Virtualization and security

Many organizations think about the security implications after implementing new technology. Virtualization offers many benefits that make IT architectures easier to sell. Virtualization can save money, increase business efficiency, reduce maintenance downtime without impacting business or causing disruption, and it can do more work with less hardware. Of course, there are many ways to implement virtualization in IT sectors using network virtualization, storage virtualization, server virtualization and desktop virtualization. Each type can contain some type of security threat. There are many solutions for types of virtualization. The important thing is that virtualization can improve security, but it cannot prevent all attacks.

Virtualization can be used in many ways and requires appropriate security measures for each situation. This article will discuss ways that virtualization can be used to increase the security of your Windows environment.

Below are a few ways to minimize risk and increase security with virtualization:

Sandboxing

“Sandboxing” is a security mechanism for separating running programs that is often used to run untrusted code or programs from untrusted third parties, vendors and websites. The main purpose of sandboxing is to improve virtualization security by isolating the application to protect against external malware, malicious viruses, applications that stop execution, etc. etc. If you have an unstable or untrusted application, just put it in a virtual machine so that it doesn’t affect the rest of the system.

Sometimes you can get a malicious attack on your application when you run it in a browser, so it is always advisable to run your programs in a virtual machine. Sandbox technology is closely related to virtualization. Virtual computing offers some of the benefits of sandboxing without having to pay premium prices for a new machine. A virtual machine has a connection to the Internet rather than the company’s local network, so it protects the operating system and programs from viruses or malicious attacks on the virtual machine.

Server Virtualization

Server virtualization is server resource masking, which helps divide a physical server into smaller virtual servers to maximize resources. The administrator divides the physical server into multiple virtual environments. These days, official records are often stolen from servers by hackers. Server virtualization allows small virtual servers to run their own operating systems and reboot independently. Virtualized servers are used to identify and isolate unstable applications as well as compromised applications.

This type of virtualization is mostly used on web servers that provide low-cost web hosting services. Server usage manages the complex details of server resources, increasing utilization rates and maintaining capacity. A virtualized server makes it easier to detect malicious viruses or malicious elements by protecting the server, virtual machines and the entire network.

The advantage of using server virtualization is that it creates a layer of hardware abstraction between x86 hardware and the operating system. It also reduces the density of virtual servers relative to physical server hardware. Server virtualization creates an image of the server that makes it easy to tell if the server is not working properly.

Network Virtualization

Network virtualization is a combination of hardware and software network resources and combines network functions into a single virtual network. With network virtualization, virtual networks minimize the impact of malware when a system becomes infected. Network virtualization creates logical virtual networks out of the underlying network hardware for better integration with virtual environments.

An important feature of network virtualization is isolation. It allows you to dynamically create multiple virtual networks that coexist in isolation to deploy configurable end-to-end services on the fly. They are managed in these virtual networks for users by sharing and using network resources obtained from infrastructure providers.

Another major feature of network virtualization is segmentation, in which the network is divided into subnets, a process that results in improved performance by minimizing local traffic on the network and increasing security by making the internal structure of the network invisible to the outside. Network virtualization is also used to create a virtualized infrastructure to support complex requirements by creating single instances of software applications serving multiple clients.

Security Hypervisor

The term “hypervisor” refers to small software or hardware that creates and runs virtual machines. The machine that contains the hypervisor is called the host machine. Hypervisor security provides hypervisor-enabled virtualization, including development, deployment, provisioning, and management. (Read more about virtualization security: tips for preventing virtual machine hyperjumps.)

There are a few key security recommendations for hypervisors:

• Install vendor-issued hypervisor updates. Most hypervisors will have automatic software updates and will install updates when detected.
• Secure with thin hypervisors, which makes deployment easy and efficient to run with minimal computational effort. It also reduces the chance of malicious code attacking the hypervisor.
• Do not connect unused physical hardware to the host system or unused network cards to any network. Sometimes disks are used to back up data, so unused devices should be disabled unless they are actively used for backups.
• If you don’t need the file sharing service or any other service between the guest OS and the host OS, disable all unnecessary services.
• There must be security between guest operating systems so that they can communicate. Non-virtualized environments should be handled by security features such as firewalls, network devices, etc. Д.

Desktop Virtualization

Desktop virtualization allows images to be created, modified or deleted and separates the desktop environment from the physical computer that is used to access it. The administrator can easily manage employee computers and protect them from unauthorized access or virus intrusion. It provides more security for the user by providing a guest OS image for the desktop environment and does not allow data to be copied or saved to a drive other than the server, making desktop virtualization a more secure option for networking.

Security Infrastructure

A virtualized information infrastructure allows you to control access to resources and provides visibility to ensure proper information processing. All activities in the computing environment must be monitored through the infrastructure.

Virtual switches

A virtual switch is software that provides security using isolation, control and content inspection methods between virtual machines and allows one virtual machine to communicate with another.

This prevents an attack from occurring between switches. The primary purpose of a virtual switch is to provide a network connection to communicate with virtual machines and applications on a virtual network with a physical network.

Guest OS security

This is the operating system on the virtual machine, and it is used to host the primary operating system and share resources with other virtual machines on the same host. Virtualization allows you to share information with the OS using disks or folders created by network drives. It contains some security features such as systematic update of the guest OS, backup of virtual disks and application of the same policy to non-virtualized computers.

High availability and disaster recovery

These days, the most important thing is to keep data and services available in the IT sector. Virtualization reduces the time and cost of disaster recovery by backing up data to a large, unique file, which saves time when reinstalling the OS and restoring data. This allows you to restore the virtual machine to any host that meets the power requirements, and also provides the ability to recover quickly after a physical failure.

Server Isolation

Virtualization uses server isolation mainly for business purposes. Multiple servers can run on a single virtual machine without virtualization, but there is a risk in having multiple servers on a single server. Virtualization allows you to run multiple servers on the same machine, isolating the servers from each other as they run in different virtual machines.

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In addition, cloud computing is an industry with a global market value of nearly $500 billion that continues to grow. Experts predict that the global cloud computing market will exceed $1.5 trillion by 2030.

Most companies are already using cloud computing technology to some degree. There are many reasons why they are important to businesses, whether cloud services are used for big data storage and analytics, providing web services, scaling infrastructure, or disaster recovery.

Key characteristics of cloud computing:

• On-demand provisioning of resources. User defines what capacities and for what purposes he needs.
• Payment for resources upon use.
• Network access, which makes remote management and use possible.
• Scalability – users can add and remove resources on demand.
• Fault tolerance through the use of a distributed network of remote servers.

In this article we’ll look at how this helps businesses streamline processes and implement new solutions.

Cloud services

The following types of cloud computing are distinguished:

• Private cloud – a company uses its own infrastructure to organize Cloud services for internal use.
• Public cloud – services are provided by large service providers.
• Hybrid cloud – the business uses a bundle of private and public Cloud services.
• Multicloud – the business uses services from multiple service providers, linking them into a single ecosystem.

Clouds use different cloud deployment models

• IaaS – Infrastructure as a Service. Customers get computing resources: servers, networks, storage.
• PaaS – “platform as a service”. Customers get customized tools for different tasks – for example, DBMS, machine learning environment.
• SaaS – “software as a service.” Customers get out-of-the-box applications to work with – e.g., CRM, email, website builders.
• XaaS – “everything as a service.” It’s a general term that encompasses new products, tools and technology. For example, vendors already offer workstations as a service (DaaS), artificial intelligence as a service (AIaaS).

Depending on the deployment model, users will have different levels of control and responsibility.

Infrastructure as a Service

With IaaS, the customer is responsible for managing everything from the operating system and software to the applications and data. The provider performs other tasks such as virtualization, server maintenance, data storage, and network configuration. Customers are charged based on the amount of resources they use.

The clearest example of IaaS is cloud servers. The service provider builds, configures, and provides the customer with a virtual computer. You connect to it over the Internet and use it however you want – for example, setting up an environment to produce a web application.

Some companies use IaaS as part of their infrastructure to store non-critical data and applications in the cloud. This offloads local storage.

Other companies use IaaS as part of a disaster recovery plan. Cloud providers store redundant backups in data centers. Even if there’s a problem in one of these data centers, user data isn’t affected-the copy stays elsewhere.

Platform as a Service

PaaS cloud computing model solutions give customers a place to develop, test and host their own applications. Customers are responsible for managing the data and software, and the service provider handles the rest.

For example, ready-to-run MySQL and PostgreSQL databases are available on Timeweb Cloud. The provider provides the ability to manage them through a Public API or dashboard interface, with all the necessary software already installed. At the same time, the service provider is responsible for hardware setup, software updates, and database administration.

With PaaS solutions, you don’t have to worry about software updates, operating systems, or storage needs. PaaS customers only pay for the computing resources used.
Software as a Service

In the SaaS model, a customer purchases a license to use an application that is hosted by a provider.

SaaS solutions are suitable for small companies that lack the financial or IT resources to deploy the best solutions. Thanks to this model, there is no need to worry about the cost of equipment and the work of specialists. Examples of SaaS are website builders, VPN services, CRM systems.

The benefits of the cloud

The cloud helps businesses save money. Organizations are reducing the amount of physical infrastructure and eliminating the tedious work associated with managing data centers. Cloud solutions also help employees work efficiently wherever they are – in the office, at home, in a café, or anywhere else.

The benefits of cloud computing:

• Help reduce IT infrastructure costs.
• Provide remote access to work tools.
• Accelerate innovation and deployment.
• Help securely store data.
• Simplify infrastructure management.

Let’s look at them in detail.

Optimize IT infrastructure budget

Data centers that a company maintains on its own are expensive. So are the professionals who take care of the equipment. The cloud helps reduce those costs by eliminating the need to purchase and maintain expensive infrastructure.

With less physical hardware, technicians don’t have to spend hours setting up servers, updating software and performing other tedious maintenance tasks. Instead, business leaders redirect the attention of the IT department to other important tasks.

The pay-as-you-go model helps companies be flexible. You can deploy solutions that were once too expensive or complicated to use on their own.

The cloud also provides flexibility in decision-making. Let’s say you run an online store. On Black Friday, its traffic increases 15 times. To handle this surge, you’ll need resources to handle the extra traffic.

In the past, that would have meant constantly having to pay for backup capacity that would be needed for a short period of time. But cloud computing has changed that. With them, as traffic increases, resources will automatically scale and adapt to the spike in activity.

With cloud computing, you only pay for what you actually use. This allows you to meet your needs without spending money on your own server hardware and everything associated with it.

By the way, in their official channel Timeweb Cloud assembled a community of experts who talk about IT trends, share useful instructions and even invite you to work with them.

Anytime, Anywhere Access

With the cloud, you have on-demand access to the files and applications that run the business from virtually anywhere in the world. Employees remain productive regardless of location. This approach also helps ensure a consistent user experience across company branches.

Innovation

Innovation is directly related to business growth. Using legacy technology prevents an organization from both experimenting with new products and deploying those solutions at a scalable level.

Using the cloud as the foundation of infrastructure leads to increased productivity, lower costs and increased flexibility. For example, in the world of Internet of Things (IoT) product development, companies are innovating at a pace that is only possible with the cloud.

Accelerating deployment

One of the goals of DevOps is to improve the quality and speed of digital product deployment. This is achieved through an agile communication process that helps traditionally isolated teams work together throughout the development cycle.

Adding new features while maintaining stability is another reason organizations move to the DevOps model. If a company doesn’t use cloud technology in conjunction with DevOps, it misses the chance to accelerate product development, and it ignores improvements in business operations.

Improved security

Cloud service providers are enterprise-level organizations that follow rigorous data protection standards. They devote resources to developing advanced security protocols and comply with regulatory requirements – for example, storing American citizens’ data.

With this approach, businesses don’t think about how to “land” customer data so they can operate without breaking the law. Companies pay to solve problems that would take noticeably more money and time to solve on their own.

Reducing the complexity of managing infrastructure

Executives and business owners want their products to evolve. This poses a dilemma: What to spend more resources on – researching and creating new solutions or managing and protecting current infrastructure?

Service providers are responsible for securing and managing the IT infrastructure, allowing organizations to dedicate resources to operational scalability in other areas.

For example, if an organization moves to the cloud, it has more resources to devote to business development, improving service quality, or testing new growth strategies.

How businesses use cloud computing

The following features of cloud computing make it useful for businesses:

• High deployment speed.
• Data preservation.
• Easy sharing of information between different services.
• High level of security.
• Scalability.

Below are common situations in which clouds help make business processes simple, efficient and flexible.

Software testing and development

If you’ve ever developed your own digital product, you know how time-consuming and expensive the process can be. Installation and configuration of hardware and/or software is required, as well as ongoing training of the employees involved.

Creating a website or adding complex features to an existing project can take months. This puts the business at a disadvantage in today’s economy. Continuous integration and delivery mechanisms, which are also available as cloud services, help reduce costs. Using them makes development and testing faster, easier, and cheaper.

Big Data Analytics

Some companies collect data to open up new lines of business, while others collect data to solve complex issues. It’s a time-consuming and costly process. But it can be optimized.

Another advantage of cloud computing is pay-as-you-go pricing. This means that you only pay for resources when they work for the business.

Data backup and archiving

Traditional data backup solutions have proven effective at storing information for long periods of time. But security concerns remain. Data can be stolen, accidentally or intentionally deleted.

Pre-packaged solutions from cloud providers make backup easy and reduce the risk of data loss. You use them to send copies to remote storage systems. This gives you peace of mind that your data will be safe. Damage to one copy will not affect the condition of other backup storage.

File Storage

Data can be stored and accessed in a variety of ways. It can be a computer hard drive, an external device, network file sharing, USB devices.

Remote storage in the clouds is also becoming popular. They allow for inexpensive storage of significant amounts of data. Users have secure access and room to scale storage.

Providers provide several types of storage for different purposes. For example, block storage is used as OS boot partitions, as well as for storing files in DBMS, analytics, and telemetry. File storages are used to create remote file systems. Object storages are suitable for economical placement of big data, media files, backups, static files with instant access via API or web-interface.

Communicating

Cloud computing is also used for enterprise communication methods such as calendars and email. Messages and data that employees send and receive are not only stored on computers, but also in the cloud. This allows them to be accessed online from any device.

Business processes

You’ve already enabled the cloud if you’re using company management tools such as CRM – customer relationship management systems.

The software-as-a-service (SaaS) model, which often relies on cloud computing paradigms, is used to deliver these enterprise applications to users. Applications in the cloud make it easier to protect and manage a company’s critical resources.

Conclusion

Over the past decade, cloud computing has grown into a giant industry. As artificial intelligence, machine learning, and edge computing emerge across industries, the Cloud Computing market will continue to grow.

The growth of computing power and the emergence of new features for end users will have a direct impact on businesses as well. Cloud services help organizations scale, maintain flexibility, and focus efforts on business operations rather than managing complex infrastructure.

By outsourcing the development, testing, deployment and management of a specialized solution to an experienced vendor, the organization can free up resources to focus on developing and launching new areas.

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The purpose of the study to identify the advantages and limitations in the activities of enterprises in the use of Big Data technologies, with a special emphasis on assessing the extent of their impact on innovation management and economic efficiency of the enterprises under consideration.

Research material and methods

The growth of the big data industry has accelerated the process of industrial modernization and structural change in the economy. With the advent of the big data era, some industries have gradually shifted their attention to a development model that combines traditional industries and big data industries. In traditional industries, the use of big data techniques to explore new needs and research and development of new materials can both reduce R&D costs and improve the accuracy of research and development of new products.

Regardless of industry specifics, every company has two areas for applying big data analytics technologies, internal and external interactions.

Within the framework of external interaction research, of interest is the accumulated customer experience, namely understanding customers through social network analysis, their social status, age, preferences, etc., information about regions, market segments, satisfaction with a product or service, ways of promotion, as well as ways of contact, etc. External interactions can also include everything that is related to the business model and structure of the business and its interaction with the outside world, such as suppliers, partners and sales channels.

The study of internal interaction is aimed at studying and optimizing company’s operational processes, the purpose of which is to increase productivity not only of equipment, but also of employees, as well as rational use of resources. It is worth noting that the main competitive advantage enterprises will be able to obtain, not so much at the expense of data collection, as at the expense of the ability to quickly extract useful information from the total sheer volume of big data generated.

Let’s consider the advantages of applying big data in the management of an enterprise:

• First, it helps improve decision-making. The big data platform has a real-time data resource collection function and can extract key information based on fast processing and analysis of massive data that can better meet the immediate needs of enterprises.
• Second, it promotes more and more diverse decision-making tools.
• Third, it enhances the credibility and quality of the decisions made, because they rely on a large statistical base of source information, which greatly strengthens the credibility of decision-making schemes.
• Fourth, Big Data technologies also guide a company’s operational strategy.

Assessing the areas of influence of Big Data technologies on management decision-making, the following should be emphasized:

1) Impact on the management decision-making environment.

Big data environment based on cloud computing has a great impact on the process of collecting information for enterprise decision-making, making plans, controlling their execution and evaluation of plans, which has led to significant changes in the decision-making environment. At the same time, enterprise management solutions in terms of big data demonstrate clear data-driven functions, that is, data-driven business development, providing proactive and reliable guidance for business improvement and innovation.

2) Impact on management decision makers.

The advancement and application of big data is completely undermining the traditional empirical decision-making model, and the bulk of the decision-making process has expanded from top management to direct. Decision makers, can flexibly use technologies such as machine learning, statistical analysis and distributed processing to extract valuable data from massive data.

3) Influencing the management decision-making process Organization.

The involvement of all employees in the decision-making process leads to a redistribution of decision-making authority of the enterprise, and the change in decision-making authority will ultimately affect the organizational structure of corporate governance and the culture of decision-making. In a big-data decision-making environment, the main problem the organizational structure must solve is how to allocate decision-making authority and choose the right decision-making method.

4) Impact on management decision-making technology.

In the context of big data, data is mainly in the form of data streams. It is necessary to use intelligent analysis technology to explore the potential relationship between data fragments and get the real information. Therefore, enterprises need to accelerate technological innovation and use the latest technology to serve the management decision-making process.

Speaking of the impact of big data on enterprise economic performance, there is no doubt that in many areas, the application of Big Data technologies can help increase productivity, create additional value and expand revenue streams. Because big data has the potential to improve efficiency and effectiveness, companies can not only produce more products at a lower cost, but also add value to products and services.

However, when examining the extent to which big data affects a company’s level of economic efficiency, it’s important that management decisions are maximized to achieve a few imperative benchmarks. First, Big Data technologies are a way to understand the customer by examining all their preferences. In addition, today’s customers are very different from the old ones. The rise of big data allows them to research products, understand the volume of consumption and explore their customer benefits before they buy them. Using big data, interactions between manufacturers and consumers can be personalized, thereby producing consumer-driven products and providing customer-centric services. And based on the data, it is possible to find social and business forms suitable for enterprise development environments, use this data to analyze and understand user and customer attitudes toward products, and accurately discover and interpret many new user needs and behaviors.

Secondly, with the help of big data technology, companies can collect and analyze resource extraction, specific conditions and reserve allocation needed in the enterprise mode to form an enterprise-level resource allocation map, similar to an “electronic map”. The different benefits will be point-to-point data and graphical mapping, so that plant managers can view their own plants more intuitively and make better use of various existing and potential resources. Without big data, it will be difficult to find correlations between behaviors that were once thought to be completely unrelated.

Third, Big Data technologies can be used to plan production technologies. Big data not only changes the way data is aggregated, but also affects the production and delivery of enterprise products and services. By using data to plan production architectures and processes, they can not only help them discover methods of combining values that are not known in traditional data, but also provide appropriate, customized solutions to detailed combining problems for enterprises. The function of big data virtualization greatly reduces enterprise business risks, allows the enterprise to give appropriate deterministic answers before production or service starts, and allows production and service orientation.

Fourth, through the correlation analysis of big data, according to the overlap and coincidence of data from different brand markets, the direction of the company’s method will become intuitive and easy to identify, and will be more confident in brand promotion, choice of location and strategic approach. In addition, big data technology can contribute to the intelligent operation of enterprises. Intelligent enterprise operations management mainly aims at dynamic communication between the enterprise and users, and provides users with more dynamic and acceptable quality services based on user feedback. With the help of Internet channels, modern enterprises can better communicate with users, users can use the Internet to use more equipment resources and get better services through timely feedback of their experience. On the one hand, it guarantees the efficiency of enterprise performance management; on the other hand, it also provides a powerful guarantee for user experience management and user consumption prediction.

Fifth, through the calculation of big data, social information data, customer interaction data, the enterprise can conduct horizontal design and segmentation of brand information. Business intelligence software Yixin BI tools and retail experience can also help companies better understand the process of increasing sales and eliminating unnecessary costs.

Sixth, big data creates differentiated benefits that are mostly reflected at the strategic level of the business model. Big data can help companies improve their strategic decision-making capabilities. Through data analytics, companies can quickly formulate strategic plans that align with the market. By streamlining processes to improve cost efficiency, big data can allow companies to obtain market and customer information more intuitively and quickly, and market research and customer demand studies can be faster and more efficient.

However, when talking about the undeniable benefits of applying Big Data technologies to modern businesses, we should not forget about the existing limitations of applying these technologies in today’s environment. Today, all industries and sectors are exposed to and using Big Data to varying degrees. However, many businesses or organizations that implement Big Data are not successful. There are still many limitations and challenges in applying big data within the enterprise. According to the study, there are common problems with failed big data implementations. The most typical and serious problems are the following.

The problem of in-house data processing. Today, most companies can only process structured data, and structured data makes up only 15% of total data, and technology for processing more than 85% of semi-structured and unstructured data is inadequate. Mature, improved data processing and analysis technologies are a challenge for enterprises. Newly generated data around the world is increasing by 40% annually. The total volume of global information may be doubling every two years. The increase in utilization rate is less than 5%, and 90% of existing digital content is unstructured.

The shape of big data is important in determining the tools to process and make decisions about visualizing the face of a decision. Moreover, much of the information about a company is stored in multiple databases, with data difficult to share and correlate between different business modules. Achieving correlation and integration of data information between business platforms, is also a major challenge facing businesses. Business intelligence is a major technology in the era of big data, but it is not widespread and is only used in industries closely related to IT (finance, telecommunications, networks, e-commerce, etc.).

In addition, in the era of big data, companies are faced with huge volumes of data, the protection of which becomes extremely difficult. This data includes not only business secrets, but also private confidentiality. Some unscrupulous “hackers” use it to damage the interests of businesses. Enterprises are dealing with information security issues, which is another major problem.

Also a limitation associated with the problems of data processing within the enterprise can be attributed to the rather high cost of solutions, which are often accompanied by a lack of quick results. Enterprises, especially mid-sized businesses, do not adhere to the market development strategy and limit their budget expenditures on information technology. Big data tools are compute-intensive and expensive to purchase, install and use. Business owners want to see a return on investment in the short term, but such systems as big data and their application is a long-term process, and it is impossible to say for sure that the use of such technologies can produce the expected result quickly. The use of big data technologies refers to innovative projects, and as we know they are difficult to assess the effectiveness of investment and a guaranteed result, so not all companies are eager to implement them in their operational processes. However if we talk about companies close to the public sector, things are easier there, due to the general focus of the state on the development of such technologies and the allocation of budgets there is based on a slightly different understanding of the process.

The problem of data storage formation within the enterprise. The most important challenge for enterprises when launching big data technologies is data fragmentation. In many enterprises, especially large ones, data is often located in different departments, respectively stored in different repositories, and the data processing technology in different departments may also be different, which leads to the inability of the company to access its own data. If businesses can’t take advantage of that data in a timely manner, its value is lost.

The problem of “sluggish” enterprise management systems. Currently, only a few high-tech enterprises place a high value on the use of big data in decision-making. Most business leaders don’t realize the value of big data. Some business leaders believe that big data is just data entry and collation, and its use cannot directly benefit an enterprise. However, it is known that the more data a business has and the more effectively it integrates with each other, the more competitive the business is.

Although some companies collect and analyze data, their managers still follow the traditional management model and follow too closely the cause-and-effect relationships. In the era of big data, we’re not chasing causality, we’re correlating. In massive data, as long as the factors that have more to do with improving corporate profits are dug out, it can provide strategic support for managing corporate decisions to some degree. This requires corporate executives to have a deep understanding, which creates a new challenge for the thinking style of management decision makers.

The problem of considering the impact of big data on the quality and timeliness of enterprise management decisions. Making managerial decisions in the enterprise is becoming increasingly complex, it is difficult to analyze the value of information related to decision-making, which to a certain extent determines the level of development of system competencies of decision-makers. At the same time it should be noted that, for example, there is still a deficit of specialists in the Russian market, there is no formed professional community, which would perform the function of informing the market from inside. That is why many companies train their professional staff independently, but these measures are still not enough. It should be taken into account that the speed of corporate decision-making is not as fast as market changes. In addition, enterprises face the problem of diversification of decision-making subjects. In this case, enterprises need to establish a hierarchical decision management system to improve the scientific level of management.

The problem of providing data storage. Today’s big data is information about the phenomena under study from different sources, different standards, large volumes of data, multiple structural forms and real-time requirements. These challenges undoubtedly increase the complexity of data collection and integration, especially in terms of data pre-processing and filtering. If the filtering is too fine, it is easy to filter out useful information, and the level of detail in the screening is too coarse, and the desired analysis effect cannot be achieved. Problems in data security and privacy issues arise from a lack of one hundred percent customer confidence in big data technology in the area of data privacy and personal information. In general, it is fueled by the lack of full-fledged legal and regulatory regulation in the area of big data.

Forming directions for improving the processes of using big data technology, the following should be emphasized:

First, it is necessary to improve the security of big data collection, use and storage. The issue of protecting data privacy caused by enterprise management is becoming more and more important. Verizon’s 2015 data breach survey report shows that more than half of the top 500 companies have been hit by “hacking” attacks. In response to this problem, enterprises must build big data silos, monitor information security in real time, and streamline decision-making procedures. The national government should also improve the legal and regulatory framework for the existence of Big Data and increase penalties for misconduct with it.

Second, professional talent needs to be developed. In the era of Big Data, the problem of talent shortage is gradually becoming prominent. In academic studies, McAfeeA and others have pointed out that talent is an important factor influencing corporate management decisions. In this regard, enterprises can choose highly qualified professionals for continuing education through internal training; government agencies should encourage colleges to focus on training talent in this field; colleges and universities should also change the traditional education model and focus on innovation and practical linkages in the curriculum system to ensure that there are enough qualified professionals.

Third, the data model must be unified and systematized. For example, all data are stored in one database. Big data analysis is very different from traditional data analysis. Big data platforms and analysis will be used to digitize the fragmented market, and then customer data will quickly build decision data so that companies can track and respond quickly to changes in the market environment. Creating a single data model can help companies integrate different businesses and form an actionable circle of operations.

Fourth, an open data sharing system must be created. Future big data companies must have a common mission. Enterprise data is often limited, and it often requires someone to share it to enrich their form of data. This requires businesses not only to be open-minded, but also to be able to share data.

Fifth, it is necessary to view big data as a strategic resource. Data is like oil, and it is inexhaustible oil, placed in a cornucopia if stored. Businesses with a strategic vision can judge the value of data in the future and are willing to spend some cost to store some potentially valuable data.

Sixth, a system to support and encourage the use of big data needs to be developed and implemented at the state level. Data processing technology has always been seen as an important factor influencing the widespread use of big data. Without stable and secure data processing technology, it will not be able to exploit the enormous commercial value it contains. Therefore, it is worth paying attention to the development of appropriate technologies for data analysis and processing. The government should actively encourage related technologies and pay attention to research and development of data processing technologies in universities, enterprises and research organizations.

Conclusion

The technological changes taking place within the global digital transformation, which are taking place on a global scale, bring a huge number of opportunities into the activities of companies and people’s lives. The use of big data is one part of the digital transformation. The world is changing and will never be the same again. The only question is how quickly the process or business model in which a company exists will become obsolete. In the course of this process, the boundaries of industries are being erased and what used to be the company’s advantage may lose significance altogether, and instead of existing ones, completely new areas will emerge that were previously unnoticed; it is these shadow growth areas that the company can identify through the use of big data technologies.

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The new era has brought with it a new perspective on all areas of business. Modern technology is affecting the entire cycle of production, sales, customer relationships and within companies themselves. Those who will not keep up with global changes risk falling by the wayside.

Analysts are unanimously saying that the Internet of Things will have a key impact on business in this decade. Several studies predict that by 2020 there will be about 50 billion smart devices in the world (now – 6.4 billion). IDC specifies that the IoT market will reach $1.7 trillion by the same year, with $737 billion by the end of 2016. Tellingly, much of the investment in the Internet of Things last year touched manufacturing, trucking and energy systems.

58% of executives consider IoT implementation a strategic issue for their company, and almost all – 95% – will launch related projects in the next three years, IDC predicts. The reason for this focus on IoT is a clear improvement in the operational efficiency of the business.

Simple sensors and deep analysis will bring profits

In key industries, the Internet of Things boils down to installing sensors on a specific thing (a car, a building or any object), quickly obtaining data from these sensors and analyzing it quickly. This makes it possible to have up-to-date information about the context of a thing in dynamics, and advanced analysis tools provide recommendations for optimizing the processes in which it is involved. The output gives the company the ability to create personalized offers for its customers and optimize the business process based on real-world circumstances.

It is not for nothing that the Internet of Things is actively developing in the industrial sector. There it helps to reduce equipment downtime, reduce (or even completely eliminate) problems with equipment operation, increase the speed of production and its continuity, reduce problems with suppliers, and so on. The upshot of all this is not only improved margins, but also the ability to invest new funds and resources in innovation.

New business processes will generate new ways to communicate

But it’s not just the production cycle that will be affected by the changes. The development of the Internet of Things will lead to the fact that selling a product will no longer be the final link in the chain of business processes of an enterprise. Thanks to sensors that will be able to transmit information about the state of the product, a new function will be added – the provision of services related to the process of its operation.

“Equipment vendors are bringing new product lines to the market that are already equipped with IoT sensors. For example, many companies that make compressors and pumps already offer such machines that will notify the owner themselves when they need routine repairs or filter gauging. This is achieved with a much deeper analysis than the classic vibration level monitoring,” explains Vasily Nomokonov.

The product-service combination does not only mean additional profits related to the after-sales service. Comprehensive monitoring of the operation of each of the manufactured refrigerators will help to understand how to eliminate or minimize the most frequent reasons for breakdowns at the production stage. In fact, a new channel of communication between the manufacturer and the consumer is being created, which will make possible proactive diagnosis and repair, remote software updates and sale of additional products and services. All of this will be based on predictive analytics and big data analytics. The next step will be to replace products with services.

The issue of using the Internet of Things is relevant not only for industry, but also for retail. Researchers at McKinsey claim that the introduction of IoT in this business segment will lead to serious economic benefits on a global scale: from $410 billion to $1.2 trillion in additional annual profits by 2025. The search for ways to apply these technologies in retail is still ongoing, but already today the Internet of Things is in demand in inventory management, payment processing, supply chain control and some other areas.

Pictures of a futuristic future, repeatedly outlined by screenwriters and embodied in dozens of films, such as refrigerators that order their own food from a specific supermarket or smart homes that prepare breakfast by the time the owner wakes up, will also one day become a reality. This concept will also find economic application. In a smart building, dozens of control systems coordinate: electricity, water, heat, ventilation, and even elevators. Calculations of various companies show that a smart house can save up to 30% of expenses only on energy saving by means of balanced energy consumption only when it is necessary and only in the necessary quantity.

The quest for profit will force a rethinking of the IT landscape

Against the background of reducing the cost of infrastructure necessary for the introduction of the Internet of Things, a fundamental revision of all business processes and the giants of the market, and new players will begin: starting with a rethinking of the principle of pricing and ending with the rules of ROI, which will have to include still poorly calculated indicators such as degree of loyalty.

However, the implementation of sensors alone will not defeat the competition. The large number of connected devices brings an unprecedented amount of new data. Their value and volume are nothing compared to what was used to hide behind the concept of big data a couple of years ago. On the one hand, it brings the ability to accurately track changes in context. But on the other hand, it requires a new level of capabilities from the company’s IT infrastructure.

First and foremost, we are talking about the need to use cloud technology. The logic here is simple: such a huge amount of data, which the era of Internet of Things will bring with it, must not only be stored somewhere, but also done cheaply. At the same time, the processing and analysis of all this information should take place not only on the principle of storage and further multifaceted analysis, but also in real time, or as close to it as possible. Such opportunities now provide only cloud technology, and there is no alternative.

Market giants are moving to the cloud

In isolated form, of course, the technology of Internet of Things will not create benefits for the enterprise. In addition, we should not forget that the issue of competent IT-infrastructure and resource management is also a security issue. The lack of a clear strategy (which is a business issue) and competent data flow management (for which IT departments should be responsible) will likely lead to a decrease in operational efficiency and, consequently, to a complete fiasco. And if the first point is solely in the competence of the company’s management, as for the second, the world-famous vendors already have a lot to offer clients.

As usual, market giants are happy to use the increased capabilities of vendors. For example, General Electric has deployed the Predix platform in the Microsoft Azure cloud, which enables intelligent management of industrial equipment using IoT technologies. For one company-owner, more than 50,000 miles of power transmission infrastructure was laid out, served by drones that feed data into an analytics application. Not only did this avoid hiring 2,000 employees, but it also sped up the process of identifying and troubleshooting problems. Calculations prove that the potential annual savings are in the millions of dollars. To link industrial data to business processes and analytics, Predix integrates with the Azure IoT Suite and Cortana Intelligence Suite, as well as a line of business applications — Office 365, Dynamics 365 and Power BI.

The cloud experience of these and other companies confirms the general trend of moving to these kinds of services. IDC forecasts indicate that in just 18 months most organizations’ IT infrastructures will be fully hosted in the cloud. And by 2018, the typical IT department will be working with predominantly cloud-based applications and platforms rather than traditional in-house tools.

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Back in 2008, Nicholas Carr, an American journalist who specializes in high-level analysis of technological innovations, published a book known as “The Great Transition. What’s in store for the cloud revolution” . This study is essentially a panegyric to the concept of IaaS (Infrastructure-as-a-Service; infrastructure as a service). Carr looks at the possibility of providing computing capacity as a utility service. At the outset, he mentions Mike Sullivan, one of the founders of VeriCenter, who resigned as chairman of Microsoft in 1999 to pursue his idea. It was to free businesses from having to maintain IT infrastructure. His business model was based on the idea of providing data processing services for a modest fee. That way, the company only had to provide its employees with access to the Web from the simplest and cheapest devices. The computing capacity, according to Sullivan’s idea, had to be on the side of the service provider.

Why do businesses need the cloud at all?

With cloud technology, businesses have the ability to scale quickly. This means that computing power can grow quickly and painlessly and the time to implement certain innovations (for example, from developing applications to run in the cloud to integrating them into business processes) is greatly reduced. Moreover, it will cost less. IT infrastructure requires substantial expenses from business on technicians’ salary, on license fees that give the right to use certain software, on buying or renting physical “hardware” – servers, network equipment, etc. In the case of clouds, the company receives the same as a separate service for much less money.
This is exactly what Carr was talking about.

Small companies can make very serious savings with clouds – they don’t pay for all the infrastructure needed to build their IT system, i.e. physical hardware, software, employees. They only spend on subscription fees to the IaaS provider. This is all the more advantageous because, for smaller companies, there are clouds with pre-installed software designed for specific work scenarios. For example, for companies providing transportation services, there will be software to calculate routes, monitor fuel consumption, GPS tracking vehicles, etc.

Large companies also benefit from cloud technology – they can use it to ensure continuity of operations, migration of virtual machines between physical servers, and easy management of the entire infrastructure. But in the first case, we are talking, as a rule, about public clouds, and in the second – about private clouds.

Thanks to clouds, it is possible to use different physical equipment. Servers of different generations and manufacturers are combined into one cluster; you can combine data centers with different geographical locations – if one data center is attacked by DDoS, the data will not suffer – they are synchronized in advance with the second, backup. Thus, it is enough to simply switch traffic from one data center to the other. And the user will not notice anything.

In general, the cloud for the company means savings through the efficient use of physical resources. Think about the virtual office. Virtualization allows a significant increase in efficiency in the use of server capacity.

Clouds for private users

Cloud technology can be of interest both for companies and individuals.

We have already mentioned the former. And private users need the cloud, in case they have light projects and need “light” services, in other words, those, which do not consume a lot of resources. For example, a server for testing software under development or an e-mail server. A typical user would definitely find it more profitable to pay for a cloud account than to rent or buy a separate server, which requires configuration and maintenance, but certainly will not be loaded to half of its capacity. It is cheaper and easier to use the cloud, because the administration of “iron” requires both special skills and time.

Corporate customers also, as we’ve already mentioned, appreciate all the advantages of cloud solutions. Both private and public. It is no coincidence that the demand for Google services for business is steadily growing.

Who does not need the cloud?

Cloud technology will not be in demand in companies that have static tasks, whose activities are strictly regulated. These are companies that do not have rapidly changing processes and do not expect dynamic growth. Take, for example, a construction site – why does it need clouds? Let’s assume that air conditioning, access control, security, video surveillance systems are provided at the site. But there were 100 cameras before they were commissioned, and they will still be there in five years. In this case, the introduction of the cloud is not only economically inefficient, but also creates additional vulnerabilities in terms of security.

Or, for example, it does not make sense to use clouds in some defense projects, because it is in their interest to minimize security risks, and the load of such projects is clearly calculated in advance and specific equipment is selected for it. Deploying and maintaining clouds requires additional infrastructure, capacity and manpower. Why do you need it when it is more economically profitable to do the project without it?

Although, of course, it all depends on the situation and the specific task at hand. For example, the Israeli army actively participates in the life of the OpenStack community, their military experts speak at summits. You have to think, for a reason. So their commanders see an opportunity to benefit from this technology.

What kind of companies need cloud technology?

Cloud technology is needed by fast-growing companies. These are all software, IT companies, service projects, telecom operators, the media…

For example, IT developers need clouds because resources and technology needed to perform their tasks, as well as the number and content of tasks themselves, can not always be predicted in advance. Clouds enable developers to use a variety of solutions. In addition, IT professionals can automate the allocation of cloud resources, which will significantly reduce the waiting time for developers, for the product – the time of release, the timing of bringing it to market, and thus the waiting time for profits for management, business owners and investors. The latter, as Mitch Wagner, editor of the online industry publication Light Reading told my friend and colleague Ilya Stechkin, “It’s important to see the real benefit of technology for their business: how it can help improve metrics such as customer satisfaction, business profitability, ROI. People are interested in being able to cut costs. There are popular topics, such as the Internet of Things. How emerging technologies help bring that concept to fruition.”

With companies that have projected growth in computing capacity, the case is more complicated – whether they need the cloud should be decided on a case-by-case basis. Another thing is that in today’s environment, every company is a bit of a software company. The same Wagner told a favorite story – about a company that manufactures fitness equipment and supplies it to gyms and hotels: “Even they came up with the idea that it would be good to give users the ability to log in to the simulator, so that it automatically adjusts to their parameters. And here they are, customers of a cloud service provider.

Conclusion

Here is a strange thing: almost every modern business needs the cloud. The more conservative a business is, the less it needs cloud technology. Do businesses want to “stake out the field” in the future or do they prefer to live in the present? If they do, it makes sense to ask a different question: “How exactly can a business use cloud services?” Even builders, in partnership with a provider, can offer cloud services to residents as part of the smart home concept. What’s more, if they don’t do so in the very near future, the liquidity of their properties will tend toward zero. After all, a “smart” city will need not only “smart” cars, but also “smart” houses. And the future will need smart people and efficient businesses. But that is a different story – not just about the Internet of Things.

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