As the landscape of cybersecurity threats continues to evolve, securing the defense supply chain has become a critical priority for national security. One of the most significant steps taken by the U.S. Department of Defense (DoD) in response to the growing concern over supply chain vulnerabilities is the Cybersecurity Maturity Model Certification (CMMC). The CMMC is a unified cybersecurity standard designed to protect sensitive defense information and improve the security of the entire defense industrial base (DIB).

The CMMC, implemented in 2020, aims to address the cyber risks posed by contractors and suppliers within the defense supply chain. Given the complexity of modern supply chains, where multiple contractors often have access to confidential and classified information, ensuring that every entity meets stringent cybersecurity standards is paramount. In this blog, we’ll explore the role of the CMMC in securing the defense supply chain, its components, and its implications for defense contractors.

What is the CMMC?

The Cybersecurity Maturity Model Certification (CMMC) is a set of cybersecurity standards introduced by the Department of Defense (DoD) to improve the security of its supply chain. It was created to address the increasing number of cyberattacks targeting defense contractors, often leading to the exposure of Controlled Unclassified Information (CUI) and other sensitive materials.

The CMMC builds upon existing frameworks, including the National Institute of Standards and Technology’s NIST SP 800-171, and incorporates cybersecurity best practices from various sources. Unlike its predecessor, which primarily relied on self-assessments by contractors, the CMMC introduces an independent certification process that requires defense contractors to achieve a specific level of cybersecurity maturity.

The CMMC is structured around five levels of cybersecurity maturity, each representing a different set of practices and processes aimed at securing information and systems. These levels range from basic security practices (Level 1) to advanced, risk-managed practices (Level 5). Depending on the type of information a contractor handles and their role within the supply chain, they must meet the requirements of a specific CMMC level.

The CMMC’s Role in Securing the Defense Supply Chain

The CMMC plays an integral role in fortifying the defense supply chain against cyber threats in several key ways:

1. Mitigating Cyber Risks Across the Supply Chain

One of the primary reasons the DoD implemented the CMMC is to address the increasing risks posed by contractors, sub-contractors, and third-party suppliers within the defense industrial base. A vulnerability in one link of the supply chain can compromise sensitive defense information, leading to catastrophic consequences. The CMMC ensures that each entity in the supply chain adheres to stringent cybersecurity standards, creating a more robust defense posture.

Cybersecurity is no longer an isolated concern for just the prime contractors but must be addressed across the entire chain. By mandating that all DoD contractors meet specific CMMC requirements, the DoD can create a unified defense against cyber threats, ensuring that every level of the supply chain contributes to securing sensitive information.

2. Reducing the Risk of Data Breaches and Espionage

Defense contractors handle vast amounts of Controlled Unclassified Information (CUI), which includes sensitive but unclassified data like military contracts, operational details, and technical specifications. The loss of this data to malicious actors can compromise national security and give adversaries a competitive advantage.

The CMMC provides a framework to protect this data by ensuring that contractors implement practices like data encryption, continuous monitoring, and access control. By aligning contractors’ cybersecurity measures with the CMMC standards, the risk of data breaches, espionage, and intellectual property theft can be significantly reduced.

3. Enforcing Compliance and Accountability

Previously, the DoD relied on contractors to self-assess their cybersecurity capabilities based on NIST SP 800-171. However, this approach had limitations in ensuring consistency, transparency, and accountability. Contractors may not always report their cybersecurity status accurately, or they may not fully comply with security requirements.

The CMMC solves this problem by implementing a third-party certification process. Each contractor must be evaluated by an accredited third-party assessor (C3PAO) to ensure they meet the necessary security standards. This certification process provides greater accountability and makes it clear which contractors are truly meeting the cybersecurity requirements.

4. Addressing the Threat of Supply Chain Attacks

Supply chain attacks, such as the SolarWinds hack, have demonstrated the vulnerability of even trusted vendors in the defense sector. Malicious actors often target smaller suppliers in the supply chain to gain access to larger systems. These attacks exploit the interconnectedness of supply chains, where even one compromised vendor can provide a gateway to broader vulnerabilities.

The CMMC helps mitigate the risk of these types of attacks by requiring all entities within the defense supply chain to meet baseline security standards. With the CMMC in place, even smaller contractors are held accountable for their cybersecurity measures, reducing the likelihood that an attacker can exploit vulnerabilities in the supply chain.

5. Increasing Trust Between the DoD and Contractors

For the DoD, ensuring the security of sensitive defense information is critical, and the CMMC helps build trust between the department and its contractors. By implementing a rigorous certification system, the DoD ensures that contractors handling sensitive information are equipped with the necessary cybersecurity measures to protect that information.

This certification not only helps safeguard national security but also ensures that contractors are demonstrating their commitment to cybersecurity, which in turn builds confidence among all stakeholders, including the DoD, contractors, and the public.

6. Fostering a Culture of Cybersecurity Within the DIB

The CMMC encourages a broader cultural shift within the defense industrial base. It emphasizes that cybersecurity is not just an IT issue but a critical component of overall business operations. Contractors are incentivized to implement best practices, invest in cybersecurity training, and continuously improve their cybersecurity posture. Over time, this will foster a more secure, resilient, and proactive cybersecurity culture within the DIB.

By aligning security measures with the evolving threat landscape, the CMMC helps contractors stay ahead of emerging threats and ensures that they are continuously adapting their practices to protect sensitive defense information.

Key Components of the CMMC

The CMMC is structured around a set of practices and processes that contractors must implement to achieve certification. These elements are organized into five levels:

• Level 1: Basic Cyber Hygiene – Requires fundamental cybersecurity practices, such as using antivirus software and implementing password policies.
• Level 2: Intermediate Cyber Hygiene – Builds upon Level 1 with additional practices like multi-factor authentication and system monitoring.
• Level 3: Good Cyber Hygiene – Requires compliance with NIST SP 800-171 and includes more advanced cybersecurity controls.
• Level 4: Proactive – Introduces a proactive approach to cybersecurity by incorporating advanced threat detection and response capabilities.
• Level 5: Advanced/Progressive – Focuses on cutting-edge cybersecurity practices and continuous improvement to manage and mitigate advanced persistent threats.

Each DoD contract will specify which CMMC level is required, based on the type of information involved and the role of the contractor within the supply chain.

Conclusion

The Cybersecurity Maturity Model Certification (CMMC) plays a critical role in enhancing the security of the defense supply chain by ensuring that all contractors meet stringent cybersecurity standards. With the growing complexity of cyber threats and the increasing interconnectedness of the defense industrial base, the CMMC provides a much-needed framework to safeguard sensitive information, reduce risks, and build trust between contractors and the DoD.

For contractors, achieving CMMC certification is no longer just a good practice but a necessity for doing business with the federal government. The process may be challenging, but it is a crucial step in securing the future of the defense supply chain and ensuring that the U.S. military remains resilient in the face of evolving cyber threats.

The post The Role of CMMC in Securing the Defense Supply Chain appeared first on Cybertec.

1. Assess the Current IT Environment

Before making any changes, agencies must conduct a thorough assessment of their existing IT infrastructure. This includes:

• Mapping Network Architecture: Understand how systems, applications, and devices are connected and where vulnerabilities may exist.
• Evaluating Access Control Models: Review current access control mechanisms (e.g., VPNs, firewalls) to determine gaps in security.
• Identifying Sensitive Data and Systems: Recognize where critical data resides and the systems that must be protected at the highest level.
• Audit Existing Security Policies: Review current cybersecurity policies and frameworks in place, such as NIST’s Cybersecurity Framework, to understand their alignment with Zero Trust principles.

2. Define Zero Trust Principles and Objectives

With the current state of security in mind, agencies should define their approach to Zero Trust and set clear objectives. Key principles to consider include:

• Verify Explicitly: Ensure that every access request is authenticated, authorized, and continuously verified, regardless of the user’s location.
• Least Privilege Access: Grant users only the minimum necessary access they need to perform their tasks, and enforce strict access controls.
• Assume Breach: Operate under the assumption that a breach is inevitable, and design systems to detect, respond to, and minimize the damage of any potential attacks.

A formal Zero Trust policy should be developed that outlines goals, timelines, and responsibilities for implementation across the agency.

3. Implement Identity and Access Management (IAM) Systems

Identity is central to Zero Trust, so agencies must implement a strong Identity and Access Management (IAM) system. Key actions include:

• Multi-factor Authentication (MFA): Deploy MFA for all users accessing government networks and resources. This provides an additional layer of security beyond simple passwords.
• Role-based Access Control (RBAC): Implement RBAC to ensure users only have access to the systems and data necessary for their job roles.
• Single Sign-On (SSO): Use SSO to streamline user authentication while ensuring that every access request is continuously validated.

Centralized IAM solutions allow agencies to monitor and control who can access what resources, making it easier to manage user permissions and reduce the risk of unauthorized access.

4. Micro-Segmentation of the Network

One of the key tenets of Zero Trust is micro-segmentation, which involves dividing the network into smaller, isolated zones to limit the potential impact of a breach. Agencies should:

• Segment Critical Assets: Ensure that sensitive systems, data, and applications are isolated within protected network segments.
• Enforce Strict Controls Between Segments: Implement firewalls and access controls to prevent lateral movement between network segments.
• Apply Security Policies Based on the Sensitivity of the Asset: Tailor security measures to the specific needs and sensitivity of each network segment.

Micro-segmentation limits the ability of attackers to move across a network and access data they shouldn’t have access to, helping contain breaches.

5. Continuous Monitoring and Threat Detection

In a Zero Trust model, constant monitoring is essential. Agencies should implement continuous monitoring and threat detection systems to assess the health of their IT infrastructure in real-time. This includes:

• Behavioral Analytics: Deploy systems that use machine learning to detect unusual behavior or anomalies, which could signal a cyberattack or breach.
• Security Information and Event Management (SIEM): Implement SIEM tools to collect and analyze security data across the network, enabling faster detection and response to incidents.
• Endpoint Detection and Response (EDR): Ensure that all endpoints (laptops, servers, mobile devices) are continuously monitored for threats and vulnerabilities.

By maintaining a continuous security posture, agencies can detect and respond to threats more quickly, ensuring that any breaches are caught early and mitigated before they escalate.

6. Enforce Data Encryption and Secure Access

Data security is a critical component of Zero Trust. Agencies should enforce data encryption both in transit and at rest to protect sensitive information. Actions include:

• End-to-End Encryption: Ensure that all data transmitted across networks is encrypted, preventing interception or unauthorized access.
• Encrypted Storage: Encrypt sensitive data stored in databases, cloud environments, and on endpoint devices to safeguard it from unauthorized access.
• Secure Access to Cloud Resources: As many federal agencies move to the cloud, ensuring that cloud environments are securely configured and comply with Zero Trust principles is critical.

Encrypting data protects it even if an attacker gains access to a system, adding an additional layer of defense.

7. Automate and Orchestrate Security Responses

To reduce the response time to cyber threats, agencies should automate and orchestrate security responses. This involves:

• Automating Incident Response: Use security automation tools to respond to incidents in real time, such as blocking compromised accounts or isolating affected network segments.
• Orchestrating Cross-Tool Communication: Ensure that security tools work together in an integrated manner, enabling coordinated responses across endpoints, networks, and applications.

Automation and orchestration help minimize human error and reduce the time it takes to mitigate threats, improving overall resilience.

8. Ensure Continuous Improvement and Adaptation

Zero Trust is not a one-time implementation—it is an ongoing process. Agencies must commit to continuous improvement of their security posture by:

• Regular Audits and Assessments: Continuously evaluate the effectiveness of Zero Trust policies, tools, and processes through regular audits and risk assessments.
• Adapt to New Threats: Stay up-to-date with evolving cybersecurity threats and refine Zero Trust strategies to address emerging risks and vulnerabilities.
• Training and Awareness: Provide ongoing training for employees to ensure they understand Zero Trust concepts and best practices, as well as how to recognize and report potential security incidents.

An agile and adaptive security posture ensures that Zero Trust remains relevant and effective in the face of new challenges.

9. Collaborate Across Agencies and Stakeholders

Zero Trust implementation will require collaboration not only within agencies but also across various government entities and private sector partners. Some steps include:

• Engage with Vendors and Third-Party Partners: Ensure that third-party vendors and contractors align with Zero Trust principles, particularly when sharing sensitive data or working on critical systems.
• Government-Wide Collaboration: Participate in cross-agency forums and share best practices for Zero Trust deployment, helping to build a unified approach to cybersecurity across federal IT systems.

Collaboration is key to ensuring that Zero Trust principles are applied consistently across the government.

Conclusion

Transitioning to Zero Trust Architecture is a critical step for federal agencies to enhance their cybersecurity defenses in the face of evolving threats. The shift requires a holistic approach that incorporates robust identity and access management, continuous monitoring, micro-segmentation, and encryption. By following these steps, agencies can successfully transition to a Zero Trust model that not only meets the requirements set forth in Executive Order 14028 but also builds a resilient, future-proof security framework capable of protecting federal IT systems against advanced cyber threats.

The post Steps to Transition to Zero Trust Architecture for Federal IT Systems appeared first on Cybertec.

For federal agencies, understanding the implications and requirements of Executive Order 14028 is crucial. This blog aims to break down the key provisions of the order, highlight what federal agencies need to do to comply, and explain the broader significance for the U.S. government’s cybersecurity strategy.

Key Provisions of Executive Order 14028

Executive Order 14028 is multifaceted, with several key directives aimed at strengthening the cybersecurity infrastructure of federal agencies. These include:

1. Improved Cybersecurity Incident Reporting
   The order mandates that federal agencies enhance their ability to detect and respond to cybersecurity incidents. It requires agencies to implement capabilities for sharing cyber threat information more rapidly. Additionally, it establishes a standardized process for reporting cyber incidents to the Cybersecurity and Infrastructure Security Agency (CISA), which will act as the central hub for coordinating responses.
2. Zero Trust Architecture
   A major component of the order is the push towards adopting Zero Trust Architecture (ZTA) across federal networks. This security model assumes that no device or user is inherently trusted, regardless of location. By continuously verifying access requests, agencies can significantly reduce the risks of cyber intrusions and minimize potential damage from data breaches.
3. Enhancing Supply Chain Security
   The order acknowledges the growing threats posed by vulnerabilities in the software supply chain, exemplified by high-profile incidents such as the SolarWinds hack. Agencies are directed to implement software bill of materials (SBOM) and improve software security across the federal procurement process. This means agencies must prioritize secure coding practices, conduct vulnerability assessments, and ensure that software vendors meet rigorous security standards.
4. Enhanced Endpoint Detection and Response (EDR)
   Federal agencies are required to implement endpoint detection and response tools on all government networks. These tools are vital for detecting malicious activity at the device level and for providing ongoing monitoring to quickly identify and address emerging threats.
5. Collaboration with the Private Sector
   The order encourages stronger collaboration between the public and private sectors, especially regarding the sharing of cyber threat information. Given the vast number of private sector entities that support the government’s infrastructure, this partnership is essential to identify, mitigate, and respond to cyber threats effectively.
6. Cybersecurity Training and Workforce Development
   A skilled workforce is one of the most crucial components of a robust cybersecurity strategy. Executive Order 14028 emphasizes the need for agencies to invest in cybersecurity training, upskilling, and creating a diverse, skilled workforce that can address emerging cyber threats.
7. Implementation of Security Measures on Federal IT Systems
   The order directs federal agencies to review and update their IT systems’ security frameworks, ensuring they are equipped to defend against evolving threats. The implementation of these measures will improve overall network resilience and help agencies better prepare for future cyberattacks.

What Federal Agencies Need to Do

Federal agencies must align their cybersecurity policies with the directives outlined in Executive Order 14028. Some specific actions agencies should take include:

• Review and Update Cybersecurity Frameworks
  Agencies should conduct comprehensive audits of their cybersecurity policies, identifying areas where they fall short of the order’s provisions. Agencies will need to make necessary adjustments to their incident response plans, IT infrastructures, and security protocols to ensure compliance.
• Invest in Zero Trust Architecture
  Implementing a Zero Trust model is a significant shift in the way agencies handle cybersecurity. Federal agencies must begin the process of transitioning to ZTA by enhancing access controls, deploying identity and authentication systems, and continuously monitoring network traffic to detect anomalies.
• Work with Vendors to Strengthen Software Supply Chain Security
  Agencies must partner with software vendors to ensure that software products meet minimum security standards, including the use of SBOMs. Ensuring that third-party software is secure and regularly updated is essential to mitigate vulnerabilities within the federal supply chain.
• Enhance Incident Response and Reporting Protocols
  Agencies need to update their cybersecurity incident response protocols to align with the reporting requirements of CISA. This includes making sure that agency personnel are trained in recognizing cyber threats and following proper reporting procedures to ensure swift responses.
• Focus on Workforce Development
  Building a capable cybersecurity workforce is crucial. Agencies should consider investing in both ongoing training for current employees and developing strategies to recruit skilled cybersecurity professionals. In addition to technical skills, agencies should also emphasize the importance of a culture of security across all levels of the workforce.
• Implement Endpoint Detection Tools
  Federal agencies must deploy EDR systems to protect all endpoints within their network. These systems will help agencies monitor and respond to potential security incidents before they escalate.

The Broader Implications of Executive Order 14028

While Executive Order 14028 is primarily focused on the federal government, its effects will ripple out to the private sector and the broader cybersecurity community. The order provides a roadmap for how government agencies should approach cybersecurity and sets a new standard for security across federal networks.

In particular, the emphasis on supply chain security, Zero Trust, and incident reporting will likely influence private sector cybersecurity practices, especially for organizations that work with government entities or rely on government systems. By setting a high bar for government cybersecurity, Executive Order 14028 raises the stakes for all organizations involved in the nation’s critical infrastructure and services.

Conclusion

Executive Order 14028 is a forward-thinking approach to addressing the growing and ever-evolving cyber threats facing the nation. For federal agencies, compliance with this order is not just about following a mandate—it’s about strengthening the security of the federal government, improving coordination with the private sector, and protecting the country’s digital infrastructure.

By taking proactive steps to implement the measures outlined in the order, federal agencies will be better equipped to defend against cyberattacks, mitigate risks, and create a more secure digital environment for all Americans. Cybersecurity is no longer a passive requirement—it’s a crucial element of national security, and Executive Order 14028 sets the foundation for a more secure and resilient future.

The post Understanding Executive Order 14028: What Agencies Need to Know appeared first on Cybertec.

According to Forbes, Fifty-seven percent cite “integrating all social, mobile, web, commerce, service efforts and investments to deliver an integrated, frictionless, and omnichannel customer experience” as a long term goal; fifty-four percent cite it as a short term one.

Forty-nine percent seek to “modernize IT infrastructure and technologies with increased agility, flexibility, manageability and security” in the long term; forty-five in the short term.

So, here are a few of the top digital transformation technologies that will dominate the way enterprises in 2019.

Internet of Things

Indeed IoT. While we all have read about or in somewhat experienced about IoT, the truth is that the rate of adoption of IoT has not been uniform across industries. Today, IoT spending is dominated by the manufacturing sector.

However, IoT unleashes new opportunities for several industries, through smart connected products and machines, and enables the continuous collection of environmental and user data that can be used to improve business and service performance. 2019-20 could be the breakthrough year for the wide adoption of IoT.

A World Economic Forum report says – Historically, consumption patterns were based on a “first moment of truth” (influencer), then a “second moment of truth” (at retail) and then a “third moment of truth” (consumption). IoT has the potential to move all three steps to a “continuous moment of truth”. This effectively reduces the traditional barriers to entry and could affect business models as it changes the economics of trial.

Artificial Intelligence

Artificial Intelligence will move from boardroom talk to adoption; from use only by large, tech-savvy corporations to enterprises of all sizes across industries; from use cases in limited scenarios like banking/ customer care to several business processes. Why?

Because of three reasons. (1) Digitalization has given rise to very large, diverse data sets and an ever-accelerating accumulation of data (2) Rapid growth of computing capacity and decreasing prices enables the processing of large data sets by an increasing number of users (3) Evolution of new data-use algorithms.

And, as AI is capable of learning and making decisions almost in the same way as human beings and enables machines, devices, programs, systems and services to function in a manner that is sensible – enterprises will lap up the possibility of making sense of data through AI.

Bots and Virtual Assistants

We have seen bots in action. We have experienced bots in making customer service easier and cheaper. But, believe it or not, very few enterprises have used bot technology internally to make business services/operations faster and cheaper. 2019-20 could definitely see a big change in this respect.

Companies that produce office automation software are already investing big on adding to their portfolio trainable digital assistant technologies that are smart, predictive, have the capability to learn, and can quickly adapt to changing the environment.

Cloud

Yes. We are not kidding. Sample this. anyway laptops given to every employee in one of the largest multinational corporations are wired in a way that every file created is auto stored in the Cloud than on the machine.

Increasingly organizations will use the cloud to bring applications, data, and IT services closer to customers in order to improve the performance of digital touchpoints. This has another significant benefit for them. Easy use of analytics by moving the data closer to the analysis engine.

Hybrid clouds allow enterprises to manage the servers that run their “Cloud” applications on premises, as well as enable seamless movement of jobs between enterprise data centres and the public cloud. This means more efficient backup, file sharing, and Software as a Service (SaaS) apps at less capital investment.

There are many more trends that are shaping the future of enterprises. However, when we look at some fundamental shifts that are still taking root in organizations across a diverse spectrum and especially in the emerging economies, it is not the buzzwords that hold sway, but technologies that can bring in a tangible impact on the bottom line as well as their capability to compete effectively.

Are you looking for a digital partner that can transform your business and help you deliver amazing user experience? We can help.

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In fact, the earliest records of using data to track and control businesses date back from 7.000 years ago when accounting was introduced in Mesopotamia in order to record the growth of crops and herds. Accounting principles continued to improve, and in 1663, John Graunt recorded and examined all information about mortality roles in London. He wanted to gain an understanding and build a warning system for the ongoing bubonic plague. In the first recorded record of statistical data analysis, he gathered his findings in the book Natural and Political Observations Made upon the Bills of Mortality, which provides great insights into the causes of death in the seventeenth century. Because of his work, Graunt can be considered the father of statistics. From there on, the accounting principles improved but nothing spectacular happened. Until in the 20^th century the information age started. The earliest remembrance of modern data is from 1887 when Herman Hollerith invented a computing machine that could read holes punched into paper cards in order to organize census data.

Big DataThe 20th Century

The first major data project is created in 1937 and was ordered by the Franklin D. Roosevelt’s administration in the USA. After the Social Security Act became law in 1937, the government had to keep track of contribution from 26 million Americans and more than 3 million employers. IBM got the contract to develop punch card-reading machine for this massive bookkeeping project.

The first data-processing machine appeared in 1943 and was developed by the British to decipher Nazi codes during World War II. This device, named Colossus, searched for patterns in intercepted messages at a rate of 5.000 characters per second. Thereby reducing the task from weeks to merely hours.

In 1952 the National Security Agency (NSA) is created and within 10 years contract more than 12.000 cryptologists. They are confronted with information overload during the Cold War as they start collecting and processing intelligence signals automatically.

In 1965 the United States Government decided to build the first data centre to store over 742 million tax returns and 175 million sets of fingerprints by transferring all those records onto magnetic computer tape that had to be stored in a single location. The project was later dropped out of fear for ‘Big Brother’, but it is generally accepted that it was the beginning of the electronic data storage era.

In 1989 British computer scientist Tim Berners-Lee invented eventually the World Wide Web. He wanted to facilitate the sharing of information via a ‘hypertext’ system. Little could he know at the moment the impact of his invention.

As of the ‘90s, the creation of data is spurred as more and more devices are connected to the internet. In 1995 the first super-computer is built, which was able to do as much work in a second than a calculator operated by a single person can do in 30.000 years.

The 21st Century

In 2005 Roger Mougalas from O’Reilly Media coined the term Big Data for the first time, only a year after they created the term Web 2.0. It refers to a large set of data that is almost impossible to manage and process using traditional business intelligence tools.

2005 is also the year that Hadoop was created by Yahoo! built on top of Google’s MapReduce. Its goal was to index the entire World Wide Web and nowadays the open-source Hadoop is used by a lot of organizations to crunch through huge amounts of data.

As more and more social networks start appearing and the Web 2.0 takes flight, more and more data is created on a daily basis. Innovative startups slowly start to dig into this massive amount of data and also governments start working on Big Data projects. In 2009 the Indian government decides to take an iris scan, fingerprint, and photograph of all of its 1.2 billion inhabitants. All this data is stored in the largest biometric database in the world.

The post Big Data-A Short History Of Big Data & Analytics appeared first on Cybertec.

• The Importance of Data Conversion: 

  Data conversion is a critical process in the migration of information from existing information databases to new ones that often requires changes in data formats. Data conversion refers to the transformation and transfer of data between different systems when the systems undergo replacement or updates as well as the change in the format of data to ensure that it is compatible with the new database. There are different kinds of data conversion processes that can be useful for businesses including document conversion, e-book conversion  and pdf conversion among others.

  Data conversion is very closely associated with system conversion and till date, this aspect has not received the attention it deserves, when planning for such a system change. So far, it has been relegated to the position of a minor task of the major legacy change. Hence, data conversion deserves a special standing of its own- as a separate strategic initiative as part of the whole data management process. Especially in the healthcare sector, the quality of historical data conversion plays a crucial role in determining the quality and availability of patient data accumulated over time. Data conversion is also of great importance for the insurance sector. Companies can make use of different data conversion and document strategies that help ensure that their data is compatible with their systems.

  Correct data conversion should ensure the following:

• • Data is converted into an appropriate format that fits the destination database
  • Data is transferred correctly
  • Data works in the new destination database
  • Data retains its quality
  • Data consistency is maintained at all times across all systems using that particular data

The present day challenges to ensuring a smooth and successful data conversion include the following:

• • Challenges of migration of data from legacy systems and replacements to new systems as well as system consolidations: this process is associated with high failure because of the size, breadth, and complexity of the projects.
  • Complexity of data: the merging of structured and unstructured data creates new difficulties. This renders it more difficult to convert such data into a particular format.
  • Project timelines:  this creates challenges in completing the task.
  • Effect on the quality and accessibility of the data: challenges persist in ensuring that the quality and accessibility remains unchanged following the conversion.

• 10  Key Strategies of Successful Data Conversion:

  The complexity of data conversion requires that certain strategies be put in place. Here are some essential strategies that you must apply in order to ensure the success of your data conversion projects.

1. Proper Planning:

   Successful data conversion requires proper planning. Any data conversion project needs to start with defining the boundaries of the project. You can plan your project by asking a variety of questions to define these boundaries. These include:

• • What kind of data needs to be converted?
  • What is the quality of data and its availability? Does it require full or partial conversion?
  • Which data should be moved to the new database?
  • Which data should not be moved?
  • What kinds of formats are needed for data conversion? For example, your project may require SGML, XML, HTML, and other formats. An efficient SGML conversion outsourcing provider may execute this task and deliver the product quickly. You can then use this data for your SGML-compatible databases.
  • What is the original data format and what is the final format?
  • What would be the extent of digitization?
  • Is the destination database compatible with the software used for data and HTML conversion?
  • What are the data conversion standards to be used, if any, for the successful completion of data conversion projects?
  • What are the guidelines for the process?
  • What would be the tentative duration of project?
  • How frequently would do you need to carry out the data conversion?
  • The cost of data conversion is one of the limiting factors for a data conversion project.

The more detailed your planning, the easier it would be for you to control the project.

2. Ensure Business Engagement:

   Sometimes, those in the business side of the organization do not understand the importance of data conversion. It is important to make them understand the importance of data conversion in data processing and management: about how the quality of data conversion can affect subsequent processes that makes use of this data. Data conversion is thus, a task critical from both business and technical perspectives.

3. Implement Data Standards:

   Defining and implementing data quality standards helps to ensure consistency across the different databases. Consistently measure and track data quality and constantly check the effect on the business value. (hyperlink to article on data quality impact on business value).

4. Data Profiling and Cleansing:

   Ensure that proper data profiling and data cleansing procedures are in place so that the original data is of high quality. This helps to smoothen out the subsequent data conversion procedures.

5. Data Management and Data Governance: 

   Following data conversion, ensure that the duplicate master data is eliminated, reducing the risk of incorrect transactions and unreliable reports. The project should satisfy all principles of data management and data governance.

6. Evaluating data complexity  

   Complexities of data strings and current data classification systems can largely influence the direction in which an organization moves forward with the tools migration and the integration processes. Data evaluation involves analyzing what kind of resources the organization possesses, the type of storage where these data resources are stored, and how complex is the data that is stored.Though data is an integral part of a business process, the problem with it is that it becomes voluminous. As organizations continue using different modes of tools and technologies, the need to filter out valued information grows high. Establishing a comprehensive set of rules and standards will help you determine which data to migrate and which to not.

7.Defining business rules

2. It is also important to define the business rules that will define how you use data. These rules will ensure to maintain compliance and compatibility with business and validation rules as well as with future policies and regulations.

8.Information governance structure

2. An information governance structure figures out who will be responsible for managing the information, data quality, access, and appointing someone who will have a final say on data usage throughout an organization. Since an entire organization is affected by data migration, it is important to be careful when deciding upon an information governance structure.

9.Assessing data quality

2. Data quality assessment eradicates duplicate contents that are irrelevant to current and future business processes. The assessment ensures high-level quality information is being transferred from the source point to the target point so that it is accessible to both current and future users.

10.Arranging migration requirements

2. Once data complexity has been evaluated, business rules defined, information standards established, information governance structure detailed out, and data quality assessed; you are required to gather the migration requirements. Make sure to carefully analyze how, who, where will the data be put to use. In addition, you will also need to estimate the impact that the data will leave in the future.

11.Risk management

2. Risk management should be an integral part of the data migration process. Make sure that all data is accessible for any potential audits. In addition, ensure that all information systems comply with industrial, government, and companywide regulations.

12.Change management

2. Change Management is another important part of data migration. Any change in the organizational setting requires careful consideration of the customers, vendors, partners, and everyone who will be participating in the new system. Change management ensures everyone involved in the system is kept on board.

13.Aligning your IT and business partnership

2. Getting all your teams on the same page will help you to a clear plan, thereby eliminating any sort of disconnect between the IT and business expectations.This is important since the IT needs to be aware of the strategic goals that a project migration needs to meet. Also, business leaders need to be aware and tactical of the operational challenges that are associated with a project.  Getting all of them on the same page will help to align both the goals and the challenges thereby helping to create a better migration strategy.
   

   Finally — finding the right vendor for your organization

   There are a few practices that organizations must follow to implement data migration successfully.

   However, one needs to consider choosing a vendor who will help to align with an organization’s vision and culture and provide a solution to address project requirements and unique infrastructure. In short, choose a vendor that will help you to follow the fundamental practices and help uncover business value, decrease organizational risk, and overall usability of data.

   While most of the systems or software tools face the difficulty of data-to-data communication, Kovair Data Lake offers an SQL server database that is capable of transferring data irrespective of the type of tool they reside in. A new release is planned that will utilize MongoDB as well for additional flexibility. It is presumed that you are already acquainted with Kovair Omnibus enterprise service bus—the centralized platform that can implement an effective communication between diversified ALM tools. These tools, when integrated with Kovair Omnibus, allow the data to be pulled through the Omnibus data store using Omnibus extractors.

   Establishing information standards

An experienced document conversion outsourcing provider would assist you with professional consultation on managing your projects efficiently, before the start. Following these best practices would ensure the best outcome of these projects.

The post Data Conversion & 10 Key Strategies for Success appeared first on Cybertec.

The persona I generated is based off of interviews Aurora Melchor, a UX Designer, conducted with her team as well as additional data points that I added from my circle of colleagues.

GOALS: Keep everyone happy; Deliver value and project success; Predictability

MOTIVATIONS: Wants interesting, fun, and challenging work; Recognition and promotion

MINDSET: Likes problem-solving; Feels the urgency to “get stuff done”; Driven by accomplishment; Often does well “riding the wave” of change

PAIN POINTS: “My day is a fractured experience!”; Inadequate planning and poor estimates; Manual repetitive work across multiple applications; Having to do more with less; Risk, complexity, and uncertainty has increased (VUCA)

To create this success orientated mindset there are a number of tips and strategies that Project Managers can look to adopt.

1 — Spend Time To Understand Your Own Management Style

As a manager, it is important that you take the time to understand your own management style. It is only when you have a deep understanding of your managing skills that you will become a better manager. One way to understand your management style is to assess your strengths and weaknesses as a manager. Sit down and write a list of each.

Under your strengths for instance, you may note down that you are an empathetic leader. You could also be a friendly person that people aren’t afraid to approach. Or it could be that you are motivational, and that you inspire people to get things done. Under weaknesses, you may note that you are impatient, or that you tend to lose your temper rather too easily. Or perhaps you push people too far without any consideration for other aspects of their lives.

If you feel that you need help assessing your management style, you could seek the opinion of those under you. Their candid opinions can go a long way in helping you understand what your style is, and where you need to improve as a manager.

2 — Create A Mindset That Is Open To Change And New Ideas

As a manager, being narrow-minded could be your worst mistake. Understand that things don’t always have to go your and often the competition you have to worry about is not operating in the same way businesses did 10 or 20 years ago. Encourage your team to come up with new ideas of doing things. Let them find creative solutions to existing challenges. And when they do make their suggestions, be open to implementing them.

The danger of being narrow-minded is that you may miss out on great ideas that could go a long way in helping you attain your goals. Even though some ideas may appear unconventional or outright absurd at first, listen to them anyway. They may be the solution you have been looking for all along.

3 — Don’t Waste Your Energy On The Small Stuff

As a manager, you hold the fate of your entire project in your hands. You simply can’t afford to be tied down with small, insignificant issues that have no major impact on your overall success or failure. The only way to learn what your right priorities should be is to look at what drives your business. If a task on your to- do list has no bearing on your business, simply cross it off your list and expend that energy on something more important.

4 — Trust And Empower Your Team

One costly mistake that many managers make is deceiving themselves into believing that they can do or oversee everything by themselves. This is the surest way to exhaust yourself and make yourself susceptible to a burn-out. You need to learn the art of delegation. Assign different responsibilities to your team, and then trust them to get the job done.

By all means try to avoid micro-managing your team. It makes them feel belittled not to mention that it could hinder their ability to give the job their best. Hawking over your team also diminishes their confidence greatly. Instead of micro-managing them, empower them and show confidence in their abilities. More often than not, they will feel obliged to make you proud.

5 — There Is Always A Way Forward

As you go about trying to complete a project, it is inevitable that you will encounter some challenges along the way. Sometimes, the challenges are problems you can easily solve; other times, they might appear to be insurmountable.

It is when you experience the most trying challenges that you will be tempted to give up. But as a leader, giving up must not be an option. Even when things seem like they can’t get any worse, you must remain hopeful. No matter how difficult things seem, it is important to remember that they will not remain that way forever. There is always a solution no matter how hopeless a situation might appear to be.

6 — Create Clear Priorities

On your way to achieving your goals there will be many distractions. It is exceedingly important that you set priorities both for yourself and your team. It is the only way you will remember to deal with the important stuff first and ignore the distractions.

Having clear priorities also makes it easier to turn down ad-hoc requests that can interrupt your work flow. If you have committed to completing a task within a given timeframe and another request for your time is made. Be polite but decline to be involved or offer another solution that allows you to tackle that issue at a later time or date.

7 — Maintain Open Channels of Communication

As the manager it is exceedingly important that you maintain clear communication channels with your team. Let them feel free to approach you whenever need be, and do not withhold any important information from them. Transparency and openness can go a long way in holding your team together and making it easier to accomplish your goals.

8 — Don’t be Afraid to Ask for Help

Even if you are the leader of your team, it is okay not to have all the answers all the time. If you need help, do not hesitate to ask for it. Sometimes, your subordinates may have the answers you so desperately seek, and there is absolutely no shame in asking for a helping hand when you need it.

As a manager you may also fear seeking help from higher up the chain of command for fear of looking like you don’t have everything covered personally. This is a strategic mistake. Often that small issue continues to grow until management can’t help but step in. Now not only is the project behind schedule but you have to shoulder an even greater portion of the blame as you didn’t seek help when you needed it.

9 — Take Ownership And Responsibility For Your Team and Actions

Accountability is one of the hallmark characteristics of great leaders. A leader should own up to all the actions of their team, be they good or bad. If something wrong has happened because of you or a member of your team, it is wise to refrain from pointing fingers and laying blame. A much more effective strategy, and one that will endear you to your team, is to work on finding a solution to the issue you find yourself in.

10 — Remain Optimistic

As a leader, your entire team depends on you for guidance. Project managers who are optimistic tend to achieve their goals. Remember that perpetual optimism is a force multiplier. If you weigh down your team with constant pessimistic comments, they might even give up on ever accomplishing their goals. Keep their spirits up and they will never doubt their ability to attain any goals.

The post What Goes on in the Mind of a Project Manager? and 10 Mindset Tips for Project Managers appeared first on Cybertec.

Today, with machine learning services becoming an offering of many public clouds, it has become both affordable and accessible. Google Cloud Platform, Amazon Web Services, and Microsoft Azure, all offer ML with such ease of use that it no longer requires a team of data scientists to implement.

The coming together of machine learning and cloud computing has given rise to “the intelligent cloud” because ML has given birth to a number of new cloud services. A few of them are listed below:

• Cognitive Computing

Cognitive Computing enables apps to see, listen, talk, and make decisions with the use of ML technologies.

• Business Intelligence (BI)

Cloud computing has greatly improved business intelligence – with intelligent insights and accurate forecasting – by merging BI platforms with ML-based tools.

• Internet of Things (IoT)

Data-driven platforms on the cloud have made it possible for data to be captured from various sensors in large quantities, making IoT more intelligent.

• Bots-as-a-service

Messaging platforms can now be integrated with bots who can respond to website visitor queries, and converse with them.

• Personal Assistants

Voice-based personal assistants like Alexa, Siri, Google Assistant, and Cortana are all powered by machine learning to offer customized experiences for users.

Machine learning can now be easily leveraged, thanks to the cloud. With its pay-as-you-go model, it becomes even more easy to experiment with various ML capabilities and scale up or down any time.

And thanks to machine learning, the cloud is now intelligent – learning from the vast ocean of data stored in it and creating better predictions and, thereby, smarter solutions.

Want to adopt machine learning and make your business smarter? Ask CloudNow how! CloudNow can help you discover relevant use cases to apply ML and run workloads to make the most of your data on the cloud.

The post Cloud Solutions Bringing Together Machine Learning appeared first on Cybertec.