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Effective methods to avoid Data loss and Data leakage

In the age of digitization and technological developments such as Industry 4.0, companies are confronted with ever-increasing amounts of data that need to be stored, analyzed, and evaluated according to business activity/priorities. Even though data is playing an increasingly significant role as a resource, it also comes along with huge security challenges. It is becoming increasingly lucrative for hackers to steal data to use it for a competitive advantage or even to monetize stolen data. When the data is stolen, companies lose a lot of money. To counteract this, data security, i.e., the protection of data from unauthorized access, is of crucial importance.

 

The protection of a company’s valuable data from unauthorized access is the task of data loss prevention (DLP) tools. Data Loss Prevention (DLP) solutions have been an integral part of the IT security strategy of many companies for more than ten years now. It is one of the most used technologies, by worldwide companies, to prevent the loss of sensitive data.  The aim is to protect any form of data against manipulation, disclosure, loss, and other forms of threats.

 

Various countermeasures can be taken to minimize the loss of a company due to data loss & to protect critical business assets. When implementing them, it is important to know what value the respective data generates for the company. Data that leads to high financial losses in the event of damage must be given the highest priority in the implementation of data loss prevention.

 

  • Backups: The most used method to counteract data loss are backups. These do not directly prevent the data loss process, but if data is lost, it can at least be recovered. Thus, it is important that the backups are carried out on a regular basis. They must also be regularly checked for recoverability and malware.

 

  • Permission Restrictions: Another technique to limit accidental data loss by employees is to restrict permissions/access to valuable files. The permission layer supports the company’s data privacy by protecting access to restricted data. Also, if an employee does not have permission to delete a file cannot delete it either.

 

  • Training and antivirus programs: There are several measures that must be taken to protect against viruses. First, the employees should be trained so that a virus has no chance of being invited into the system. However, since errors can still occur here, network anti-virus programs must be installed on every computer, every server, and every communication interface. It makes sense not to rely on just one provider here to be able to intercept several viruses.

 

  • Data leakage prevention: Analogous to data loss prevention, data must be inventoried and categorized. It ensures that users do not send sensitive or critical information outside the corporate network. Business confidential and critical information is classified and protected so that unauthorized users cannot accidentally or maliciously share data, which would put the organization at risk.

 

  • E-mail scanning: To prevent unauthorized internal sending of confidential documents, companies can prevent outgoing e-mails with attachments. However, since this cannot be practically implemented in everyday life, it makes sense to scan outgoing e-mails and only deliver them if previously set rules for sending have been observed.

 

  • Training and antivirus programs: Finally, incoming electronic communication can also be checked. This is to ensure that no Trojan or other form of malicious software can nest in the corporate network. Incoming documents in particular offer opportunities for this. Anti-virus programs must be used here to prevent a virus from being loaded. Employees also need to be trained so that fraudulent e-mails don’t stand a chance.

Data loss prevention & data leakage prevention are two main data security strategies that are adopted by worldwide companies. Companies that store sensitive and critical data, such as personal data, should place a greater focus on data leakage prevention. Operators of universally available assets, on the other hand, should consider data loss prevention as a priority.

2021: Intelligent Data Management Will Enable the Future of Your Business

2021 Intelligent Data Management Will Enable the Future of Your Business

The EU’s GDPR has a major impact on the data privacy ecosystem. The regulation is an essential step to strengthen individuals’ / Business fundamental rights in the digital era we are living in. After two years of the introduction of the GDPR, the following question still arises: What will 2021 bring in terms of data management and data protection? According to Gartner, by 2023, 65% of the world’s population will have its personal data covered under some kind of modern privacy regulations.

 

It’s predicted that the technology for the preparation, control and administration of data will become much more efficient so that data is available more quickly and reliably. With the focus on foundational components of data integration, data governance, and data preparation the effectiveness of big data projects can be improved. With the right technology, data management can also drive enormous business value and support digital transformation. It’ll certainly help organizations to better manage the availability, usability, integrity, and security of their enterprise data.

 

Data has evolved over the years and will continue to evolve. Today’s organizations are data-centric; they accumulate enormous amounts of information in many different formats. Those who are unprepared to deal with the amount of data will be left behind compared to those ready to welcome all business opportunities that big data has to offer. Here below are 5 main areas that play a huge role in the good preparation of data management.

 

  • Data orchestration

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A frequently used term in the sales and marketing domain for whom data has a high priority as their data is the foundation of just about everything, they do. Simply put, data orchestration is the automation of data-driven processes that includes data preparation, making decisions based on that data, and taking actions based on those decisions. Data and API integration and data movement need to grow together to support all kinds of DataOps (data operations) methods. It’s a process that often spans across many different systems, departments, and types of data. It also requires a combination of different technologies that ensure a central data flow. This is the only way to orchestrate data-related activities – across different locations, on-premise or in the cloud.

 

  • Data discovery

In this process, relevant data insights are uncovering and transferred to the business users who need them. A comprehensive directory for searching, making available, saving, and interpreting data and other objects is becoming more and more important. Advanced Analytics enables the automation of mundane data management tasks and frees up resources to actually generate added value from the data. With the right use of data discovery tools, even the non-IT staff can easily access complex data sets and draw out the information they need. This process of knowledge discovery can be performed by anyone, without the technical know-how that was required in the past.

 

  • Data preparation

“Data preparation is one of the most difficult and time-consuming challenges facing business users of BI and data discovery tools, as well as advanced analytics platforms, Rita Sallam – Research Vice-President at Gartner.” However Artificial intelligence (AI) has solved this problem by creating the basis for advanced data transformation and by enabling automatic cleansing and consolidation of data. This enables users without any prior technical knowledge to use data.

 

  • Model management

Model Management technologies help organizations consistently and safely in developing, validating, delivering, and monitoring models that create a competitive advantage. The focus is to put the central control of all models in a single application instead of the separate management of individual models. In view of the fact that many analytical models never go into production or quickly become obsolete (model decay), it is important that companies can quickly and easily register new models, adapt, track, evaluate, publish, regulate and document them.  Previously, model management referred just to monitoring production models, but it’s beyond that. Models drive new breakthroughs and operational improvements for businesses. According to a McKinsey study, organizations that leveraged models extensively showed a 7.5% profit margin advantage over their peers, whereas those that did not use models had a 2.5% profit margin deficit compared to their peers.

 

  • Data governance

“A data governance plan, supported by effective technology, is a driving force to help document the basis for lawful processing.” Data protection laws require companies to have data governance programs that provide “data privacy by default” and define policies, roles, and responsibilities for the access, management, security, and use of personal data. If they do not proactively advance standards and programs, they not only run the risk of contradicting legal requirements but they could also lose the trust of their partners/customers. With the use of advanced analytics and artificial intelligence in decision-making, they are therefore even more challenged to bring transparency to the algorithms.

 

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COVID19: Digitization Recovery Plan for 2021

 

To help repair the economic and social damage caused by the coronavirus pandemic, digitization will continue to boost in 2021. All those lock-down measures in response to the coronavirus outbreak have frozen the economic activity in certain sectors and harshly disrupted others, which resulted in worldwide unemployment and bankruptcies. In order to overcome all restrictions in the contactless world, citizens and businesses are relying on the internet and connectivity as social and economic activities became more digital.

 

What is now very clear, is that COVID-19 has accelerated digitalization. IT decision-makers are under pressure with using new technologies to modernize legacy processes and recognize and implement new business model innovation opportunities, more than ever before. All digital business transformations must begin and end with a crisis recovery plan and must reinforce companies’ foundations for a modern and more sustainable future. Additionally, as customers are getting more used to doing things digitally. This opens up opportunities for businesses to introduce new products and to reduce costs. The Belgian government has also agreed on an investment package of 4,3 billion EUR in digitalization, sustainability, education, health care, R&D, 5G, mobility.

 

Here below are the top digital transformation trends that will shape 2021.

 

  • Businesses’ journey to the cloud will accelerate in order to digitize quickly and effectively in the response of COVID-19. Across industries, this acceleration will result in their digital business transformation for long-term growth and profitability. This migration of infrastructure and applications to the cloud will enable leaders to innovate quickly, by significantly reducing development and solution delivery cycles, empowering operational efficiency through cost optimization, and benefiting from real-time accessibility of data.

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  • Companies will invest in 5G in order to enhance the experience of workforce mobility (remote work), videoconferencing, and digital collaboration. This adoption is motivated by the need for more bandwidth, faster speeds, reliable and resilient connectivity as businesses cannot afford to be disconnected. 5G will boost the company’s existing network by providing diverse connectivity, to ensure scalability for growth and business continuity with a faster response time, delivering a quality user experience subsequently increasing productivity and customer service. The IEEE 2020 Global Survey of CIOs and CTOs surveyed 350 CIOs or CTOs in the US, China, UK, India, and Brazil from Sept. 21-Oct. 9, 2020, revealed that 52% have accelerated 5G adoption. Doubtlessly, with all these earlier mentioned benefits, the value and adoption of 5G will become increasingly mainstream in 2021.  Additionally, by 2030, 5G modules are expected to account for almost 30 percent of total B2B 5G IoT module revenues.
  • Worldwide industries will turn their attention to robot resilience in 2021. Organizations will accelerate automation projects more critically. With intelligent automation projects, ROI is realized instantaneously, offsetting the upfront investment. Automation (RPA) allows organizations to automate certain types of work processes to reduce the time spent on costly manual tasks and reallocate resources elsewhere. Software robots will automate the work of most people by taking the unpredictable, dreary, and monotonous tasks, faster and with fewer mistakes, while human capital resources will be assigned to higher-value tasks or to fill critical gaps.
  • COVID-19 has forced companies all over the world to adapt to and embrace remote work. With the safety concerns that continue to grow, companies are negotiating remote work policies as their business strategy for the long term. Even though many companies succeeded in the rapid transitions to remote work, they are realizing that remote work is here to stay. Companies and employees are realizing the significant benefits of remote work, such as increased flexibility, autonomy and productivity, better work and life balance, lowered business expenses, etc. according to a Gartner study, 74% of CFOs and Finance Leaders say that they will move at least 5% of their employees to remote working permanently post-pandemic, another 25% of the participants say they will move 10% of their workforce to remote working permanently.
  • Countries around the world are working on more comprehensive and accessible electronic health records. The access of the patient to his medical record by electronic means is part of the eHealth Action Plan validated by all the Belgian ministers of health. By simply asking your healthcare provider to activate the option, you can access to the contents of your documents. The online medical record allows the patient to have their health record at any time. Additionally, the AI healthcare market is expected to exceed $34 billion by 2025 as artificial intelligence is already playing a huge role in the digital transformation of healthcare. In fact, AI is being used currently for AI-assisted robotic surgery, assist pathologists in making more accurate diagnoses and treat illness, detect cancer in its earliest stages and subsequently develop new treatments, and doctors are using AI-enhanced microscopes to scan for harmful bacteria’s in blood samples at a faster rate than is possible using manual scanning.

 

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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.

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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.

 

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