Three ways to improve IT support By Leveraging Data

Introduction

An excellent way to improve IT remote support is through the intelligent use of data. Here are some techniques to help make this happen, and why it is important.

Information Technology departments are increasingly turning to data to help them manage the increasing complexity of their IT infrastructure. For both system administrators and support engineers, to maintain an extensive endpoint panorama composed of different operating systems, software versions and configurations on each computer, the server throughout the organization has become a major challenge.

Until recently, it was not uncommon for a company to spend up to 75% of its IT budget just to maintain existing IT operations.

However, companies that direct their IT support through digital transformation obtain benefits by being able to manage their infrastructure more strategically and at the same time improve the quality of the provision of IT services.

As a result, they are not only experiencing a reduction in resolution time but also in the cost of servicing their infrastructure.

Forget the traditional KPIs of the help desk

Today, most companies know the importance of tracking their IT support performance with the KPIs of the right help desk. It is true that the first response, the rate of resolution, the use of the agent, customer satisfaction and the cost of the ticket matter because they give an idea of how the resources are used and the quality of the services rendered. But, by themselves, they do not address the real problem.

The main challenge for IT support is dealing with the frustration of humans interacting with technology. In other words, IT departments can not reduce their resolution time if they still depend on their end users for triage and access to critical system information.

In fact, an interaction between a technician and an end user that begins with "what is the name of your computer?" Or "what is your IP address?" It usually starts with the left foot.

1. Implementation of the single version of the truth for IT remote support

The only version of truth (SVOT) is a concept of business intelligence defined as the only view of the data that everyone agrees on is real and reliable information. In general, it is compiled from different data sources on various systems. Its purpose is to facilitate decision making.

With regard to business operations and change management, the single version of the truth is often credited with improving communication, reducing the potential for conflict, and a better end-to-end user experience.

When it comes to IT support, you do not need to be an expert to know that it is very necessary. So, except in theory, how does this apply?

It starts with the use of the correct remote access tool, which provides the following three key features:

• Real-time detection of computers connected to the user based on a user name or identification search.

• A 360-view of the end-user IT profile covering systems, devices, Active Directory and software

• Easy access to real-time statistics such as CPU and memory usage, disk activity.

Getting rid of fragmented tools has its obvious benefits. Moving technicians and engineers of all levels on the same platform not only encourages collaboration but also helps provide a seamless experience. On the one hand, technicians no longer need to remotely control a workstation to see what is wrong. Instead, they can work in the background without interrupting the end user.

2. Collecting data to generate actionable information

In short, you can not endorse or guarantee what you do not know you have. Companies should be in the habit of collecting data on their terminals to generate actionable reports as a way to get out of the fire and start planning strategically.

It is good practice to start with a simple resource inventory report that includes:

• Asset Name

• Function description

• IP address

• MAC address

• Model / Manufacturer

•Serial number

• Network connectivity

Ports and protocol (s) used

• Firmware version and operating system

However, there are many other ways in which aggregate data can help IT departments.

For example, before applying patches to a series of Windows machines, it is useful to check the operating system version, the latest patch installed, and the power state of each terminal. When reviewing the consolidated report on discovery ideas, engineers can design the appropriate remediation plan and measure the success of their campaign with respect to the initial data set.

For root cause analysis purposes, IT departments can also store a daily snapshot of the end-user IT profile or final scenario. After a security incident, such as a ransomware attack, they can analyze the data to understand when the problem first came up, and perhaps infer why they were not included.

3. Optimize IT support with IT process automation

Automating IT processes is another way to leverage data to improve delivery of IT services.

With ITPA, engineers can create a workflow to automate a series of actions and dispatch their execution to multiple computers at the same time. This is useful for implementing software or patches, as well as for automating repetitive system management tasks.

In addition, a workflow can be activated as soon as the system detects when a computer or server changes its configuration or status. As a result, IT departments can increase their agility by solving a situation before it becomes a problem.

"Check, detect, and fix workflows" is great for applying IT compliance. They can be used for various purposes to automatically remedy a missing patch to remove blacklisted applications.

Process Automation IT benefits companies by increasing the accuracy and speed of delivery of their IT support services. More importantly, it helps mitigate the risk.

Digital Transformation of IT Services: Choose the Right Remote IT Support Solution

There is much alternative remote access software such as Team Viewer, Goverlan, LogMeIn and Bomgar that can help an IT department with its digital transformation. The key to success is finding the solution that is easy to implement and that meets the needs of your business.

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Benefit of Artificial Intelligence in Finance Industry

Artificial intelligence can benefit the financial sector and even transform the field permanently. This is how artificial and financial intelligence can make a difference.

Artificial intelligence (AI) has already been associated with the video game industry, but financial institutions are beginning to realize that this technology can do much for them. Perhaps the most common use of artificial intelligence modules in the banking industry involves calculating interest rates and residential values. Smart software can request, through historical price charts, the development of a model that more accurately predicts the financial future, taking into account several factors. It is these additional factors that indicate that artificial intelligence can benefit the financial sector.

Mining of Big Data Banks

Historically, pricing models have considered, for example, the seasonal demand to determine the future value of any commodity. Banks have been collecting much more information than this for some time, but only a recent boost to data monetization has forced developers to look at countless other factors. 

Solutions based on artificial intelligence determine the value of physical and investment products, noting the following:

•   As demand for one type of product influences another
•  The price fluctuations of the different investment products among each other.   
• Thegeographical location of consumers making financial decisions
•  Commercial allocation preferences of different investors
•  The trade patterns that shape hourly prices
•  The volatility of prices traded on an open exchange
•  The relative costs of goods and services in different markets

Banks and brokerages have compiled this information for decades, but so far have not had many ways to analyze it. AI modules are carrying large data elements like these and looking for opportunities. In addition, new IoT devices installed at ATM stations help identify patterns of how consumers deposit and withdraw funds. This can help reduce the risk of cash collapse caused by an excess of sudden withdrawal orders granted to the individual physical bank.

AI and the world of creditors

Most consumers are already familiar with the concept of checking their annual credit score. Each time an institution decides to see the credit score of an individual, it leaves a mark called search. Companies can get someone's score when they are applying for a loan or applying for a job.

Soft benefits, such as when a consumer makes an annual credit check while making their taxes, have little influence on a person's overall score. Difficult queries, such as those caused by a person applying for a new mortgage, are much more serious. While sophisticated mathematical models exist to determine the severity of any credit drawdown, they are often left to a high degree of interpretation.

Credit agencies are progressively introducing new scorecard technology, which takes into account potential risk and past performance, to apply their own rules more fairly to consumers. To avoid extending a credit line to someone who can default on a loan, financial institutions, in turn, are building credit risk models based on artificial intelligence. These models use predictive thinking along with self-learning neural networks to determine the total risk of any specific loan.

Neural networks learn the same way people do. Using a database stored in a virtualized file system, risk models can prevent the repetition of past errors. Consumers can receive better rates if a database does not find indications that it is a risky investment.

Simplifying compliance tasks

News services continue to report on these trends in the financial sector. However, computer security experts believe that regulatory and compliance tasks will be the area in which AI algorithms will further change the financial industry. To provide operators with value, any IA needs to have a secure digital backbone network. The data collected for the analysis should also be anonymous in many jurisdictions.

New laws such as the General Data Protection Regulation (GDPR) require that companies be much more open about how they are using customer data. AI software can optimize the process of erasing any personally identifiable information from stored data while automating the reporting process.

From the consumer's point of view, the biggest change will probably come in the form of greater account protections. The same predictive analytics technology that is extracting big data storage systems for actionable financial patterns will also occasionally notice irregularities. As these programs continue to undermine, they will improve by detecting problems and alerting consumers to any errors in their accounts. As a result, regular banking customers will soon be able to take advantage of the benefits of AI technology as well as the institution.

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Big Data, IoT and Block Chain: Benefits of Trending Trio

Introduction

Big Data, IoT and blockchain are changing the world as we know it. So what if we combined their benefits more often?

As technology advances around the world have reached lightning fast, technologies such as big data, IoT and blockchain have turned their individual identity into an asset for the various industries around the world. At that time, almost every technological person knows each of them independently and many also know their uses and benefits combined, but for novice readers, we will see the summary of each of them.

Big data

As its name suggests, Big Data is the information that is in great volume. Data can be of various types, ie structured data (database, in order), unstructured data (traditional row and column storage) or semi-structured data (unstructured data with some organizational properties).

There are many industries that can benefit effectively from large data analysis solutions such as Health, Retail - Consumer, Financial Services, Web and Digital Media, Telecommunications, e-commerce and customer service, etc. where data is in volume Massive - so the storage and Big Data Management tools should run more scans. In addition, there are several tools on the market that use Biggest Data, that is, Hadoop, Apache Spark / Storm, Ceph, Google Big Query, etc.

IoT (Internet of Things)

In simple words, IoT is the 'active thing' connected to the Internet. These "Active Things" can be Sensors, Devices, Appliances, Vehicles, etc. They collect and send information over the Internet through a server or receive information and act accordingly or they can do both. In the next few days, the requirement will be of the third type: they collect information and send, and also receive information and react accordingly. There are thousands of applications of these devices in theory that will soon become a reality. In addition, this type of application will be huge in many industries and the data transferred will be huge, managed by Big Data applications. Some examples can be considered as IoT for Buildings (Houses, Offices and Parking lots, etc.), IoT in Agriculture, IoT in Automobiles and IoT in the Health Sector, and so on.

How Big Data can improve the combination of multiplayer gamesBlockchain Technology

The Blockchain technology came to light with the origins of Bitcoin. But over time, it has been discovered that the same technology can be used for many things (various databases, which have some value), as well as simply making financial transactions safely. Blockchain technology has a distributed architecture for the database system. It does not have a centralized data address, but the data is replicated as part of the 'Blocks' on several machines (called 'nodes') on the Internet, so it is very difficult to hack anyone.

In the Blockchain database, each record with some key (hash code) is known as a "Block". It contains details such as the timestamp of a specific transaction and the previous "Block" key in the chain, which is also replicated across multiple locations/nodes.

Therefore, it is almost impossible to manipulate these blocks since there is not a single data source and if someone tries to change in a single block, that change will make the subsequent blocks irrelevant, so that a certain manipulated block will be discarded from Blockchain by others us (users on the network). In simple terms, since this algorithm has a distributed architecture and the same information is replicated in several places, it is practically impossible to make changes at each location/node, so this architecture is very secure.

Concern about Big Data and IoT Data Security, its centralized architecture and cost

Big Data services in some sectors can be very sensitive and should be safe and private, ie banks, defence, health, etc. Therefore, the main concern of the owners or stakeholders for this Big Data is the security of their data. However, there are many technologies available for Big Data security that can be discussed during the big data query, but there are some serious shortcomings of such techniques and Data is vulnerable.

In a similar practice, the data received and sent between IoT devices are very sensitive and must be immune, ie in surveillance, urban traffic controls, in the defence sector, etc. The IoT application is so large that multiple devices detect, send, receive, and act. the greater the data production and the control.

The other concern with managing Big Data produced is its traditional centralized architecture. Many of the devices in the IoT application also send data and receive it from a central server (one or more). Although this type of architecture for data management is vulnerable and not totally secure since the data source is unique or limited. In addition, the cost of managing your central servers will increase day by day by accumulating data every day. So there must be some fundamental change in the management of such data.

Solution through Blockchain technology

There are some legacy features and benefits inherent in the operation of Blockchain technology, through which we can secure Big Data and IoT data (at a low cost) in a way that is practically impossible to breach. Through Blockchain's distributed architecture, the biggest concern in securing and managing growing data can be solved, since no central database is required.

The data is validated and replicated across multiple network nodes, which is almost impossible to attack. In the coming years, there will be an automation boom, in which billions of IoT devices will manage many tasks. Administering central servers can also be avoided and data can be transferred over the Blockchain secure network.

This will definitely increase the Data Transition Time (TAT), as well as the security of such data since the devices are not connected to a single location. In addition, the main advantage will be the reduction in the maintenance cost of these billion IoT devices, since the manufacturers will not need any central repository to update or update the firmware of the said device.

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Legal And Ethical issues of Big Data

Introduction

As data technology advances, the ethical challenges of big data increase and generate questions that society has never before faced.

Data is now one of the most precious resources in our world, and in recent years, companies have been learning how to use it to be more successful and profitable. Big Data, a term used to refer to the use of the analysis of large data sets to provide useful information, is not only available to large corporations with large budgets. Companies of all sizes participate in the action to improve their commercialization, reduce costs and be more efficient. As a result, the ethical challenges of big data have begun to emerge.

Big Data is useful in almost any industry, but it has great potential in the health field to reduce waste and improve the patient experience. Although there are many advantages in the use of data in healthcare, there are some challenges that are holding back widespread adoption in the industry. New legal and ethical challenges are affecting the future of Big Data in healthcare, and also in other industries.

New Big Data Risks

It is no secret that the electronic storage of patient data has led to a large number of new problems in recent years. Cyber-attacks, which lead to data breaches, have compromised the privacy of millions of patients in the United States. In 2017 alone, 477 infractions were identified in health organizations, affecting 5.6 million patient records.

Beyond blatant theft, electronic records provide health care providers with better research tools, allowing predictive analytics to identify patterns in large data sets. While this is fantastic for medical research and treatment, there are ethical challenges on how to use the data without harming patients. All health businesses need to adopt better ways to implement safety and keep patient records private.

Technology, although it has helped companies evolve and has received more analysis to work with, has also opened an even larger number of claims for several claims. Everyone is extremely cautious about violating laws and bad practices because they do not want a lawsuit. Problems related to big data and security arise in many fields, and you need to be aware of the best practices in whatever field you are in.

The Benefits of Big Data in Health Services

Health is one of the biggest industries affected by the big date. So what are the great data that healthcare has to justify the risks? Many things. While there are certainly problems and concerns with the big date, it is usually turning businesses around, especially medical care.

If you've waited for what seemed an eternity in your doctor's waiting room, Big Data can help you accurately predict the right time for patients and schedule appointments as appropriate. However, the big date can do more in the hospital than shortening waiting times: it can save lives and reduce emergency room visits. Reporting real-time data can have a positive impact on patient outcomes, helping providers make decisions in a way that benefits patients.

Human error is responsible for many deaths, especially when drugs are mixed. Large data can be used to cross-reference possible interactions and provide warnings when errors occur. Mass data also has the potential to improve public health as a whole, since the analyzes can track the health of communities and populations and more easily observe health trends. For these benefits to be maximized, transparency in data is essential.

Avoid lawsuits in the medical sector

Doctors and hospitals cannot simply think of providing care, unfortunately, they should also consider the possibility of lawsuits. Every year, there are more than 17,000 cases of professional negligence in the United States. With the benefits of Big Data, how can hospitals use this powerful tool while protecting themselves from litigation?

Unfortunately, there is no way for providers and organizations to avoid a demand in all situations. Medical malpractice occurs when mistakes are often made by carelessness and by not taking good care of the patient. They are part of the cost of doing business and will occur fairly regularly if people are not careful. However, the best way to minimize litigation is awareness and full attention to regulations and best ethical practices. Professionals should also take care of themselves and be aware of how they appear at work, show their dedication, and communicate with patients, rather than make assumptions, it is critical to optimize results and avoid lawsuits.

Balance the good and bad of Big Data

There is no doubt about it: the big date is important for health and it is necessary. Instead of fearing legal problems, companies must create ethics and regulations to support their business. There will always be problems along the way, but the power of Big Data cannot be ignored. Big data is changing many industries, saving more patients and improving the quality of medical care.

Everyone in the field must realize how important it is to keep up with changes in trends and regulations. Health professionals have a very important job and now they need to worry about patients' privacy as well as their health and well-being. Having good intentions and making an effort to stay informed is the best way for health professionals to navigate the emerging big-time world in health services. The demands are scary, but this fear is no excuse for not providing the best care possible. The time has come for medical care to follow other industries and implement everything from business intelligence strategy to big-time initiatives.

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