of AI capabilities in the form of APIs (on the one hand, Vision or predictive), and the source code of the platforms of Machine Learning released by major Internet operators, on the other hand “.

These technology facilitators will keep pushing companies to become APIs (APIs) in order to optimize their resources. It is therefore necessary to understand the world of APIs in this transversal, cross-enterprise approach, which is not without posing a number of challenges for large companies. To succeed one must develop the fallowing roadmap strategy:

  • Build stronger relationships with clients;
  • Optimize internal processes;
  • Accelerate the development of new developments.


To conclude I’ll say that we live a golden age of artificial intelligence, boosted by the increasing interest of web giants for the stakes of Big Data. The first AI investors are indeed the pure players of the internet and the main players of the software. The movement is launched, and it is our responsibility to anticipate the effects of this revolution on large companies.