How to Detect and Prevent Email Security Risks in 2023?

As online communication becomes increasingly necessary for any company to flourish, an e-mail will be a significant security problem in certain instances in 2023. In fact, e-mail security risks, such as whale phishing, whaling, and ransomware, are already rising at an alarming pace nowadays. Cyber threats have become paramount issues for both big and small businesses, and consequently, they must develop methods to mitigate increasing issues with e-mail security.

Since more than 90% of cyber-attacks are started by e-mail because the weakest link in the security chain is e-mail, an infringement of security may negatively affect the image of either the consumer or the business. However, combating attacks by hackers requires a multi-layered e-mail security procedure. One issue is that e-mail is not a protected communication medium by default.

13 Email Security Risks in 2023 and Their Solutions

1- Spoofing and Phishing

E-mail spoofing happens when a cybercriminal sends an e-mail to a user masquerading as someone the user knows. Phishing is another hazardous method to mislead customers into giving cybercriminals personal data like bank accounts or social security numbers. 

E-mail spoofing to the original sender is easy to accomplish and hard to trace. Cybercriminals sometimes add pictures and trademarks that seem more genuine and authentic. They even create a connection that appears natural. It leads users to a fake website, though.

As spoofing and phishing are two of the most common types of Email threats, customers need to be informed of the accessible anti-phishing solutions.

2- Domain’s Squatting

Squatting is registering, selling, or using a domain name to profit from another party’s brand. Consequently, companies and their customers may become targets for domain squatting.

To address domain squatting, monitor domain name registrations (demark registrations and domain auction sites). Also, take legal action against domain squatters using domain names that are similar or identical to your trademarks or brands. 

3- Dangerous Files

If harmful information is received from the user via an email attachment, it may take over the whole computer system and network. Dangerous files, such as malware or viruses, can be sent through email as attachments, links, or even embedded within the body of the email. These files can compromise email security, infect systems and steal data. 

To guarantee an efficient solution, these files must be examined using an anti-virus and behavioural analysis program based on signatures. Use file extension blocking to prevent dangerous file types from being sent through email. Blocking file types include .exe, .bat, and .jar.

4- Vulnerabilities in E-mail Security

Vulnerabilities in e-mail services induced by provider misconfigurations need to be identified. When exploiting e-mail vulnerabilities, they penetrate the target system, expose information, and make it inaccessible. It is important to take a comprehensive and proactive approach to address vulnerabilities in email security.

Conducting Email security assessments to highlight email security issues can be helpful such as vulnerability scans, penetration testing, and risk assessments. 

5- Crypto-Ransomware 

Crypto ransomware encrypts a user’s files and demands a ransom payment in exchange for the decryption key. This attack can seriously affect email security and result in data loss or financial damage.

To address crypto-ransomware, backup data regularly to a separate location not connected to the network. Use access controls to restrict access to important files and data. This can include implementing strong password policies, two-factor authentication, and least privilege access. A ransom must be paid once infected to unlock all encrypted data. In this respect, the e-mail security services must be strengthened, and the analytical services must be expected to detect and avoid ranking-specific behaviours.

6- Configuration Errors 

This is a pervasive security problem. A poorly configured e-mail service may lead to a big issue by enabling e-mail to be delivered without authentication. For example, a cybercriminal without authentication access to your e-mail service may send a random email to one of your employees. A cybercriminal who embodies the CEO may be more likely to succeed.

E-mails with known vulnerabilities in the internet browser may lead to identity theft, data leakage, and access problems. Sometimes a link may include an exploited piece of code. In this situation, protection steps must be taken by the e-mail service and security components.

It is important to have proper configuration management practices implemented to prevent configuration errors. This includes documenting configurations, deploying change control processes, and regularly reviewing and testing system configurations to ensure they are up-to-date and functioning as intended. Additionally, ensure that team members responsible for system configurations have the necessary training and expertise to configure the system properly.

7- Browser Exploit Kit 

A browser exploit kit is a software toolkit used to create and distribute malware through vulnerabilities in web browsers. These kits typically contain pre-built exploits to target specific email vulnerabilities and threats in web browsers such as Internet Explorer, Chrome, Firefox, and Safari.

E-mails with known vulnerabilities in the internet browser may lead to identity theft, exposing confidential data, and access problems. Sometimes a link may include an exploited piece of code. Protection steps must be taken by the e-mail service and security components.

When a user visits a compromised Website or clicks on a malicious link, the exploit kit automatically detects the user’s browser and attempts to exploit any known vulnerabilities. Once the exploit is successful, it can download and execute the malware on the user’s computer.

To protect against browser exploit kits, it is important to keep web browsers and plugins up-to-date with the latest security patches. Additionally, users should exercise caution when clicking on links or visiting unfamiliar websites and use antivirus software. Web developers need to follow secure coding practices to help prevent browser exploit kits. 

8- Spear Phishing Attacks and Business E-mail Compromise (BEC)

Both spear phishing and BEC attacks can have serious consequences for individuals and organizations. In addition to financial losses and data breaches, these types of attacks can also damage an organization’s reputation and erode trust with customers and partners.

Another crucial problem is that a cyber thief who circumvents all security measures uses the ignorance of the end-user to attack the system. Because 97% of the world’s population cannot recognize a sophisticated phishing e-mail, users should be regularly informed about hazards via phishing tests, exams, surveys, and games.

To protect against spear phishing and BEC attacks, you must implement strong security measures, such as two-factor authentication and encryption. By remaining vigilant and proactive, individuals and organizations can help avert these types of attacks and mitigate their impact if they do occur.

9- File Format Exploits

File format exploits are a common tactic used by hackers to exploit vulnerabilities in software and gain access to a user’s system. Furthermore, file format weaknesses have become an essential source of information security threats for many corporations. Attackers that exploit these vulnerabilities (these are critical since they frequently impact multiple systems) create malicious files that cause application problems (such as buffer overflows). For example, an attacker may create a malicious PDF file that infects Windows, Macintosh, and Linux systems via an Adobe Acrobat file format vulnerability.

Keep all software and operating systems updated with the latest security patches and updates to address known vulnerabilities in software and reduce the risk of a file format exploit. Moreover, content filtering can help block suspicious file types and prevent them from entering the network. It can include blocking files with macros or other potentially dangerous content.

10- Malware

Cybercriminals use malware to gain unauthorized access to the network, steal sensitive data, or cause other types of damage. Malware includes viruses, worms, trojans, ransomware, and spyware which can be delivered to a network via email attachments, malicious websites, or infected software downloads. Once installed, malware can run undetected in the background, collecting critical information or causing destruction to the system.

To protect against malwares, users should be careful when downloading software, opening email attachments, and clicking on links received from unknown sources and installing reputable antivirus software. There should be a regular backup for important data to prevent loss in case of a malware attack.

If a computer is infected with malware, take immediate action to remove it. There’s a need to run antivirus software, restore from a backup or get help from a renowned IT security provider such as Enterprise Engineering Solutions. 

11- Email Bombing

In this cyber-attack, an attacker floods an email inbox with many emails, overwhelming the recipient’s email server and making it unavailable or crashing. It is often conducted by using automated scripts or tools to send a large number of emails to the recipient in a short time. This procedure is usually used to disrupt the functioning of an organization or individual’s network. The attacker targets the email server, and the recipient loses access to their email, disrupting operations.

To avoid email bombing, organizations need to implement email filtering and traffic management systems to detect and block malicious traffic. Some tools are used to help users manage their inboxes, including spam filters and the ability to block specific senders.

Individuals can create rules to automatically filter out unwanted emails or use email providers with strong spam filtering capabilities. Additionally, they should be cautious about sharing their email address online and only provide them to trusted individuals or organizations.

12- Man-in-the-Middle (MITM) Attacks

It is the type of attack where an attacker intercepts emails between two parties, allowing them to read, modify, or even delete the content of the email. The attacker could also use intercepted emails to steal crucial information (login credentials or financial information). Such attacks can be carried out in several ways, including Wi-Fi spoofing, DNS Spoofing, and Email Hijacking. Users can take several measures to protect against MITM attacks, such as using encryption to protect communications and being cautious when using public Wi-Fi networks. 

Furthermore, organizations can deploy security measures, such as multi-factor authentication, to protect against email hijacking and other types of account compromise. One should also use reputable antivirus and anti-malware software to detect and prevent MITM attacks.

13- Weak Passwords

Weak passwords are a major security risk for email accounts. Don’t create a weak password to avoid guessing and other password-hacking techniques. Your password should not be simple or easy to remember, such as “ANYNAME,” “12345,” or “qwerty.”

It is prohibited, as hackers can easily compromise it, allowing them to access the account and misuse personal data, financial information, or confidential business information. To protect against weak passwords, users should follow best practices for password security, such as:

  • Create and manage strong passwords for multiple accounts using a password manager.
  • Add an extra layer of security to your account with “Two Factor Authentication,” such as a one-time code, fingerprint, or an additional password.
  • Use strong passwords (long, complex, difficult to guess)
  • A mix of uppercase and lowercase letters, special characters, and numbers.
  • Make sure to change passwords after 90 days.

Following these best practices considerably reduces the risk of weak password-related security mishaps.

4 Best Practices for Email Security

Various email security tools and practices help users defend against email security risks. You can use them to detect and prevent email-based threats.

Here are some common security tools and solutions used to prevent security risks:

  1. Anti-Spam Filters:
    Anti-spam filters block unsolicited and unwanted emails, such as spam and phishing emails. These filters use algorithms and heuristics to identify and block emails that are likely to be malicious.
  2. Anti-Malware Software:
    Anti-malware software is used to detect and remove malware from emails and other files. This software uses signature-based detection, behavior-based detection, and other techniques to identify and eliminate malware.
  3. Email Encryption:
    It helps in protecting email communications from interception and avoids any unauthorized access. Moreover, email contents, metadata (sender and recipient information,) and attachments are also protected with this tool.
  4. Two-Factor Authentication:
    Two-factor authentication is significantly the best practice if you want to add an extra layer of security to your email accounts. The users are requested to provide a second form of identification besides a password, a one-time code sent on mobile devices, a fingerprint, a smart card, etc.
    By implementing these tools and solutions, users can significantly improve their email security posture and reduce the risk of email-based threats. One of the effective approaches is using these tools to ensure maximum effectiveness against evolving threats.


Email security risks can have serious business consequences, including data loss, financial damage, and reputational harm. However, by understanding the various types of security risks and implementing effective solutions, businesses can reduce the threat of a security breach and minimize the potential damage if it occurs.

It is also important for businesses to stay updated with the latest email security threats and regularly assess and update their security measures to stay ahead of potential risks. By prioritizing security and taking a proactive approach to risk management, businesses can protect their data, finances, and reputation from the potentially devastating consequences of a security breach.

Mainframe vs. Server: How Are They Different?


While choosing the right technology for your organization, it’s essential to understand the differences between mainframe vs server. After all, mainframes have been the backbone of large organizations for decades. However, servers have become increasingly popular recently, offering scalability and affordability for many applications.

But what exactly sets these two technologies apart, and which is right for your business? Although cloud computing provides businesses with greater scalability, cost savings, flexibility, security, and reliability than traditional mainframes or servers.

In this article, we’ll take a closer look at both techs’ key differences, strengths, and weaknesses to help you make an informed decision.

What is a Server?

A server is a network device that manages access to hardware, software, and other resources while serving as a centralized storage place for programs, data, and information. It may host anything from two to thousands of computers at any time. Accessing data, information, and applications on a server using personal computers or terminals has become easier. 

What is a Mainframe?

A mainframe’s data and information can be accessed via servers and other mainframes. However, the increased scalability can only be accessed with cloud services that allow businesses to quickly and easily increase or decrease the resources they use, depending on their needs. Unfortunately, this is not possible with mainframes or servers.

Enterprises can use mainframes to bill millions of consumers, process payroll for thousands of employees, and handle inventory items. According to research, mainframes handle more than 83 percent of global transactions. 

Differences Between Mainframe And Server

Continuing the debate on server vs mainframe, these are two of the most important computer systems used in today’s businesses. Both are designed to handle large amounts of data and processing power, but they differ in several ways and have diverse strengths and weaknesses.

Size and PowerMainframes are large and powerful computers designed to handle heavy workloads. These computers today are about the size of a refrigerator.
Mainframes can process massive amounts of data and support thousands of users simultaneously, making them ideal for large organizations with critical applications.
A typical commodity server is physically smaller than a mainframe designed for specific tasks or tasks. They can range in size from a small tower computer to a rack-mounted System.
Servers often support specific business functions, such as File and print services, web hosting, and database management.
User CapacityMainframes are designed to handle many transactions per second, providing fast and reliable access to data.Servers are known to support fewer users. They are designed to handle a smaller workload but can be scaled up to support more users if necessary.
CostMainframes are more expensive than servers in terms of initial investment and ongoing maintenance costs. They require significant hardware, software, and personnel investment to set up and maintain. However, their reliability and security can justify the cost for organizations with critical applications.Servers are typically less expensive, making them a more cost-saving option for smaller businesses or those with less critical applications. They are easier to set up and maintain and require fewer resources to run.
ApplicationsMainframes run critical applications, such as financial transactions and airline reservations, where dependability and safety are of utmost importance.
They are constructed to handle massive amounts of data exclusively and provide quick and efficient access to information.
The server can be used for various tasks, including file and print services, web hosting, and database management.
They are often used to support specific business functions and can be scaled up to cater to the ever-changing business demands.
Reliability Mainframes are known for their high levels of reliability and uptime. They are capable of handling critical applications and providing protected and faster access to data, even during a system failure.
They are also equipped with advanced security features to secure sensitive information.
Servers can be less reliable due to their smaller size and limited resources. They can handle different workload levels than mainframes and may provide different levels of reliability and uptime efficiency.

Suitable Use Of Mainframe Computers in various industries and why?

Once upon a time, the term “mainframe” referred to a massive computer capable of processing enormous workloads. Mainframe is useful for health care, schools, government organizations, energy utilities, manufacturing operations, enterprise resource planning, and online entertainment delivery.

They are well-suited for the Internet of Things (IoT), including PCs, laptops, cellphones, automobiles, security systems, “smart” appliances, and utility grids. 

IBM z Systems server control over 90% of the mainframe market. A mainframe computer differs from the x86/ARM hardware we use daily. Modern IBM z Systems servers are far smaller than previous mainframes, albeit they are still significant. They’re tough, durable, secure, and equipped with cutting-edge tech.

The possible reasons for using a mainframe include the following:

  1. The latest computing style
  2. Effortless centralized data storage
  3. Easier resource management
  4. High-demand mission-critical services
  5. Robust hot-swap hardware
  6. Unparalleled security
  7. High availability
  8. Secure massive transaction processing
  9. Efficient backward compatibility with older software
  10. Massive throughput
  11. Every component, including the power supply, cooling, backup batteries, CPUs, I/O components, and cryptographic modules, comes with several impressive levels of redundancy.

Mainframe Support Unique Use Cases

Mainframes are unique to be utilized when the commodity server cannot cope. The capacity of a mainframe to handle large numbers of transactions, their high dependability, and support for various workloads make them indispensable in various sectors. The companies may use commodity servers and mainframes, but a mainframe can cover gaps that other servers can’t.

Mainframe Handle Bigdata

According to IBM, the Z13 mainframe can manage 2.5 billion daily transactions. That’s a considerable quantity of data and throughput. To handle big data, you must look for a server upgrade to a mainframe. 

It’s challenging to compare directly to the commodity server since the number of transactions they can support varies depending on what’s on the server in question. Furthermore, the sorts of transactions may be vastly different, making it impossible to compare apples to apples.

However, assuming that a typical database on a standard commodity server can handle 300 transactions per second, it works out to roughly 26 million transactions per day, a significant number but nothing near the billions a mainframe can handle.

Mainframes Run Unique Software (Sometimes)

Mainframes are generally driven by mainframe-specific programs written in languages like COBOL, which is a significant differentiating characteristic. They also use proprietary operating systems, such as z/OS. Three important points to ponder are:

  • Mainframe workloads cannot be moved to the commodity server.
  • You may transfer tasks that typically run on a commodity server to a mainframe.
  • Virtualization allows most mainframes to run Linux as well as z/OS.

As a result, the mainframe provides you with the best of both worlds: You’ll have access to a unique set of apps that you won’t find anywhere else and the capacity to manage commodity server workloads.

Mainframe May Save Money If Used Correctly

A single mainframe can cost up to $75,000, considerably more than the two or three thousand dollars a decent x86 server could cost. Of course, this does not imply that the mainframe is more costly and fails to meet your demands or to offer something incredibly extra. Remember, with a $75,000 mainframe, you’ll receive much more processing power than a commodity server. 

However, cloud computing is often more cost-efficient than investing in and maintaining expensive mainframes or servers.


Mainframes and servers are high-functioning computer systems with various pros and cons. Organizations with critical applications may benefit from the high reliability and security of mainframes. In contrast, those with less critical applications may find servers a more affordable option. However, the choice between a mainframe and a server will depend on the specific needs of the organization and the applications it needs to run.


Cybersecurity Laws And Regulations In US [2023]

Cybersecurity laws and regulations in the US are essential because they help protect sensitive information and critical infrastructure from cyber threats such as hacking, malware, and data breaches. These laws and regulations also provide a framework for organizations to secure their networks and systems. 

Additionally, these cyber laws and regulations help to ensure that companies and individuals are held accountable for any cyber incidents that may occur and that victims of cybercrime have legal recourse. 

All the laws and regulations provide a baseline for protecting sensitive information and critical infrastructure from cyber threats and attacks. However, it’s important to note that some laws and regulations may only apply to specific industries or organizations and that compliance may vary based on the particular situation.

We will cover Federal Cybersecurity Laws and some Cyber Security Laws by State.

Federal Laws and Regulations

Here are federal cybersecurity laws and regulations that businesses need to comply with!

  1. Federal Information Security Modernization Act (FISMA)

    The Federal Information Security Modernization Act (FISMA) is one of the cyber security laws in US passed in 2002. It requires federal agencies to implement security controls to protect their information systems and data.

    They aim to ensure that federal agencies have the necessary measures to protect the confidentiality, integrity, and availability of the information they collect, store, and use.

    They also require agencies to establish an information security program that includes regular risk assessments, security testing and evaluations, incident response planning, and continuous monitoring of security controls. It also requires agencies to report their compliance with the law to the Office of Management and Budget (OMB) and the Department of Homeland Security (DHS).

    Also Read: 9 Best Cybersecurity Podcasts to Follow

    FISMA also established the National Institute of Standards and Technology (NIST) as the primary body responsible for developing security standards and guidelines for federal agencies.

    NIST has published a set of guidelines known as the “NIST Special Publication 800-53,” outlining the security controls federal agencies must implement to comply with FISMA.

  2. Cybersecurity Information Sharing Act (CISA)

    The Cybersecurity Information Sharing Act (CISA) is a law passed by the United States Congress in 2015 that encourages private companies to share information about cyber threats with the government and provides liability protections for companies that do so.

    CISA aims to improve the sharing of information about cyber threats between the government and private sector to protect critical infrastructure and national security from cyber attacks. It allows private companies to share cyber threat information with the Department of Homeland Security (DHS) and other federal agencies and also enables the government to share cyber threat information with private companies.

    The law also provides liability protections for companies that share information in good faith and intend to protect against cyber threats. It includes provisions for developing information-sharing and analysis organizations (ISAOs) that would facilitate sharing of cyber threat information between the government and private sector.

    The ISAOs are voluntary organizations that private companies or other organizations can create to share cyber threat information among their members. CISA has been criticized by some privacy and civil liberties advocates who claim that the law does not adequately protect personal information and could be used for government surveillance. 

    Various organizations offer cybersecurity consulting services, but choosing the right one can be difficult. EES specializes in helping businesses assess, design, and implement security measures to protect their data, systems, and networks with best-in-class Cyber Security Consulting Services.

Role of Government Agencies

Role of government agencies such as the Department of Homeland Security (DHS), the Federal Bureau of Investigation (FBI), and the Cybersecurity and Infrastructure Security Agency (CISA).

  1. Department of Homeland Security (DHS)

    The Department of Homeland Security (DHS) plays a key role in protecting the United States from cyber threats and attacks. The DHS is responsible for protecting the nation’s critical infrastructure, which includes everything from the power grid and financial systems to transportation networks and government buildings.

    One of the DHS’s main responsibilities is coordinating and sharing information about cyber threats with other federal agencies, state and local governments, and the private sector. The DHS also works to develop and implement cybersecurity policies, guidelines, and standards to help protect the nation’s critical infrastructure from cyber attacks.

    The DHS has several key organizations within it that are responsible for different aspects of cybersecurity. The National Cybersecurity and Communications Integration Center (NCCIC) is responsible for identifying, analyzing, and responding to cyber threats and providing real-time situational awareness of the cyber threat landscape. The Cybersecurity and Infrastructure Security Agency (CISA) protect the nation’s critical infrastructure from cyber threats and provides technical assistance and guidance to other organizations.

    The DHS also plays an important role in incident response and recovery. For example, the United States Computer Emergency Readiness Team (US-CERT), part of the NCCIC, is responsible for coordinating the response to cyber incidents and providing technical assistance and guidance to organizations affected by cyber attacks.

  2. Federal Bureau of Investigation (FBI)

    The Federal Bureau of Investigation (FBI) plays a key role in protecting the United States from cyber threats and investigating cybercrime. The FBI is responsible for investigating a wide range of cybercrimes, including hacking, online fraud, identity theft, and the distribution of child pornography.

    One of the main responsibilities of the FBI is to investigate cybercrime and bring criminals to justice. The FBI has several specialized units that focus on cybercrime, such as the Cyber Division, which investigates cybercrime and espionage. The FBI also works closely with other federal, state, and local law enforcement agencies to share information and coordinate investigations.

    The FBI also plays an important role in protecting the United States from cyber threats by providing threat intelligence and warnings to organizations and individuals. The FBI also improves organizations’ cybersecurity posture by providing training and technical assistance.

    The FBI also works with other U.S. agencies and international partners to track and pursue cybercriminals and hackers outside of the U.S. and develop and implement international strategies to combat cybercrime.

    The FBI works with other federal, state, and local law enforcement agencies, the private sector, and international partners to pursue cyber criminals, improve organizations’ cybersecurity posture, and provide threat intelligence and warnings to organizations and individuals.

  3. Cybersecurity and Infrastructure Security Agency (CISA)

    The Cybersecurity and Infrastructure Security Agency (CISA) is a federal agency within the Department of Homeland Security (DHS) responsible for protecting the nation’s critical infrastructure from cyber threats and providing technical assistance and guidance to other organizations.

    CISA’s mission is to protect the nation’s critical infrastructure by enhancing the security and resilience of the cyber ecosystem. This includes working with other government agencies, the private sector, and international partners to identify and mitigate cyber threats and vulnerabilities.

    Some of the key responsibilities of CISA include the following:

    • Identifying and assessing cyber threats to critical infrastructure
    • Providing technical assistance and guidance
    • Coordinating incident response
    • Developing and implementing cybersecurity policies, guidelines, and standards
  4. The National Institute of Standards and Technology (NIST)

    The National Institute of Standards and Technology (NIST) is a non-regulatory agency of the United States Department of Commerce. It was established in 1901 and had its headquarters in Gaithersburg, Maryland. NIST’s mission is to promote innovation and industrial competitiveness by advancing measurement science, standards, and technology to enhance economic security and improve our quality of life.

    NIST conducts research and provides technical assistance in a wide range of areas, including:

    • Advanced manufacturing
    • Cybersecurity
    • Information technology
    • Material measurement
    • Quantum technology
    • Telecommunications

    NIST also provides industry-standard measurements and standards, such as standard reference materials, standard reference data, and standard reference methods. These standards are used to ensure the accuracy and reliability of measurements in many fields, including science, engineering, and industry.

  5. The Government Accountability Office (GAO)

    The Government Accountability Office (GAO) plays a key role in conducting audits and investigations of federal agencies to assess their compliance with federal cybersecurity laws and the effectiveness and efficiency of their operations. This includes their management of cybersecurity risks and threats.

    One of the ways the GAO conducts these audits and investigations is through the use of performance audits. These audits assess the effectiveness and efficiency of government programs and operations. They can focus on cybersecurity issues, such as the adequacy of an agency’s information security controls and incident response plans. The GAO also conducts financial audits of federal agencies, including assessments of their compliance with laws and regulations related to information security and protecting sensitive information.

    The GAO also conducts investigations in response to requests from Congress or other government officials. These investigations can focus on specific cybersecurity issues, such as the adequacy of an agency’s cybersecurity programs or incident response plans.

    By hiring an Expert Cyber Security Consultant from EES, companies can identify their vulnerabilities and weaknesses and take action to mitigate them. Additionally, our services can help companies comply with cybersecurity laws and regulations and implement best practices to protect their sensitive data, systems, and reputation.

State-specific Laws and Regulations

Businesses must be aware of the applicable cyber security laws by state. Many are related to data collection techniques and the requirement to alert customers within specific timelines and ways if data is breached.

  1. California Consumer Privacy Act (CCPA)

    The California Consumer Privacy Act (CCPA) is one of the cyber security laws by state passed in California in 2018. It came into effect on January 1, 2020, and gives California residents certain rights regarding their personal information collected, used, and shared by businesses. These rights include the right to know what personal information is being collected, the right to request that it be deleted, and the right to opt out of the sale of personal information. 

    The California cybersecurity laws apply to businesses that collect personal information of California residents and meet specific other criteria, such as having annual gross revenues over $25 million, buying or selling personal information, or having the personal information of 50,000 or more California residents.

  2. New York Department of Financial Services (NYDFS)

    The New York Department of Financial Services (NYDFS) is a state government agency in New York that oversees the regulation and supervision of financial services companies operating in the state. The NYDFS is responsible for enforcing laws and regulations related to banks, insurance companies, mortgage companies, money transmitters, and other financial service providers. 

    Its mission is to protect consumers and ensure the safety and soundness of the financial services industry in New York. The NYDFS has the authority to issue licenses, conduct examinations of financial institutions, and take enforcement actions against companies that violate laws and regulations. The agency also promotes fair and transparent markets and improves the financial system’s overall stability and security in New York.

  3. Other states’ laws and regulations

    In addition to the California Consumer Privacy Act (CCPA) and the New York Department of Financial Services (NYDFS), several other cyber security laws by state govern the collection, use, and sharing of personal information. Some examples include:

    • The Vermont Data Broker Regulation Act requires data brokers to register with the state, disclose their data collection practices, and allow consumers to opt out of the sale of their personal information.
    • The Illinois Biometric Information Privacy Act Law regulates the collection, use, storage, and disclosure of biometric information, such as fingerprints or facial scans. It requires companies to obtain informed consent before collecting this information.
    • The Nevada Privacy of Medical Information Act regulates the collection, use, and disclosure of personal health information and requires companies to implement reasonable security measures to protect this information.
    • The Texas Medical Privacy Act Law regulates the collection, use, and disclosure of personal health information and sets standards for protecting personal health information.
    • The Washington State Data Privacy Law regulates personal information collection, use, and disclosure. It requires companies to provide clear and conspicuous notice of their data collection practices and to provide a mechanism for consumers to opt out of the sale of their personal information.

    It’s important to note that cyber security laws and regulations regarding data privacy and protection are continuously evolving, and many more state laws and regulations regulate this area, depending on the state. It’s recommended to check all the cyber security laws by state to ensure compliance.


Staying informed about cybersecurity laws in the US is important for several reasons.

  1. Compliance

    Businesses must comply with various laws on cyber security, such as the General Data Protection Regulation (GDPR), the Health Insurance Portability and Accountability Act (HIPAA), and the California Consumer Privacy Act (CCPA). Failure to comply with these laws can result in significant fines and penalties.

  2. Risk Management:

    Understanding the current laws and regulations can help businesses identify and mitigate cybersecurity risks. This includes identifying sensitive data that must be protected and implementing appropriate security controls to protect that data.

  3. Reputation and Liability:

    A data breach or cybersecurity incident can damage a business’s reputation and lead to liability lawsuits. Staying informed about laws and regulations can help companies take proactive steps to prevent incidents and respond if they occur.

  4. Staying Competitive:

    Businesses knowledgeable about cybersecurity laws and regulations are better equipped to compete in the marketplace. They can demonstrate to customers and partners that they take data protection seriously and have the necessary controls to protect sensitive information.

  5. Protecting Customers’ & Employees’ Personal Information:

    By staying informed about cyber security laws, businesses can ensure that they are appropriately protecting the personal information of their customers and employees. This includes not only preventing data breaches but also being transparent about data collection practices and providing customers with the ability to control their personal information.

    Given the constantly evolving nature of technology, businesses need to stay updated with cyber laws and regulations. This includes regularly reviewing policies and procedures, participating in training and education programs, and consulting with legal and cybersecurity.

DevOps As A Service AWS

The combination of the latest and advanced tools, practices, and techniques to optimize and enhance the productivity of an organization is called DevOps. It helps an organization to serve its customers efficiently. Organizations working in infrastructure management and software development environments can optimize and speed up the processes.

Why AWS for DevOps?

According to cloud DevOps consulting, DevOps as a service AWS is the best solution because of specific reasons such as:

Fully-Managed Services:

DevOps Services and Solutions are fully managed. Your organization and staff must not worry about installing and deploying infrastructure and applications. It helps your team to concentrate and focus on the core task.


Each of the resources and services can be used with the help of the AWS Command Line Interface. Your organization can model and design the customized resources and infrastructure as required.

Quick Start:

If you have an AWS account, these services are ready to start. There’s no need and time consumption for installation or deployment. None of the setups is required to start it.

Secure and Protected:

It has a well-developed Identity and Access Management system, making its services the most secure and protected. Through authentication algorithms, you can monitor and regulate access to resources and limit or restrict sensitive and confidential areas.


It enhances the process and management via automation. You can automate manual tasks such as test workflows, develop workflows, configuration management, deployments, installations, and container management.

Built for Scale:

These services are scalable and flexible; an individual or a full-fledge enterprise can manage these services. These services can help you configure, simplify, and scale compute resources.

Large Partner Ecosystem:

It supports the integration of third-party tools. Your organization might integrate the open-source tools from any other source with AWS tools to form an end-to-end solution. In that way productivity of the solution can be increased.

The following are some of the other main perks of AWS pricing services:

  • No termination fines and penalties
  • Long term contracts
  • Upfront fees
  • Customized purchase period
  • You can terminate the subscription at any time

What are the Benefits of DevOps?

DevOps as a service AWS is the most efficient and reliable DevOps. It can offer your organization the following benefits:

  1. Immediate delivery and responses to the customer response
  2. Rapid speed of the process
  3. Reliability is ensured by the best practices
  4. Interoperable technology
  5. Quick adopt and deploy, leading to time and cost-saving
  6. Scalability and flexibility are the key benefit
  7. Security and protection from risks and vulnerabilities by the incident response and management
  8. Supports collaboration of third-party
  9. Open source tools can be integrated with AWS tools

What are the Core Practices of DevOps?

The following are the core practices of DevOps as a service:

  1. Continuous Testing:

It ensures the continuous assessment of the changes in the development process. Testing techniques and strategies give quick feedback to developers, ensure quality, and reduce bottlenecks in the whole delivery development process.

  1. DevSecOps:

Application security is the most crucial point for the security of your management and monitoring processes. It can save your effort, cost, and time in determining and screening the security flaws and vulnerabilities, leading to a secure and protected environment and workspace.

  1. Code Repos and Artifact:

Artifact management solutions and Code repositories based on Git are the critical components of all DevOps practices. They can help in the following ways:

  • Optimize the management process
  • Supports the use of multiple applications
  • Independent delivery and offering of values and services to the customer
  • Helps the team maintain autonomy
  1. Incident Management:

It provides the best incident practices by ensuring the following offerings:

  • Effective incident response and management
  • Implements continuous monitoring and regulating solutions
  • Excellence and performance efficiency of the application
  • Automated issue tracking and tracking
  • Process, delivery, and application management
  • Routing of the responses to the inquiries and queries
  1. Infrastructure as a Code:

Infrastructure as a code helps in the below-mentioned ways:

  • Eliminates the time taking and consuming rollbacks
  • Supports configuration, programmatical build, and destruction of the workspace
  • Enables self-service
  • Reduce the chances of errors and risks
  • Automates the maintenance processes
  1. Observability and Monitoring:

Continuous delivery and continuous delivery pipeline influence and supports insights such as:

  • Data-driven insights
  • DevSecOps lifecycle
  • Implements automation
  • Reliability, health, and performance of the application
  • Automation and virtuous cycles
  • Scalability of the infrastructure in IT operations

What is the Architecture of AWS DevOps?

The architecture of AWS DevOps consists of the mentioned components:

  1. Load balancing
  2. Amazon CloudFront
  3. Amazon Security Group
  4. Amazon Relational Database Services (ARDS)
  5. Elastic caches
  6. Amazon’s simple storage service (S3)
  7. Amazon Auto-Scaling
  8. Amazon Elastic Book Store (EBS)

What are the AWS DevOps Services?

AWS provides the following DevOps services and solutions:

  1. DevOps on AWS cloud
  2. AWS managed services
  3. AWS migration services
  4. AWS assessment services

Bottom line

As a service by AWS, DevOps offers the best cloud services and solutions for your organization with tools ranging from application development to management.


How AI can Improve Cloud Computing?

The cloud is the natural environment for artificial intelligence. The AI cloud, a concept that combines artificial intelligence (AI) with cloud computing, is just now being used by businesses. There are two reasons for this: Cloud computing is no longer only a cost-effective solution for data storage and processing but a critical component in the adoption of AI.

Using AI to aid in the automation of routine IT infrastructure improves efficiency. The combination of cloud computing with artificial intelligence (AI) provides a massive network capable of storing enormous data while also learning and improving over time now; let us explain how AI can improve cloud computing.

How AI can Improve Cloud Computing?

The AI cloud’s ability to address problems is the most compelling advantage. In this way, artificial intelligence (AI) becomes more accessible to a broader range of people. Because AI-enabled transformation decreases adoption costs and makes it simpler to collaborate and generate new ideas, enterprises benefit from AI-enabled transformation.

Using AI to give strategic inputs for decision-making is made possible by the cloud’s agility, adaptability, and scale. The cloud substantially enhances AI’s reach and impact, first with the user organization and then moving to the larger market. AI and the cloud are mutually reinforcing, enabling AI to blossom on the cloud to its full potential.

AI Cloud Solutions

Companies may become more efficient, strategic, and insight-driven using cloud computing enabled by artificial intelligence. In order to boost productivity, artificial intelligence (AI) can do complex and repetitive tasks and analyze data without human intervention.

An AI system may analyze data sets of any size for patterns and trends. Because it contrasts old and new data, data-driven insight is valuable to IT workers. As a result, companies can answer customers’ queries and concerns more swiftly and effectively, thanks to AI technology. Artificial Intelligence (AI) may provide insights and suggestions that lead to improved results may be provided through Artificial Intelligence (AI). With Amazon Personalize, you can provide your customers with in-app recommendations that are updated in real-time. EES cloud computing consulting services can help you modernize your infrastructure.

Benefits of using AI Cloud Solutions


  • To design AI solutions, cloud computing makes it simpler. You may be able to receive better results for less money.
  • Google, Amazon Web Services (AWS), or Microsoft Azure may all be used to store your data in the cloud. We can develop solutions that minimize the danger of lock-in to protect your investment.
  • Develop an end-to-end Cloud solution or integrate AI, machine learning, or forecasting into an existing application.
  • Familiar with Google Cloud AI Platform, Sagemaker, AWS Azure Machine Learning, and Cloud Python and R data science deployments.
  • Knowledgeable
  • Maintenance training will be required when the project is completed.

Cloud AI Services Consulting

Companies are working hard to ensure that cloud computing services are consistently enhanced, although general and not tailored to specific requirements. Cognitive computing may teach a computer to provide certain services depending on the information it gets from its consumers. Finding the best algorithm or training model is no longer necessary.

Expertise from cloud computing consultants can help businesses take advantage of the most recent and finest cloud data centers, clouds, and data warehouses. Consultants aid in selecting and implementing best practices for your company’s use cases in the cloud. If your firm is contemplating migrating to the cloud or implementing new technologies, hiring the services of a cloud computing specialist might be a good decision.

Cloud consulting services are provided by several prominent firms, including Deloitte, Accenture, AWS, Capgemini, IBM, Cognizant, too many of the Fortune 100 global enterprises. These cloud consultants’ clients have very particular and comprehensive requirements from all across the globe. A cloud AI services consulting firm with an excellent reputation and considerable industry experience may be the ideal choice for medium- and small-sized businesses., for example, is a fantastic choice. We provide a wide range of cloud services for several platforms.

Final Verdict

It is becoming more critical for organizations to secure their data in the cloud as more and more cloud-based services are used. Using AI-powered tools, IT departments can monitor and analyze traffic on their networks. A flag may be raised when an AI-powered system notices anything out of the ordinary. This proactive approach assures the safety of confidential information. An example of this is Amazon GuardDuty, which uses AI and machine learning to detect potential risks.

AI cloud solution has made data processing, administration, and organization simpler. AI’s marketing, customer service, and supply chain data management may benefit substantially from more reliable real-time data describing how AI can improve cloud computing. Data can be consumed, updated, and managed more efficiently using artificial intelligence (AI) tools. Use Google Cloud Stream analytics for real-time personalization and anomaly detection to help IT organizations better plan maintenance scenarios.


How is Machine Learning used in E-Commerce?

E-commerce organizations can use machine learning to provide a more personalized client experience. Customers today not only want to engage with their favourite businesses on a personal level; instead, they have evolved to demand it. In fact, according to research, 73 per cent of customers are tired of being bombarded with useless content.

Retailers may use artificial intelligence and machine learning to tailor each connection with their customers, giving them a better experience. They can use machine learning consulting to prevent customer service problems in advance.

Cart turnover rates should decrease as a result, and sales should increase. Customer support bots, unlike humans, can deliver unbiased responses 24 hours a day, seven days a week.

How is Machine Learning used in E-commerce?


The recommendation engine is the most extensively utilized role of AI in e-commerce. A good product recommendation algorithm can significantly increase your income and average order value.

A recommendation method is a sophisticated data filtering tool that uses machine learning algorithms to suggest the most appropriate product to a buyer.

The algorithms use information such as the customer’s most recent purchase, purchasing history, preferred colors, typical budgets, etc.

Pricing Optimization

Using machine learning consulting, retailers can calibrate prices driven by supply and demand, minimum price, operational expenses, competitiveness, and other factors.

Manually completing all of this isn’t easy. AI automates massive volumes of data collecting, processing, and analysis to provide better real-time dynamic pricing. This also aids organizations in recognizing early trends and forecasting demand for products for which transaction data is not available.

Fraud Protection

Chargebacks are the biggest nightmare of any online retailer. Most shoppers, especially first-time customers, believe that e-stores are untrustworthy. E-commerce stores are vulnerable to fraudulent activity. E-commerce business owners must exercise extraordinary prudence. It is not uncommon for businesses, especially internet businesses, to shut their gates due to a bad image. As a result, companies must not cut corners when detecting and combating fraud.

Machine learning can substantially limit the scope of fraudulent behavior. It can quickly evaluate large amounts of time-consuming, recurring data and detect illegal transactions earlier on by proactively detecting any abnormalities.

Image Processing

Retailers engage in artificial intelligence (AI) and image recognition technologies to influence consumer (buyer) behavior and automate processes. Investing in information visualization with visual search capabilities could help you match images of consumers with similar clothing sold online, for example. This could be determined by a user’s request based on the type of things they typically purchase (color, brand) and data from media platforms.

Another e-commerce machine learning application is its help in automatically filling in the subject information based on the photo.

Retargeting, Upselling, and Discounts

Not every person who visits your website will make a purchase. Some may seek product information, while others may put something in their cart and then abandon it. Using dynamic retargeting, upselling, and discounts, machine learning consulting can assist get more individuals to finish their transactions.

Machine learning allows e-commerce stores to better retarget consumers by analyzing data to see what has worked in the past to acquire similar profiles via retargeting. ML analyses millions of profiles, analyzing their behavior and outcomes to anticipate what will most likely convert a consumer.

Trend Analysis

Before you put things available for auction on an e-site, you should research their popularity: is it a best-seller, a regular seller, or out of date?

Whether from an outsourcing provider or internal fulfillment, procurement is influenced by trend analysis. If statistics are not carefully monitored, returned items will play a significant role in procurement. As a result, analyzing a product’s trend is crucial, as it can help lower the catalog’s total size, product maintenance costs, and warehouse space utilization.

This is made simple with machine learning because it analyses and compares product evaluations, ratings, and media platform inputs. Low-rated products may be removed from the site’s inventory.

Better Inventory Management

Inventory management is one of the most persistent issues in e-commerce. Manual stock control can be time-consuming (particularly for e-commerce stores) and can hurt accurate sales forecasting, leading to financial flow issues. ML can significantly improve the accuracy of future demand predictions. It will make supply chain management more accessible, but it will also ensure that you better understand your clients and their behaviors.

Stock replenishment is required to avoid stockouts and guarantee that client requests are met promptly. Inventory replenishment can be automated using Artificial Intelligence algorithms based on previous and current sales information. This can be set up for “Pick up from store” and “Deliver to customer” scenarios.

Final Verdict

Machine learning is here to stay in e-commerce. It has various practical applications in eCommerce, as we’ve seen. How machine learning is used in e-commerce may interest you if you wish to improve your e-commerce operations.

Machine learning is being embraced by many e-commerce companies, which are reaping significant benefits from it. ML may be a substantial advantage for firms that automate time-consuming, labor-intensive, and costly manual procedures. It can provide internet retailers with helpful information on their customers. They can assist internet businesses in increasing clicks, converting prospects into customers, keeping them, and even developing strong customer relationships.



How to Use AI and Machine Learning for Cyber Security?

You’re probably familiar with the term “machine learning.” You might have heard of “artificial intelligence,” too. But do you know the difference between AI and machine learning? And how does machine learning consulting work?

We’ve got answers.

What is Machine Learning?

Machine learning is a study that comes after artificial intelligence that allows machines to learn from data without a human. This is possible through statistical modelling and machine learning algorithms, which are used to identify sketches in data and make assumptions based on what they find. Models are then trained, validated, and tested before they can be deployed to the real world.

That’s essentially what machine learning consulting is all about: building models that give you insights into your data so you can take action based on what you find.

How to Use AI & Machine Learning for Cybersecurity?

In cybersecurity, machine learning is primarily used to protect networks.

It could be protecting a company’s network or even a national grid from cyberattacks or natural disasters. The goal of these types of applications is to protect valuable information like patient records or confidential military secrets from falling into the wrong hands. To accomplish this, companies use Machine Learning Consulting services.

Here’s the good news for AI and machine learning consulting: Machine learning is a very powerful tool for cyber security. The bad news? It can be confusing.

What Exactly makes AI and Machine Learning so Valuable for Cyber Security

Machine learning is an essential part of any robust system that wants to protect itself against unwanted intrusions. In short, it helps your system learn to recognize patterns that might indicate an intrusion. This means that your system will become more adept at detecting threats over time and tailor its responses to new types of threats as they emerge.

Machine learning works by “training” the system to recognize patterns and then using those patterns to make predictions. This type of program has two primary parts: one, which we’ll call the “model,” is responsible for making predictions, while another, which we’ll call the “code,” uses these predictions to update the model as new data becomes available.

When you use a machine-learning algorithm, it’s important to remember that it’s not just a set of instructions—it’s also an evolving process. The code needs to adapt over time in order to stay effective against new threats. As hackers get smarter and more aggressive, you need to stay one step ahead. And that’s why we’re here to help.

We’ll teach you how to use AI and machine learning in cyber security to identify threats before they happen and take action when they do to your business. Our team of experts will guide you through the world of AI and machine learning, look at your current systems, and work with you to design a solution that works for your business. As your consultants, we’ll make sure you have the knowledge and tools you need to protect your business from cyberattacks—now and in the future.

Here are some Factors that AI and Machine Learning can be used for Cyber Security


Artificial Intelligence (AI) and Machine Learning (ML) have been in the news for quite some time and have generated a lot of buzz. Companies are using these technologies from various industries to solve different problems. Machine learning uses AI to identify patterns in massive data sets and utilize those patterns to make predictions about new data.

In today’s digital landscape, new threats are popping up every day. Fortunately, we’ve got an arsenal of tools that can help us guard against these threats and protect both our data and our people.

Artificial intelligence (AI) and machine learning have gained traction recently as some of the most useful weapons in the fight against cyber security threats. When used correctly, they allow us to identify malicious files before they attack our systems, recognize patterns that indicate potential future problems, and even take automatic action to defend against attacks.

In cyber security, machine learning is used to detect threats, prevent attacks, and respond to breaches by using algorithms that can process huge amounts of data in real time.

Get The Right Help With EES

A machine learning consulting firm like EES can help you figure out how best to implement this technology in your business and how to develop the resources needed for a successful implementation. The difference between AI and ML is like a robot and a computer. While they both rely on each other, they are separate entities.

Robots rely on AI to function, and computers rely on machine learning. They are both parts of a whole but different.


What are the Characteristics of Big Data?

Big data consulting is a service where experts work with you to help you identify, collect, and analyze big data in your business. Cloud data management services are often built on cloud infrastructure and provide a way for your company to store, manage, and protect its data. Big data is any dataset that’s too big for the tools you have to analyze it or your computer’s memory. If you’re using Excel to store and analyze your data, you’re probably only dealing with small data—but if your dataset is so large that Excel can’t handle it, you’re dealing with big data.

When you need help handling your big data projects, get in touch with EES Corporation, a big data consulting firm. We offer a wide range of cloud-based data management services that make it easier to work with massive datasets, no matter what format they’re in.

A Quick Overview of the Big Data

Big data is a term that refers to the fact that companies and organizations are now able to collect and analyze massive amounts of data. This is possible due to increased computing power, advances in technology, and the increasing amount of information people create online and offline. Big data can also be characterized by its velocity, variety, and veracity. Velocity refers to how quickly the data is being generated; variety refers to the different types of datasets being analyzed; veracity refers to how reliable or trustworthy the datasets are.

The volume of data that companies collect is staggering; even if you’re not actively collecting data as part of your business model, there are important insights to be gained from the information you already have. While you may already be familiar with some types of data analysis, like running reports on sales or website traffic in Google Analytics, there are a number of other areas where your business can benefit from taking the time to analyze your data.

Some Characteristics of Big Data are:


  1. It’s not always easy to analyze with traditional tools
  2. It can be difficult to get accurate results without a lot of time and effort
  3. It can provide insights into customer behavior and preferences, which may lead to more sales or improved marketing efforts
  4. The amount of information available is enormous, but so are the possibilities!

If you’re new to the world of big data, it’s not the easiest concept to understand. At a very basic level, big data simply describes large volumes of data that are hard to work with using traditional methods. But beyond that, several factors contribute to what qualifies as big data:

Volume, It’s all in the name! Big data describes data sets that are so large they’re difficult to deal with in more traditional ways. The amount of data can be so much that it occupies storage space on several servers instead of just one. This volume can include anything from tweets and emails to website traffic logs and medical records.

The first V, volume, measures how much data is generated – but there is more to this than simply considering the amount of information coming in. Different types of information are often measured in different ways; for example, one megabyte of text is equivalent to 1 million characters but only 8 million bits (a bit is a single binary digit).

Velocity, This refers to how quickly new information is generated, collected and stored. For example, every second, Facebook users share over 684,478 pieces of content. Logging all this content in real-time would be impossible—so companies use automated tools to do it for them and then go back through it later at their leisure.

The Second V, Velocity, describes how fast your company or organization receives new information from its sources.

Variety, Not all information is created equal, especially when it comes to big data. There’s a wide variety of information that companies need to manage, including a mix of structured data (data with fixed fields) and instruction.

The third V, variety, refers to how many different types of data are collected. Some sources may be more valuable than others depending on what the business needs; for example, if you’re working at a hospital, you may want easy access to patient health records, but that same type of data wouldn’t be relevant in an auto shop.

Big Data Consulting

It is a form of consulting that helps businesses understand big data capabilities and work with it to improve their operations or make other kinds of business decisions. Big data actually states the large amounts of data that companies collect across social media, search engines, and other places. EES can help its clients and customers sort any kind of heavy data to sort it out for them. As businesses grow, they accumulate more and more of this data, which can be analyzed for patterns.


Top 5 Big Data Challenges

It is not easy to name the top 5 Big data challenges as it is data with volume, velocity, variety, and veracity. A massive amount of unstructured, raw, coming from different platforms and uncertain and imprecise is called big data. It can be defined as:


The volume of big data is primarily terabytes or even exceeding exabytes.


Data is created at the pace of approximately 1.7 megabytes per person per second.


The data is associated with various platforms as it is unstructured and raw when it is received.


A massive amount of data is imprecise and uncertain.

Top 5 Big Data Challenges

Big data faces the following top 5 challenges:

Big Data Security and Loopholes

Usually, at the time of big data deployment, security issues are ignored at the initial stages and phases, which is a significant challenge for the big data deployment process. Organizations and enterprises focus on analyzing, managing, storing, understanding, monitoring, and regulating the security data set aside. It sets the ground for attackers and hackers. Data breaches, record breaches, and database heists can lead to the loss worth up to the millions. Without spending a fortune, you can get multiple advantages from EES corporation agile, reliable, and scalable Cloud Big Data Consulting services, such as finding meaningful insights, performing data analytics, etc.


Big data security issues and loopholes can be handled in the following ways:

  • Organizations and companies should recruit more cybersecurity professionals.
  • Data encryption and segregation should be implemented in every phase.
  • Identity and access control and management should be regulated continuously.
  • Endpoint security should be practiced.
  • Real-time security tools and techniques should be used.

Scarcity of Professionals and Spending a Lot of Money

Most companies and enterprises lack skilled data professionals compatible with modern and advanced data tools and techniques. These qualified data professionals and expertise include data analysts, data specialists, and data engineers. Data managing and handling tools evolve and advance as per data need and time passage; meanwhile, data knowledge and understanding are not evolved accordingly. It creates a gap and space between tools and data professionals.

Big data adoption needs a lot of money investment such as:

  • Hiring and recruitments
  • Electricity and power expenses
  • Cloud services
  • Maintenance of frameworks
  • Expansions
  • Software development
  • Software configuration
  • Hardware maintenance and repair


Following are the best possible solutions for meeting the challenge of scarcity of professionals and spending a lot of money:

  • Companies and organizations should invest more in recruiting and hiring skilled professionals.
  • Companies should conduct more training programs and workshops.
  • Enterprises should buy artificial intelligence-powered knowledge analytic solutions.
  • Hybrid cloud solutions for companies with low budgets.
  • Data lakes offer the most reasonable data storage opportunities.
  • Optimized algorithms help reduce and decrease the power consumption of computers and systems being used.

Lack of Understanding and Knowledge of Big Data


Most of the time, organizations and enterprises neglect the comprehension of big data. Enterprises ignore the pros and cons of big data, the infrastructure needed to deploy correctly, and all other basic knowledge of big data. Suppose the current processes and algorithms of big data are not altered according to the requirements of the enterprise, instead of advancement. In that case, it can resist the organization from going for improvement and progress.

As big data is capable of massive changes, its knowledge and understanding are vital for all employees, including top management to ordinary workers. The utilization and deployment of big data depend on the acknowledgment of workers.


Enterprises and organizations should conduct regular workshops and training to ensure acknowledgment.

Big Data Growth Issues

One of the biggest challenges for companies, organizations, enterprises and businesses is to handle the rapidly increasing quantity of data. Usually, information received is unstructured, scattered, and dispersed from different sources such as text files, documents, audios, videos, and emails, making it difficult to search and find in a database. As the company progresses, data stored also grows exponentially as time passes.


Big data growth issues can be solved by several techniques such as compression, deduplication, and tiering techniques.


The compression techniques are used to reduce and compress the data bits leading to a significant reduction in the actual size of the data.


Deduplication includes removing and eliminating the duplicated and unwanted data from the bulk of data to decrease the overall data size.


Data tiering is technique companies and organizations use to store data bulks in appropriate and suitable spaces and environments, data storage tiers. Data tiers include the followings:

  • Public clouds
  • Private clouds
  • Counting on the information size
  • Flash storage

Integrating Data

Integrating data from all different platforms is one of the most challenging works for IT personnel. Most of the data come in dispersed and disassembled forms from other platforms. Sometimes half of the platforms are not supported locally. The developer must continuously alter the program or source code if the data is received in an unsupported form. It leads to the slow processing of the advancement cycle of the organization or enterprise.

In that way, many big data processing platforms create a huge hindrance and challenge for IT to re-arrange the complete infrastructure.


The best solution for this challenge is the software automation tools with APIs for considerable data, records, and databases.

Capgemini vs Deloitte: Which is best for cloud services?

Deloitte is one of the largest and most prominent services worldwide. However, Capgemini offers impressive project management, meeting presence, updates, and implementation. Also, they are easy on customer pockets. This article will highlight and compare Capgemini vs Deloitte cloud services in detail.

Capgemini vs Deloitte – Cloud Services

The Cloud is laying the foundation for businesses to become digitally agile.


Capgemini Cloud helps businesses harness innovation to open new collaboration and value chain optimization avenues. It is revolutionizing how we work and live by giving people the capacity to do more with less—accelerating human novelty.


Deloitte propels business transformation using innovative applications in the Cloud. Its services combine integrated business technology, a people-first approach, and business acumen to discover and activate potential. It also offers a full spectrum of capabilities that help businesses implement a compelling Cloud journey.

Benefits of Cloud Services

capgemini vs deloitte

Modernized Datacenter

  • Enhanced agility and quality at reduced costs.
  • Public Cloud Application Migration.
  • On-Premise Automation via Private Cloud.

Modernized Applications

  • Enhance performance, scalability, and productivity.
  • SaaS or managed ISV Public Cloud applications.
  • Custom Cloud Applications.

Business Agility

  • Reduced time to market.
  • Identify new business opportunities.
  • Build Cloud-native applications for new services.
  • Cloud Application Integrations.
  • Real-time APIs development and deployment.

Capgemini vs Deloitte Cloud Offerings


Capgemini helps businesses develop a business-case-based Cloud roadmap by providing different services, which include:

Cloud Strategy

Cloud adoption gets limited by people not having a comprehensive business transformation plan and failing to identify risks. Capgemini offers cloud strategy sessions that fuel digital transformation using:

  • Cloud Business Vision: Aligns business objectives with cloud strategies to create targets and goals.
  • Cloud Value: Highlight the costs and benefits of your Cloud journey.
  • Cloud Roadmap: Scour through different options and activities and plot your Cloud journey.
  • Cloud Transformation Plan: Underline business skills and changes required to harness the Cloud’s full potential.

Cloud Applications

Capgemini offers Cloud application services that help businesses transform agility, efficiency, and performance, including:

Capgemini Enterprise iPaaS

A cloud-agnostic platform assisting businesses in enhancing the delivery of APIs and other services. Capgemini Enterprise iPaaS helps clients by providing:

  • Flexible pricing
  • Open-source products
  • Dedicated Data Isolation Instances

Software-as-a-Service (SaaS)

Accelerate your Cloud journey by choosing, deploying, and integrating the right Software-as-a-Service (SaaS). Capgemini provides SaaS solutions and business integrations using pre-built accelerators. It enables users to access software from top vendors, including Microsoft, Google, Salesforce, SAP, Netsuite, Oracle, and Workday.

Cloud-Native Applications (PaaS)

Build cloud-native applications and increase business agility. Capgemini offers a good deal of enhancement services, and you can deploy enhancements continually to improve services.

Migrating Workloads to the Cloud

Capgemini offers robust methods for migrating workloads to the Cloud. Their services include aligning your cloud architecture and migration pattern with your business goals:

Cloud Architecture

Define your business case and establish the architecture and operating model needed to succeed.

Migration Execution

Manage factory model migration.

AWS Cloud Migration for SAP

Capgemini offers its Cloud Choice with AWS end-to-end portfolio that helps businesses leverage SAP on the AWS Cloud for enhanced efficiency and automation.

  • Workloads Assessment: Transforms businesses’ agility and application portfolio using a Cloud-first approach to reduce cost. It provides a systematic, cloud-agnostic assessment of applications and helps clients make informed decisions:
  • Business case: Illustrating the business value of Cloud design.
  • Cloud Suitability: Evaluating applications for migration by checking value and sensitivity
  • Proof of Concept Planning: Underlining a migration roadmap
  • Cloud options: Choosing the suitable Cloud service model and assessing how applications perform in a cloud environment.
  • Capgemini Cloud Platform: Businesses leverage the right technology and processes to harness the total efficiency and agility of the Cloud. Capgemini provides a portfolio of cloud services and business enhancers using its cloud management platform.


Deloitte engineers business transformation by providing services that help organizations manifest their unique cloud advantage:

Cloud Strategy

Cloud transformation approaches are pretty complex, and there’s no one-size-fits-all. Deloitte customizes solutions to meet the industry demands of different businesses by assessing how a practical roadmap can get created to maximize cloud potential.

Application Modernization & Migration

Businesses can reimagine their architecture and IT functions with high efficiency.

  • Cloud Modernization
  • Cloud Migration

Cloud Analytics & AI

Deloitte cloud services allow businesses to harness advanced analytics, make insight-driven decisions, understand modern business operations, and increase value.

  • Machine Learning
  • Data Analytics
  • Artificial Intelligence

Cloud Business Transformation

Deloitte Cloud services allow businesses to create sustainable value by systematically identifying meaningful opportunities and capitalizing.

  • Self-funded Transformation
  • Cloud Strategy
  • Business Change Management

Cloud Infrastructure & Engineering

Businesses can modernize infrastructure by harnessing next-generation technology to enhance:

  • Security Design
  • Data Center Modernization
  • Network Transformation & 5G/Edge Capabilities

Cloud-Native Development

Deloitte cloud speeds up the deployment of cloud applications. It creates cloud-native solutions that are easy to build and deploy.

  • Modern App Development
  • DevOps
  • Cloud Integration

Cloud Operate

Deloitte’s operations and management support provide businesses with a flexible, scalable cloud solution that speeds up business development.

  • Cloud Managed Services
  • FinOps as a Service and Observability
  • Application Managed Services

Cloud Workforce & Operating Model

Businesses can transform their Cloud operating model and workforce. Including:

  • Cloud Processes & Tools
  • AIOps
  • Smart Workforce with the Deloitte Cloud Institute
  • Organizational Readiness

Cyber & Strategic Risk

Become more innovative and resilient against persistent cyber-attacks.

  • Control and Compliance Management
  • Digital Identity
  • Infrastructure and Application Security Management
  • Detection and Response Management

ERP & SaaS

Businesses can deploy comprehensive next-generation ERP & SaaS services, scalable from anywhere.

  • SAP on Cloud
  • Cloud SaaS Solutions
  • Oracle on Cloud

Hybrid Cloud

Businesses can maximize agility by integrating cloud infrastructure and apps to build a hybrid cloud ecosystem:

  • Planning, Strategy, and Deployment
  • Edge Computing
  • Application Modernization and Migration

Capgemini vs Deloitte Takeaway

Capgemini has a neutral social sentiment when analyzing social media channels and online mentions. So does Deloitte. Deloitte aims to tackle the core business issues of today and the future. Capgemini has in-house tools, which help analyze the data and find key insights.

The solutions are advanced and can handle errors smoothly. It allows businesses to start and expand their insurance wings to expand market capitalization.

Deloitte provides the ability to conduct real-time scenario planning and modeling. The Cloud platform can ingest a range of datasets and produce clear outputs. The team also offers knowledgeable data scientists to help you interpret the data.

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