One way to collect, analyze and action your data is by creating a database. Database organization is the key to success in business management. It can make it easy to find what you need and also help keep your company running smoothly. In this article, we’ll discuss how to properly organize your database and give tips on how to make sure it stays that way.

Define Your Database

The obvious starting point has to be deciding on the purpose of your database. You need to identify what information needs to be stored and why. Consider who will need to be accessing it and who will be able to edit the information.

When it comes to design and maintenance, there’s plenty you can learn from the internet by reading specialist websites. If you want to research database denormalization you can discover its definition, advantages and disadvantages. It’s also possible to discover examples where normalized tables have been combined into one. Whether it’s data engineering consultancy or learning about programmatic advertising, help can be found online.

Create A Database That Is User-Friendly

You need to decide how much information needs to be stored, as this can determine the structure of your database. The design should make it easy for people who don’t know anything about databases or IT systems. It will be important that people can find what they need quickly and efficiently by following a logical sequence. Have a good think about the terminology used for your files, folders, tables and columns because they need to be both understandable and consistent.

Store the data in a way that each item is accessible from any other item. This removes the need to duplicate your records or change the numbers every time there are updates made elsewhere within the system. In technical terms, this process is called normalization.

Make Sure The Data Is Accurate And Up To Date

If your data is inaccurate it can lead to many problems, so be sure to fully train the database users. If you notice that something has been updated incorrectly or missed you should take action straight away, advising the relevant employee.

Regularly invest time in performing quality assurance checks using software such as AccessChk for Microsoft’s Windows operating systems. This will ensure everything is running smoothly and that nothing important has been missed. It might sound like an arduous task but if it’s done often enough it may only take a few hours each month. Always bear in mind that any data input into your system must go through these tests before being considered completely finished.

Keep Track Of All Changes Made

By now you may have created forms, queries, reports and tables using Microsoft Access or a similar software package. It’s important to stay on top of the data changes because if you don’t it will lead to errors and mistakes. If the data is in a spreadsheet, make sure that when new entries are added they’re placed at the end of the sheet so the old information isn’t overwritten. You need to request regular reports to fully discover the changes that have been made to your system. If you don’t, errors may continue to be made and essential data could be irretrievably lost. This could be costly in terms of time, money and future business.

You may wish to keep an accurate log book, spreadsheet or table with dates next to each entry detailing what was added or modified. It might seem like a tedious process at first glance but if you maintain these logs throughout the life cycle of your system they will quickly become invaluable when searching for specific items and identifying issues.

Regularly Back Everything Up

If you don’t keep copies of your database,  you risk losing all the information it contains. You need to decide how often you want to backup your data, and that will depend on the type of system you’re using. The ideal method is for database administrators to back up their systems every night when people have finished work for the day. This will help provide a safety net in case anything goes wrong. You should also use different storage media for backups so if one device fails there’s still another available. This could then be used until the other has been repaired or replaced with a new disk drive. Your employees would be able to continue using the database during this time, which would mean there would be no adverse business implications or downtime.

Data backups can help ensure that important data won’t be lost after an unexpected incident like flooding or theft at your workplace. If you are concerned about cybercriminals and hacking, keep a copy of the database on a computer that has no internet connection. It’s also important to appreciate that over time, data on memory sticks and external drives can become corrupted or lost. These devices can also get lost and mislaid, so cloud storage can be a valuable option in this scenario.

Create A Master List Of All Your Contacts

This is the hub of your business, both now and in the future. Add notes to each contact, such as their interests and previous purchases. Import any new contacts into your database by exporting them from other databases or social media sites (e.g., LinkedIn). Group similar contacts together in categories for easier management. This can help you with things like marketing campaigns or the purchase of office supplies and equipment.

When your company database is well-organized and maintained, it will become a vital tool for your business. It will be your ‘go to’ for key information that can help your company prosper and grow over the years that are to come.

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Although supporting cloud storage applications and transactions, data centers provide seamless data backup and recovery facilities. Since business data storage offers various capabilities, businesses turn to new technologies like AI and machine learning to advance their data center infrastructure. 

Machine learning, an advanced subset of artificial intelligence, can analyze and identify patterns in large quantities of knowledge. It can optimize any aspect of the data centers operation, including planning and design, maintenance of uptime, IT workload management, and cost control. The effectiveness of data centers is supposed to be enormously enhanced by AI and machine learning. According to IDC, as a result of embedded AI functionality, 50 percent of IT assets in data centers can operate autonomously. 

Machine learning and AI to Control Smart Data Centers 

Data Centers have evolved from being just a storage facility to a critical IT infrastructure for businesses. Modern data centers use several servers to refine further and increase their processing and computing capacity. Data centers are perceived as a massive supercomputer. A data center is required by almost every company these days to process loads of information every day. 

Technologies like AI and machine learning are starting to reach various computing applications, revolutionizing data centers’ management for businesses. AI data centers can assist businesses in driving decision-making powered by data. They will also help companies keep ahead of ever-growing requirements for data storage and processing.

AI in data centers will significantly enhance data security as these centers are more vulnerable to cyber threats. This technology determines everyday network activity and detects cyber hazards based on network anomalies and deviations. AI can also streamline complex computing management in data centers and allow data processing centers to run autonomously and effectively.

The use of systems powered by machine learning may potentially lead to predictive and preventive maintenance. By improving energy quality, regulating temperature, and modifying cooling systems, they can provide collection efficiency. It has been of utmost concern to maximize energy use as electricity is a critical factor for data center infrastructures. 

Every year, energy prices soar by about 10%, resulting in higher costs per kWh. More than 90 billion kWh of energy is consumed annually by data centers in the United States alone. As data centers worldwide use around 416 terawatts of electricity, content is increasing on a global scale. Nevertheless, AI and machine learning will offer various benefits to using energy in data centers by businesses. For example, Google’s search engine has applied AI to efficient energy usage in its data centers. It has resulted in a 40% reduction in energy consumption. 

It is also possible to use AI and machine learning to track server performance, network congestion, and disk usage. It helps in detecting and predicting data outages. The revolution in AI and machine learning will also improve data centers’ infrastructure and promote intelligent and more automated data management. 

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According to Juniper Research research in 2016, up to 70% of all forms of credit card fraud are primarily card not present (CNP) transactions. In 2020, the number of online transactions was around double that or even tripled that of 2016. In such situations, you must protect your data during all aspects of business operations, including online transactions. To secure data, individuals must follow a 360-degree approach to ensure that a security breach occurs internally or externally. 

Top 10 Security Methods for Encrypting the Data During Online Transactions 

Avail Advanced Anti-Malware Program

It is almost impossible to encrypt the data to 100 percent security. We should, however, take enough small measures to keep hackers’ doors shut. Using the system or laptop’s specialized anti-malware programs. It will protect your computer from classified and unclassified attacks and other digital devices you are using. You should make sure that it is continuously updated and is always on, rather than just using an anti-malware program. Users should also be able to flag mutated malware threats with the anti-virus scanner.

Ensure that the Password is Strong Enough 

The secret to online transactions is the password. But the hidden truth is that breaking into your system and gathering personal information is also a key for hackers. Henceforth, having reliable and unbreakable passwords is obligatory. Use passwords that are hard-to-guess and include upper- and lower-case letters, numbers, and symbols. For online accounts, make sure you use different passwords.

Data Encryption is a must 

Encryption is a means of concealing information in a string of codes that appears as random data that is difficult to decipher. Encryption is one of the necessary methods for the authentication and security of data transfer. Data encryption is accessible to safeguard emails and other essential details. This protects sensitive information from leakage efficiently through online purchases. 

Anti-theft your device 

Steeling personal data or information from a stolen smartphone has been in the league for a long time: Anti-theft your device. However, technology has revised its frameworks. Today, if it goes missing, you can delete all the details from your smartphone or any device. Norton Mobility Security allows you to ‘factory reset’ to completely wipe out the missing device’s data. This contains your confidential contact list, messages, call history, browsing history, bookmarks, among other personal details. 

Don’t use Public Computer or a Public wi-fi 

Currently, almost every organization offers free wi-fi connectivity. But they aren’t very safe. There are fewer security features for public wi-fi and public computers than for a private network. Henceforth, whether you are linked to public wi-fi or operating on a public computer, never try to make online transactions. They are one of the loopholes used by hackers to get data. 

Utilize a Virtual Deal Room for Sensitive Transactions

Most of the company’s data is made public while shared on Dropbox or Google Drive, the so-called secure source. However, using a virtual deal room to exchange company-related confidential data is a much safer decision. A virtual data room permits you to manage various sensitive information without a physical data room.

Deal only with reputed sites

It is as dangerous to make payments on an unfamiliar site as opening a link that does not show secure signs. Never transact directly to any site unless you are aware of it. The advanced security features used in payment processors like PayTabs would prevent the wrong hands from getting your financial details. 

Overwrite Deleted Files

Deleting vital data on a computer system seldom suggests that it is always deleted. Sometimes, this data remains on the disk, and anyone who knows the tactics, essential hackers, will retrieve it. The only way to guarantee that the deleted data is gone is to overwrite it. Online tools to streamline this process are available. 

Prefer Virtual Keyboards

Hackers are not only on the screen of the computer; they are also spying on your keyboard. There are viruses and malware that can keep a record of what you type on your keyboard. Now, when making online transactions, it is safe to use a virtual keyboard.

Review Company Policies on Cybersecurity

Many of the cybersecurity attacks take place because of employees. Several workers involved in the transaction process are unaware of the cybersecurity policies of the organization. Therefore, to preserve current policies concerning cybersecurity problems, your employees should have due care. Meanwhile, your employees should also check what platforms you want to use. This will make them know how to use the platform correctly.

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So, what are data center proxies?

To administer and run proxy IPs, companies that sell proxies have assigned servers. Data center proxies are a type of proxies whose data center servers manage their IP addresses. Due to their speed, they are familiar, enabling many users to perform their tasks before being detected by websites. You can, therefore, use them on less stable websites for web crawling or data mining.

For websites with more robust security features, however, the pace is a disadvantage. Once too much traffic from a particular IP address is detected by systems over a short span of time, they flag it for bot-like behavior. This has prompted the blocking of several data center proxies. But as they are cheap compared to residential proxies, you can buy in bulk and move from one IP to another whenever any are blocked.

For websites with better security features, however, the pace is a drawback. Once systems detect too much traffic from a particular IP address over a short period, they flag it for bot-like behavior. This has prompted the blocking of several data center proxies. They are cheap compared to residential proxies. Whenever any are blocked, you can buy in bulk and move from one IP to another.

However, data center proxies have some disadvantages in that some websites can easily spot and block their fast traffic. And they are not very pleasant at providing cybersecurity.

Residential Proxy vs. Data center

Residential proxies do not get a data center with their IP addresses. Instead, their IP addresses are provided by providers of internet services. Using plug-ins, ISP customers allow proxy sellers to use their IP addresses. As you navigate a residential proxy, your computer appears to be browsing from the ISP customer’s residence.

Compared to data center proxies, residential proxies are very costly. They are also slower for accessing or mining data from well-secured websites but more reliable. Although maintaining the stability and security of residential proxies, static residential proxies are often almost as fast as data center proxies.

Before deciding whether to use the residential proxy or the datacenter proxy, one needs to determine the website they want to access first. Sometimes, with any proxy form, you will find that you can crawl the web, mine data, and change your location.

What are the types of Data Center Proxies?

Data center proxies are mainly classified based on the protocol used.

• Hypertext Transfer Protocol (HTTP) Proxies

You may have found many of the URLs that have an HTTP section as you browse the net. This is because, via the HTTP protocol, most internet surfing takes place. The browsing experience typically includes entering or clicking on a URL, which goes to the server hosting the site as a submission. Hopefully, the server will give you a response in the form of information from the website upon receiving your request. This arrangement is referred to as a client server-model where you send a request to a server and respond from the server. The proxy server serves as an intermediary between your browser and the server while using an HTTP proxy.

• Secure Socket Proxy (SOCKS)

The SOCKS protocol works by transmitting network packets between the server and your browser via a proxy service. Although HTTP proxies are in use to retrieve site information, for other general purposes, SOCKS proxies are useful. Compared to HTTP proxies, they are known to be a lower level of proxy.

When to use Data Center Proxies

As with other proxy types, for specific purposes, data center proxies are better suited than others. Data center proxies will typically perform tasks that require high speed. Also, you can use them for:

• Data mining in smaller websites lacking adequate security systems
• Web crawling
• Purchasing products that you wish to purchase and resell at wholesale. Make sure you have a big pool of proxies and quick bots to execute this correctly.
• Change of location to access sites with geographical constraints. This could be to get discounted rates, perform regional market analysis, or access services that are not currently available.

Conclusion

Data center proxies will perform virtually all the functions for which proxies are intended. They will give you adequate privacy to allow you to search anonymously for information and access websites. Their speed makes them popular among users of the private internet. However, for business usage, where a high degree of privacy is needed, you should not use them. As always, to understand the type of functionality required for your mission, conduct thorough research.

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Master Data Management (MDM) is the method of generating and maintaining quality data. An entity can have a single master copy of its master data, such as data on clients, products, items, etc. Usually, non-transactional data within the company is referred to as a master, and such data can include clients, vendors, staff, goods, etc.

Let’s discuss the importance and relationship between data quality and MDM

Importance of Master Data Management (MDM)

There are many cases of incidents where low data quality has caused many companies with a lot of pain. How many times have you noticed misspelled versions of your name stored inside the same company against two different accounts? MDM is not a new idea. However, in a fast-paced business environment where businesses can not afford to lose clients because of data problems, it has become increasingly necessary. MDM is important for large organizations because it offers the company a single version of the reality of their master data.

The Complexity of Maintaining Data Quality in Organizations

Data Quality is the concern where, in most situations, data collected in the systems is not of the largest quality due to human errors. First of all, individuals are not the highest paying individuals in companies doing data entry. Furthermore, they don’t care if they don’t have incentives to collect useful quality data.  Capturing incorrect email emails, addresses, etc., is a common mistake that individuals make in organizations. And that is why there have been so many data quality tools around for address correction and items of that nature.

When several IT systems within the company maintain the same information differently, the problem is compounded. Now in one system, correcting consistency doesn’t correct the other automatically. To make matters worse, think about a big company purchasing another big company. The other company may carry a lot of information that needs incorporation now. This is an immense task from a data quality perspective and controlling the quality of data after the merger. This is an introduction to know about the importance and relationship between data quality and MDM.

Master Data Management for Single Source of Reality

It is one thing to have high-quality data. But there is another way to handle the information across structures and when dealing with mergers and acquisitions. And that is where MDM comes into the equation. MDM’s principle is to establish a single master data hub to provide a single, authoritative source of master data. The master data feeds into other IT systems within that organization (customers, vendors, products, employees, etc.).

How Data Quality and MDM Are Related?

Initiatives for Master Data Management (MDM) and Data Quality are closely related.

An MDM solution cannot be required by small organizations, whereas large organizations with sizeable master data must consider implementing it. Even without considering MDM, it is possible to provide a data quality initiative; the reverse is impossible. Any initiative to implement MDM must have a portion of data quality to it.

If there is an MDM drive on the outlook, data quality should be regarded as a requirement for any Master Data Management initiative. The road to MDM starts with data quality. And the discovery of master data, profiling, and analysis is the starting point for any data quality process.

Depending on the case, there are three different ways that Data Quality (DQ) and Master Data Management (MDM) can get implementation:

• Implementation of data quality separately where either MDM is not implemented or is not in consideration in the near term.
• Implementing Data Quality as the first step towards MDM, first implementing Data Quality, and then implementing MDM as a different next step. This enables data correction before MDM implementation status across all applications, a popular approach in many businesses.
• Implementation of data quality following the implementation of an MDM. In these instances, as part of the MDM initiative, cleaning up data occurs. To make this possible, in their MDM suite of tools, several MDM vendors have begun to come up with bundled data quality tools.

Data quality is an essential feature of the MDM initiative. The MDM solution is in the application in a single master data object or all operational master and reference data. An MDM project is also not something that any organization’s IT department can be expected to conduct in isolation. It needs the full participation of both IT and business staff. It takes all data quality and MDM implementation stages, Data Governance teams, Data Stewards, and business teams.

For any MDM project initiative, business involvement is crucial simply. As it is only business users who can understand and identify what the Data Quality Level is for the organization. And what makes sense and what does not? Yes, to make MDM happen, IT needs extensive involvement. But it’s the organization that is pushing the implementation.

Conclusion

Data quality is essential to any MDM implementation, even within organizations that don’t need MDM; it may also occur independently. To fully leverage the power of Master Data Management, MDM solutions need IT and business teams to work together to identify data quality requirements.

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Data Warehouse

The data warehouse’s role is to achieve convergence of data across business lines and systems to provide centralized support for management analysis and business decision making. A data warehouse can fundamentally help you turn your company’s operational data into high-value, accessible information. It also delivers the correct information to the right people at the right time. But in other situations, the traditional data center would not be able to fulfill the data analysis needs. It’s hard to assess value mining on global data with data warehouses. It can’t adequately represent the value of the group’s massive data assets in terms of scale and effect.

Data Center

This has led to data centers, which is not only a program or tool, but a comprehensive department that offers data asset management and services across a variety of systems, software, processes, and requirements for the entire organization. The architecture system of data centers in the sense of big data is the ELT framework. At any time, it extracts the desired original data from data centers for modeling and analyzing according to the demands of the upper layer applications. Second, establishing data centers aims to merge all of the enterprise’s data, open the data gap, and remove the data format inconsistency. Data centers play a crucial role in the company’s digital transformation and sustainable development; data centers are born for decoupling. Application and data decoupling are the central significance of building data centers for businesses. In this way, companies can create on-demand data applications that fulfill business needs without restriction.

Characteristics of Data Center and Data Warehouse

Integration is the most important in traditional data warehouses. Because of the processing and storage costs, it is essential to collect and consolidate data from various data sources and reduce the redundancy of its data as much as possible. Consequently, data entering data centers must be processed, formatted, rearranged, and summarized. All of its data has one particular physical characteristic and is organized. The new generation of data centers uses distributed computing, but centralized delivery of consumer products does exist. The data center also operates in distributed storage and processing, in terms of the system architecture.

In comparison, the data center is the point of contact between the front desk and the back office, precipitating standard business tools and technologies. Data centers refer to comprehensive platforms that incorporate data collection capabilities. Data centralization ensures that heterogeneous data processing, governance, modeling, analysis, and implementation can be streamlined to enhance business through internal and external multi-source data management. The importance of data collaboration can be revealed to the outside world, becoming the center of the company’s data asset management. The overall technological architecture of data centers adopts a cloud computing architecture model for computing resources and storage resources. It bundles and integrates resources through multi-tenant technology and opens up data services “one-stop” to customers.

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From Google to Facebook, every company working with data has its own data center. But still, every organization doesn’t have a data center of its own because it’s very costly to develop and operate data centers. That’s why most small and medium-sized businesses just lease space from a third-party data center.

Let’s look at the different types of Data Centers :

• ​Hyperscale Data Center: A hyperscale data center is also known as a hyperscale data center for businesses. This is one of the most modern data centers currently open. The company that supports it owns builds and manages these types of data centers, and that is why it is used only by big companies. Hyperscale data center is not feasible for SMEs, and that is why it is used by industry leaders such as Google, Amazon, Facebook, etc. Hyperscale computing is a requirement for big data storage and cloud in this type of data center. A hyperscale data center has an overall size of around 1000 sq. feet and they really are one of the best data centers. Besides that, there are nearly 500 cabinets upwards, but it can also have about 450 cabinets. Some of the critical distinctions between hyper-scale data centers and other types of Data Centers are the high fiber count.

• Colocation Data Center: It is that kind of data center where the single data center owner sells cooling, fuel, and data center space of various firms and other hyperscale customers at different locations. Interconnection is one of the main drivers in this form of the data center. You should be aware that a data center for collocation provides software interconnection as a service such as Salesforce or even Platform as an Azure service. Through this, enterprises can use a powerful and modern data center all the resources without having to deal with a lot of complexity. The colocation data centers have a radically different architecture and direction, specification, and technological architecture for transitioning customers in this type of data center, selected integrators.

• ​Wholesale colocation data center: In the case of a wholesale data center, there is one owner and that single owner sells power, space, and cooling much like normal collocation to hyperscale firms and businesses. But one important thing to know about data centers for wholesale colocation is that interconnection isn’t really required. Big companies are merely using this sort of data center to maintain their IT infrastructure. Similar to the traditional collocation data center, the wholesale collocation serves fewer customers.

• Enterprise Data Center: The enterprise data center is mostly built on-site but can also be built off-site in some cases. The company owns an enterprise data center facility is also owned by the company that it supports. Some parts of the enterprise data center are assigned to various sections of a business. It can be as high as 40MW+ and can have about 10 cabinets.

• ​Telecom Data Center: A telecom data center is a type of data center which is primarily operated by a telecommunications company, including AT&T and Verizon. But only one service Provider Company can also own this sort of data center. High connectivity is the business engine, and thus a telecom data center would not be able to operate correctly without reliable connectivity. Cloud computing, mobile services, and even the driving of content delivery are responsible for the telecom data center.

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With change at the center, companies across sizes should continually ask themselves these two questions – how easily they can reinvent themselves, and how they are prepared for their potential needs? Data has opened up new avenues for companies to expand and evolve, but despite this opportunity, many companies are still dealing with two significant issues – first, the sheer volume of data being produced every day, and second, the growing demand on IT [Information Technology] to become simpler and more agile.

Looking to the future of the data era, companies will look to embrace modern IT technologies that can improve decision-making, data access and efficiency in the application. Therefore, a great need for data storage emerges in this new period that takes the company from knowledge into innovation. The latest data storage should be able to handle any workload; maximize performance as required, and drive productivity without compromising.

Besides these, there are three additional features that companies can look at in their modern storage solution:

• Data-Centered Design: Provide a data-centered architecture that can optimize system capacity, scalability and storage efficiency to meet any workload without compromising.
• Intelligent Automation: Offer intelligent automation through programmable, autonomous technology that simplifies management and optimizes system resources, while allowing proactive health analytics to track, evaluate, and troubleshoot the environment quickly.
• Adaptability: Delivering adaptability as this will enable speed and agility of applications, flexible models from edge to core to cloud without disruption and flexible consumption by choice, predictability and investment protection.

Today’s companies are on the verge of capitalizing on digital transformation. There’s, however, a constant tug-of-war between cost and productivity that hinders the way every company will achieve its digital goal.

To remove these tradeoffs in performance, scalability, and flexibility in storage, a data-centered, intelligent, and adaptable infrastructure is required to transform and mobilize both traditional and modern workloads.

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The ground reality is that IT operations would be interrupted during this pandemic in the data centers. Coronavirus Effect on IT is a fact to know. Given that travel restrictions are widespread and stringent, last-mile IT field engineers may face challenges such as refusing access to vital facilities they typically monitor. Furthermore, even if they can reach a customer location, due to quarantine restrictions, physical access to customer premises to address hardware faults in the data center-such as switching off a simple drive may be hampered.

Looking at the broader situation also exposes other potential barriers that reduce potential disruptions. Access to both complex and commonplace parts such as fans and power equipment could be one common aspect while solving IT infrastructure and systems faults. These parts may be requested for public health concerns of higher-order, or they may be delayed by the challenges of shipping them from geographic regions where there is limited movement. The manufacturing and distribution of such parts will likely be delayed, which would also cause delays in the implementation of any solutions.

Reducing Distractions

Maintaining uptime regarding IT assets and regular operations in the current environment requires various steps. Organizations with IT asset management control will be better equipped to support stable IT operations. This is due to their ability to have a complete IT inventory that facilitates asset tracking, thus allowing greater control over the company’s IT environment.

Besides knowing where all of their hardware assets are located in the world, and given the different on-ground scenarios and constraints around the world, they also can detect faults that may occur during this global challenge. Another significant impact on their business and IT operations is the increased use of automation, robotics, and AI by organizations adopting these advanced technologies.

Dynamic baselining is one such example where organizations reap dividends from predictive analytics for proactive infrastructure management. Another example of this is the integration of technologies such as S.M.A.R.T. events that can generate alerts before actual failure. Organizations use remote automation and AI to ensure smooth operations through automated and constructive failure detection and resolution capabilities.

The intensity of AI tools in terms of pattern recognition through predicting and self-learning also leads to quick troubleshooting of IT problems, potentially due to better turnaround times than by human interaction. Such technologies are coming into their own and rapidly becoming relevant and faster, given the constraints of social distancing.

The versatility of remote monitoring tools is also becoming significant in automating fault resolution processes for hardware infrastructures. Such tools can initiate service tickets for hardware component failures, communicate with systems remotely via standard protocols such as SNMP, WMI, and SSH, and then relay hardware events back to the IT administrator via a secured TCP outbound link.

In addition, severe disruptions could overwhelm call centers and their staff. In such a scenario, useful IT customer service portals may help business customers raise and track service tickets from any computer, resulting in quick monitoring and fault resolution. The ubiquity of mobile apps and their functionality also contributes to increased awareness of their strengths outside customer service portals. Mobile apps allow users to identify devices that require support by merely using a camera on the phone to scan the bar code.

The application then triggers the automatic insertion into a ticket submission form of the corresponding serial number. Companies that use mobile apps via conventional portals will increase service and attention usability and productivity while discovering a new way to remain connected. While a significant cause of concern, the severity of the current crisis has led organizations to rethink how they can evolve and innovate to minimize disruption. Various services and tools can ease the pressure on IT operations and bring businesses peace of mind.

More significantly, automation and remote monitoring can have a significant impact on reducing outages while making the use of their versatility to help companies work through these tumultuous times.

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Data centers have definitely been tested during this pandemic and have proven that they put “important” in vital services by effectively providing the opportunity to do work, studying, exercising, grocery shopping, socializing, doctor’s appointments, attending religious places and entertainment, all from home a reality.

This social distance season has illuminated our ability to communicate, work, and learn from remote places effectively. We have checked and discovered the efficacy and advantages of virtually doing most things. This highlights something which every generation learns at the risk of sounding dramatic: the world never stays the same. Some of the changes made in social distancing will stick around. It is merely common sense. Why waste time, energy, and overhead on traveling to a physical office or the site of a client, when those minutes or hours could be spent productively? The same is true for doctor visits and studying – these things do not have to happen face to face.

The use of cloud platforms and data-intensive applications has been on the rise already and has surged during the pandemic. What’s next, then? Where are we going from here? How’s the post-pandemic future of data centers going to look like?

Increase in Demand

Before the pandemic, analyst firm Gartner predicted that by 2021 the cloud computing and services industry would hit almost $300 billion, up from $175.8 billion in 2018, with software as a service (SaaS) leading the development. SaaS expected to rise from $72.2 billion in 2018 to $113.1 billion in 2021 in the same projection.

In a post-pandemic environment, the need for SaaS solutions to sustain an increasingly distributed workforce would be even greater. SaaS, once considered tools for SMEs, is gaining popularity with big business customers. An enlarged customer base means new resources, greater competitiveness, and creativity and, let alone, increased demand for data center space. Many SaaS providers will start looking like the big cloud companies of today, using strategically located data centers to give a growing customer base better coverage.

Cloud Companies and Geography Evolving In Size

Traditional cloud providers are getting powered up. For hyper-scale operators like Twitter, Facebook, and Amazon, 100MW would be the starting point for power-capacity. To responsibly feed their appetite, these mega players are gradually investing in clean energy sources and taking power sources closer to the latest data centers.

Much has been said about enterprises abandoning data center ownership and farming it out to public cloud providers such as the hyper scalers mentioned above. Nonetheless, the fact is, the growth of the distributed workforce would produce far more confidential data that cannot be put at risk. Security concerns will ensure that data centers from enterprises do not leave. The need for security and the approached age of existing facilities will combine to slow down the decline in enterprise data center growth.

Initially, new centers will appear in developed, predictable locations such as Northern Virginia, Chicago, Dallas, Phoenix, and the Bay Area. In these Tier, I market there is ample power, space to build, accessible network infrastructure, and tax incentives that have been set. We can also anticipate rising demand in Tier II and III regions, however, as they provide the capacity to accommodate larger data centers and cost-saving opportunities versus significant metro areas. They are appropriate destinations for more and more distributed networks, too.

The national and global demands on bandwidth generated during the period of self-quarantine show that the time is also ripe for rapid growth in edge data centers. The resulting changes in industry and society would only intensify the need for more capacity. Look for cable companies and telcos to lead the way, exploit cutting-edge data centers to expand network life, and add function without huge outlays of money, with SaaS and CDN providers also gaining religion quickly.

Rapid Response to Requests

This rise in demand, adoption of new solutions, and adventures into new markets will boost data center building volume. Super-sizing data centers and post-pandemic building boom would accelerate the evolution of conventional construction processes and place pressure on supply chains to keep up with emerging technologies. Building the use of information management (IMM) systems will become a standard, and two-dimensional models will gradually be replaced by three-dimensional alternatives providing a more detailed evaluation of requirements, clash resolution, cost, and scheduling.

Prefabrication then speeds up the production process for the project with a consistent blueprint. In addition, more pieces of the puzzle will be built off-site to accommodate simultaneous construction projects, from power racks to walls. Modularization and prefabrication will reduce labor costs and open up opportunities for diversity in the workforce. More women can be expected to join the construction industry in this modern technology-driven period, providing a broader pool of talent to draw from for these critical, time-sensitive projects.

The rapid growth of data centers, including edge facilities, would increase the need for more robust management solutions in an increasing number of non-traditional locations. The price of a truck roll to a remote location, for example, will become a critical factor in operational planning. Datacenter operators would need platforms that meld technologies such as AI and SDDC (Software-Defined Data Center) to allow them to perform a variety of current hands-on tasks, such as resetting breakers from one remote location.

There are endless ways in which humanity will never be the same after COVID-19, and data centers will enlarge to serve the future economy rather than continue to be pushed to the limit.

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