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OUR BLOG


Month: May 2022

ITIL and PRINCE2 for Effective Change Management in the United States

Posted on May 25, 2022July 26, 2022 by Marbenz Antonio

How to Implement ITIL Change Management in an Organization

As many service managers in the United States are well aware, ITIL® 4’s greatest strength is its holistic and comprehensive character, without being too prescriptive. Practitioners may also see similarities between it and other approaches and frameworks like Agile, DevOps, Lean, and COBIT.

However, there has been less discussion concerning ITIL’s compatibility with PRINCE2®. Moving through the ITIL certification path can lead to further qualifications, one of which is PRINCE2.

When businesses combine service and project management, PRINCE2 is the logical and evolutionary best practice step, and, like ITIL, it recognizes the existence of complementary bodies of knowledge.

Everything in service management is essentially a project in some shape or form: new services, upgrading infrastructure, or adopting ITIL practices; however, what is critical for success – in my experience from the United States – are looking not only at the “what” and “how” of projects but also the “why.”

US project management – more methods needed

Some organizations in the United States have project management down to a science, depending on their maturity.

However, in the small to medium-sized firm (SME) industry, initiatives are less formalized and operated more “by the seat of their trousers.” While I believe that SMEs are in desperate need of good project management approaches, I believe that major enterprises in the United States might benefit as well – especially if they operate on a world basis.

PRINCE2 – taking a lead from ITIL

Reading and working with the PRINCE2 guidelines reminded me of ITIL 4 Foundation in its easy-to-digest approach, which sets it apart from other, often formal textbooks. And, like with ITIL, you may adopt and adjust the recommendations to your company and environment using the “tailoring” concept.

While organizational change management (OCM) – the strategies employed to win hearts and minds – is more explicit in ITIL 4, But believe PRINCE2 project managers are more likely to conceptualize and work in this manner. This is critical because corporations simply introduce risk into initiatives by failing to examine how the change would affect people’s lives.

Project management skills today

During the Covid-19 outbreak, there was no new technology to facilitate remote work. However, businesses have struggled to adapt their systems and procedures to suit employees working from home.

This has made it difficult for project managers to move programs ahead when employees are scattered. However, by employing projects to re-evaluate and “bake in” continuous improvement, firms will be in a condition of ongoing learning and will emerge from Covid-19 much stronger.

PRINCE2 certification

People that have achieved professional development qualifications like ITIL 4 Managing Professional and PRINCE2 show how to achieve effective change, not just intellectually but practically. It is also important to have the ability to manage the continuing investment in change and improvement, human resources, and the integration of OCM into an effective change effort.

Lastly, the combination of best practice knowledge, beliefs, and practices offers the ideal method for making individuals successful change agents.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

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ITIL 4 and Cloud Services: Connecting Multiple Frameworks

Posted on May 25, 2022July 26, 2022 by Marbenz Antonio

DevOps en pratique · iTPro.fr

One of the most interesting technological developments these days is the migration of organizations’ IT services to the cloud.

There are several benefits to doing so, ranging from more flexibility and collaboration to lower total expenditures.

You’ve spent the last year working with multiple enterprises to migrate their data centers and apps to the cloud. You discovered that enterprises and providers may not always be on the same page regarding how cloud frameworks function and operate.

Customers, anxious to save time, money, and resources, select a vendor to host their cloud services and begin migration activities, only to discover that the cloud environment does not operate exactly like their on-premises environment. Customers demand the same procedures, structure, and general maturity that they have created over many years for their on-premises technology systems.

Different languages, different meanings

To start, each side has its own set of processes and a separate language. This implies they may use similar language but with distinct meanings. For example, “change management” can imply many different things to various customers and vendors.

When one side believes the other is responsible for, say, change management, a gap between customer expectation and service actuality develops. For example, an on-premises update might take place in two hours — with procedures so developed that any problems could be resolved quickly. A shift to cloud services might need two to three days to complete.

Meanwhile, cloud suppliers have evolved their processes, structure, and maturity to assure scalability across a much bigger and uncertain scope: their infrastructure may be global, with infinite clients, and all the unpredictability that entails.

As a result, both firms and suppliers may discover that their working methods do not quite match.

Why has this been let to happen? Because of the focus on speed to market, governance and controls have taken a back seat.

How does ITIL help?

How does ITIL 4 handle the unique issue of businesses migrating to cloud computing?

Just because a corporation is using newer technology does not imply it can abandon the controls, standards, and processes/practices that have made the IT function effective in the past.

Additionally, ITIL 4 identifies and collaboratively integrates other techniques, such as Agile, Lean, and DevOps. Rather than each strategy working in isolation, ITIL 4’s unified approach strives for comprehensive experience management.

DevOps, Lean, and Agile are fantastic, but how can you simultaneously implement Agile and waterfall-based change that benefits the whole organization? ITIL comes into play when consistency is required.

To be clear, the goal isn’t ITIL 4: it’s about enhancing collaboration among a variety of organizations.

As a result, when both cloud service providers and their customers have accepted and modified the ITIL framework, it almost assures that everyone is on the same page and speaking the same language before migrating on-premises infrastructures or applications to the cloud. The ITIL framework scales independently of the location of infrastructure or applications (on-premises or in the cloud).

Without a common framework, providers may fail to match customers’ expectations, leading to increased irritation on both sides. Using the same framework, regardless of the amount of detail in its adoption or specific procedures, ensures that cloud migrations occur as quickly as possible.

The need to completely retrain people or, worse, rebuild apps and procedures to run properly in the cloud is also much reduced.

When both enterprises and providers utilize ITIL as the baseline and core that binds everything together – and aspires for the final goal the company desires – moving to the cloud can be a smooth and efficient process.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

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Service Management Skills and Organizational Culture for today’s Businesses

Posted on May 25, 2022July 26, 2022 by Marbenz Antonio

How to Succeed as a Manager of Tech and of People - Creately Blog

What characteristics, skills, and organizational culture contribute to today’s successful service management team?

This is important because the Covid-19 pandemic has caused businesses to shift more quickly: developing efficiency and decreasing expenses that will help them escape extinction next year or even next quarter.

As a result, the skills and cultural behaviors necessary have broadened – not only generalist or specialized – and employees must be prepared to learn and adapt regularly.

ITIL 4 outlines three competency models:

  • T-shaped – professionals with deep knowledge who specialize in one area
  • Pi shaped – broad knowledge combined with competence in two or more areas
  • Comb-shaped – having multiple areas of skill and deep knowledge

To allow proper service management and increased maturity, organizations must have a solid mix of individuals with the skill sets and capabilities across all three competencies.

What is service empathy?

Service empathy is another important factor for the service management professional and team: it is about considering the interests of others by putting yourself in their shoes.

This requires a certain level of flexibility and emotional intelligence to empathize with individuals working on various company tasks based on a thorough understanding of their requirements. Therefore, it comes down to how a service manager may assist a client in having a better result in their day or difficult situation.

Because of the pandemic, believing in company leadership teams are evaluating strategy, direction, and company culture, which indicates people’s perspectives in service management are evolving to greater empathy.

Creating a culture of service management

The digital mindset needed in today’s service management requires a culture that is collaborative, creative, and always learning.

Taking an innovative approach to creating tomorrow’s ideas and skills must begin with a solid foundation of leadership that supports a cultural transformation.

To achieve this, a clear picture of why and what’s in it for the people involved, as well as the organization, is needed. The reasons for change must be presented strategically, not like a hammer to the head, but like a distracting butterfly that people want to pursue — engaging people on their level and showing the worth of change.

However, it is also important to recognize that the path to altering culture is not without flaws. You must empower individuals to participate in the solution by providing practical means to bring them into the conversation and soliciting their thoughts.

Have we got there? Meaningful methods to measure improvement

How can you tell whether your organization’s service management skills and culture have changed and improved?

It’s less about statistics, in my perspective. For example, are people more interested if you measure their ideas and attitudes near the end of a cultural change journey? Do they believe the environment is a haven for failure? How do they rank the customer focus? How much continuous learning occurs?

These are the outcomes that may be expected if leadership empowers and accepts this form of core change – successfully changing the organization’s culture, approach to service management, and employee experience.

Leaders who embrace this – and inspire empathy – will see why these factors of advancement are important.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

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What are the important aspects of a data fabric architecture?

Posted on May 24, 2022July 26, 2022 by Marbenz Antonio

Data Fabric: An established imperative for the digital era | Hexaware

Organizations need a unique method that gives greater insights and business outcomes quicker without sacrificing data access restrictions to simplify data access and empower people to exploit trustworthy information. There are several techniques, but you’ll want one that can be used independently of your data estate. A data fabric is an architectural concept that allows enterprises to simplify data access and governance across a hybrid multi-cloud landscape for better 360-degree customer perspectives, improved MLOps, and trustworthy AI. In other words, the barriers to data access, data integration, and data security are reduced, giving end-users full flexibility.

Organizations do not have to relocate all of their data to a single location or data store using this method, nor do they have to embrace a decentralized approach. A data network architecture, on the other hand, involves a balance between what must be logically or physically dispersed and what must be centralized.

Because of this balance, the number of purpose-fit data storage that may participate in the data fabric ecosystem is not limited. This means you get a global data catalog with embedded governance that functions as an abstraction layer, one source of truth, and a single point of data access.

Six core capabilities are essential for a data fabric architecture:

  1. A knowledge catalog: This abstraction layer enables openness and cooperation by providing a shared business understanding of the data for 360-degree customer perspectives. The knowledge catalog functions as a store of data insights. The catalog includes a business vocabulary, taxonomies, data assets (data products) with important information such as quality ratings, business words connected with each data piece, data owners, activity information, linked assets, and more to help you understand your data.
  2. Automated data enrichment: You’ll require automated data stewardship services to build the knowledge catalog. These services include the ability to auto-discover and classify data, detect sensitive information, analyze data quality, link business terms to technical metadata, and publish data to the knowledge catalog. To manage such a massive volume of data within the company, intelligent services powered by machine learning are required.
  3. Self-service governed data access: With key governance capabilities such as data profiling, data preview, adding tags and annotations to datasets, coordinating in projects, and accessing data anywhere via SQL interfaces or APIs, these services enable users to quickly search, analyze, modify, and use data.
  4. Smart integration: Data integration skills are critical for extracting, consuming, streaming, virtualizing, and transforming data regardless of its location. Smart integration ensures data privacy by utilizing data rules designed to improve performance while minimizing storage and egress expenses. Each data pipeline receives protection.
  5. Data governance, security, and compliance: There is a unified and centralized approach to setting policies and rules with a data fabric. The capacity to automatically link these policies and regulations to various data assets via metadata, such as data classifications, business terms, user groups, roles, and more, is readily available. These policies and guidelines, which include data access restrictions, data privacy, data protection, and data quality, may then be implemented and enforced across all data during data access or data movement on a massive scale.
  6. Unified lifecycle: End-to-end lifecycle utilizing MLOps and AI to compose, construct, test, deploy, orchestrate, observe, and manage the many parts of the data fabric, such as a data pipeline.

These six important features of a data fabric architecture enable data citizens to utilize data more trustingly and confidently. Regardless of the type of data or where it resides — whether in a traditional data center or a hybrid cloud environment, in a traditional database or Hadoop, object store, or elsewhere — the data fabric architecture provides a simple and integrated approach to data access and use, empowering users with self-service and enabling enterprises to use data to maximize their value chain.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

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Intellectual Property Metaverse

Posted on May 24, 2022July 26, 2022 by Marbenz Antonio

Live, Work and Play in a Legal Metaverse: Preparing for a New Online Existence

The word “intellectual property” is a wide one. In general, it is believed to refer to mental creations. Of course, this includes significant media, where the material — such as written or spoken word, movies, characters, music, images, streaming media, and more — is the exclusive product of the owner, individual, or individuals who developed the content. Owners have the right to do whatever they want with their content (within limits), even monetize it. Anyone or anything that monetizes content without the owner’s express written authorization is considered to be infringing on intellectual property law. As a result, infractions may result in significant economic consequences.

Of course, the meaning and use of intellectual property have changed significantly in today’s internet and its expansion, developments in blockchain technology, and all new types of media. The current intellectual property law problem is also quickly expanding in the Metaverse and how it is popularly understood.

Simply stated, the Metaverse is an expanding collection of new technology-driven digital experiences that occur through features provided by new cloud computing models, the internet, and network connection. It’s thought to be some kind of virtual reality with several digital components. Individuals will be able to have meetings, study, play games, socialize, and more.

Of course, while the Metaverse is still in its early days, there is little doubt that it will enable individuals to establish their social places. It will almost definitely allow anyone to create or use content that is protected by intellectual property law. As you might think, the Metaverse presents a wide range of potential issues to content producers and owners when it comes to tracking their Intellectual Property. These issues have far consequences for media organizations and the future of content creation in general.

How You Can Protect Intellectual Property in a Digital Age

While the Metaverse may be the next frontier of experience and technology, there is good news for those with content-based business models: this has been done before. Intellectual property can and is protected, even in the digital world, where digital asset theft occurs with increasing frequency.

The following are some basic intellectual property protection strategies:

  1. Copywriting for sensitive or crucial materials
  2. Using suitable contract terms to ensure that there is no issue over content ownership.
  3. AI technology is being used to detect breaches and theft of digital intellectual property.
  4. Increasing staff resources to discover and enforce IP law.

There is even more positive news coming as a result of the adoption of blockchain. The blockchain is sometimes misunderstood as being just concerned with cryptocurrency. The blockchain may be used in combination with smart contracts. Smart contracts enable the exchange and tracking of digital property (such as NFTs). They ensure that there is never any doubt about who owns what and that commerce is promoted when digital assets are exchanged under specified and suitable conditions.

Blockchain and smart contracts are expected to grow into incredibly useful and necessary technologies for intellectual property protection. The essential qualities of blockchain are completely consistent with what is necessary for IP protection. It simply cannot be changed as a distributed system without the approval of both parties. It is nearly hard to hack the blockchain. By design, the blockchain may be used to ensure that there are no doubts about intellectual property ownership or rights.

Intellectual Property and The Metaverse

The United States approved the Digital Millennium Copyright Act in 1998, which was a major update to copyright law that has proven to be a fundamental instrument for securing intellectual property in a digital context. It allows internet businesses to send DMCA “take-down” notices. These notifications serve as an enforcement tool when one individual is suspected of breaching another’s intellectual property rights. As such, they are an almost significant tool for protecting the assets of another person or business.

Many doubts remain regarding the Metaverse, but one thing is clear: because it is a digital world, anything used, created, or copied in the Metaverse should be protected by the DMCA. Enforcement will certainly be difficult, and a flood of new problems will undoubtedly surface. Individuals who produce intellectual property for or in the Metaverse, on the other hand, should have their assets protected, at least in principle, but how can you protect it if you can’t find or experience it?

The Role of Artificial Intelligence 

Artificial intelligence has long been used by media companies and other businesses such as Google, Netflix, Microsoft, Amazon, and IBM. AI can help in the administration of intellectual property law by identifying possible breaches. Today, it is apparent that corporations have whole business models dedicated to such technologies and skills.

However, a key question remains: How can AI be used to enforce intellectual property protection in the Metaverse? How can it be used in connection with blockchain?

AI has been employed by companies such as IBM for anything from customer service to enhanced cloud and network management and cybersecurity. However, AI can be trained to detect intellectual property breaches. An AI algorithm, for example, may be programmed to look for unauthorized usage of video, images, or other digital assets. When assets are discovered, legal notifications can be issued to the proper people, demanding that the assets be removed. The same AI may then be used to assess what type of monetization the property violation has participated in, allowing the content creator to be notified and empowered to take action or get compensation.

All of this begs the question: Is your content protected in the Metaverse? How do you keep track of your content? How will you secure your innovations and business concepts, and what legal protections will be in place? As the Metaverse is being developed, many of these questions remain unresolved. However, there is good news: the intellectual property has persisted even as business models have transformed in a digital economy. It is fair to assume that the same protections that have allowed intellectual property law to thrive – including the employment of AI – will continue to exist in the Metaverse.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

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How a data fabric overcomes data sprawl to minimize the length to insights

Posted on May 24, 2022July 26, 2022 by Marbenz Antonio

Reducing Data Sprawl - Jim Sinur

In an increasingly scattered and complicated world, data agility, or the ability to store and access data from wherever it makes the most sense, has become a concern for companies. The time it takes to identify essential data assets, gain access to them, and then use them to drive decision-making can have a massive impact on an organization’s bottom line. Data and IT leaders must move beyond traditional data best practices and toward current data management agility solutions powered by AI to decrease delays, human mistakes, and total expenses.

A data fabric can help an organization simplify data access and enable self-service data consumption while being agnostic to data environments, processes, utility, and geography. A data fabric continually finds and integrates data from various data sources to uncover important associations between the available data points by employing metadata-enriched AI and a semantic knowledge graph for automatic data enrichment.

As a result, a data fabric self-manages and automates data discovery, governance, and consumption, allowing organizations to reduce time to value. You may improve this by adding master data management (MDM) and MLOps capabilities to the data fabric, resulting in a genuine end-to-end data solution accessible to all departments inside your organization.

Data fabric in action: Retail supply chain example

To properly understand the usefulness of the data fabric, consider a retail supply chain use situation in which a data scientist wants to forecast product backorders to maintain optimal inventory levels and reduce customer churn.

Problem: Developing a strong backorder forecast method that captures these factors into the account used takes weeks or months since sales data, inventory or lead-time data, and supplier data were all stored in separate data warehouses. Getting access to each data warehouse and then creating connections between the data would be a time-consuming process. Also, because each SKU is not represented equally across data repositories, the data scientist must be able to construct a golden record for each item to avoid data duplication and misrepresentation.

Solution: By securely integrating all data sets inside the organization, whether on-premises or in the cloud, a data fabric delivers considerable savings into the backorder forecast model generation process. Its self-service data catalog auto-classifies data connect metadata to business terms and serves as the data scientist’s single regulated data resource required to build the model. The data scientist will not only be able to use the catalog to rapidly identify required data assets, but the semantic knowledge graph within the data fabric will enable relationship discovery between assets faster and more efficiently.

The data fabric allows for the creation and enforcement of data rules and regulations in a single and centralized manner, ensuring that the data scientist only has access to assets that are relevant to their work. This eliminates the requirement for data scientists to seek permission from a data owner. Also, a data fabric’s data privacy capabilities ensure that proper privacy and masking rules are implemented to data utilized by the data scientist. You may utilize the MDM capabilities of the data fabric to build golden records that assure product data consistency across several data sources and offer a more seamless experience when merging data assets for analysis. Data scientists may spend less time wrangling data and more time enhancing their machine learning model by exporting an improved integrated dataset to a notebook or AutoML tool. This prediction model could then be easily placed back into the catalog (together with the model’s training and test data, which could be tracked throughout the ML lifetime) and monitored.

How does a data fabric impact the bottom line?

The data scientist now gets a more accurate picture of inventory level patterns over time and future predictions thanks to the newly developed backorder forecast model built on a data fabric architecture. Supply chain analysts may utilize this data to prevent out-of-stocks, which enhances total revenue and promotes customer loyalty. Lastly, by combining disparate data on a single platform in a controlled way, the data fabric design may help greatly cut time to insights in any business, not just retail or supply chain.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

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Four use cases that define the new phase of data management

Posted on May 24, 2022July 26, 2022 by Marbenz Antonio

Four Common Data Management Use Cases You Need to Know

A combination of events in the data management and AI environment is pressing down on businesses of all sizes, industries, and locations. Some of these have been coming for years, if not decades, such as the ongoing spread of data across multi-cloud systems. Others have lately come into greater focus: a global drive to adopt new data privacy rules, a post-pandemic expectation by consumers to be known personally across all touchpoints, and increasing scrutiny of any racial, gender-based, or socioeconomic bias in AI models.

While specific point solutions have addressed some of these problems in the past, it is becoming clear that a more comprehensive solution is required – one that can meet a business’s most critical data and AI needs while also offering the easiest way to solve further challenges. The data fabric is that solution.

A data fabric is an architectural solution to allowing self-service data consumption in an organization by simplifying data access. This architecture is independent of data environments, processes, utility, or geography, and it integrates end-to-end data-management capabilities. A data fabric automates data discovery, governance, and consumption, allowing businesses to maximize their value chain by leveraging data. Enterprises may increase the value of their data by providing the correct data at the right moment, regardless of where it lives, using a data fabric. We’ve listed four of the most important data fabric use cases below, along with a quick description and links to a more in-depth eBook and trial. These use cases serve as the foundation for a rich and intuitive data buying experience. This data marketplace capability will help businesses to supply high-quality managed data products at scale throughout the enterprise in an efficient way.

Multicloud data integration

The increasing growth of data continues unabated, and it is now accompanied not just by the issue of segregated data, but also by a lot of alternative sources spread across multiple clouds. Except for data silos, the reason seems clear and well-justified — more data provides for more accurate insights while using various clouds helps avoid vendor lock-in and allows data to be kept where it best fits. The problem, of course, is the additional complexity that impedes the real use of that data for analysis and AI.

Multicloud data integration, as part of a data fabric, attempts to ensure that the right data is supplied to the right person at the right time. The availability of integration solutions such as ETL and ELT, data replication, change data capture, and data virtualization is critical for implementing the broadest range of data integration feasible. Similarly, data categorization and governance aid in determining what the “right data” is in any particular circumstance and who the “right people” should have access to it. In terms of data delivery at the “right time,” automated data engineering tasks, workload balancing, and elastic scaling should offer all enterprises the necessary speed.

Data governance and privacy

Data privacy rules such as the GDPR in the EU, the CCPA in California, and the PIPEDA in Canada have all been passed at the same time that corporations are refocusing their efforts on data quality rather than data volume. The price of ignoring these imperatives is expensive. Poor data quality costs firms an average of $12.9 million per year, and since January 28, 2021, $1.2 billion in fines have been imposed for GDPR noncompliance.

The data fabric’s governance and privacy component focus on organization and automation. As described in the past segment, data virtualization, and data cataloging help in getting the appropriate data to the right people by making it simpler to identify and access the data that best meets their needs. Automated metadata production is intended to convert a manual process into a more controlled one. As a result, it helps to avoid human mistakes and tags data, allowing policy enforcement to occur at the point of access rather than at individual sources. Automation of data access and lineage control, as well as reporting and auditing, contribute to a business culture that understands, adheres to, and is aware of how each piece of data has been utilized. As a result, more meaningful data is generated with less effort and greater compliance. We are pleased to inform you that MANTA Automated Data Lineage for IBM Cloud Pak for Data will be available in June. This feature will give data consumers visibility into the origin, transformations, and destination of data as it is utilized to generate products.

Customer 360

Because of the worldwide pandemic, customers increased their adoption of digital contacts with enterprises, emphasizing the benefits of a business that was attentive to their specific needs online, in-person, and in hybrid settings (such as curbside). As we return to our everyday routine, the customer’s expectation of convenience and customized treatment persists. High-performing organizations have recognized this and have prioritized enhancing the customer experience over the next two to three years.

The data fabric solves this need by providing a set of capabilities that provide a more full, 360° picture of each consumer. Self-service data preparation tools are a helpful first step in preparing data for matching across data sets. The properties of the customer may then be auto mapped for a trainable intelligent matching system. Entity resolution, once matched, helps guarantee that identity data are of high quality and shows links between entities. Data is then cataloged to apply more information via metadata, virtualized for access regardless of location, and displayed to make identifying data quality and distribution easier and to enable faster data transformations for analysis.

MLOps and trustworthy AI

As the public becomes more aware of how AI is used in enterprises, models are being analyzed more carefully. Any suggestion of bias, especially when it comes to race, gender, or socioeconomic class, has the potential to erode years of goodwill. Beyond popular opinion and moral imperatives, however, being able to trust AI implementations and readily explain why models arrived at making inferences leads to better business decisions.

The data fabric allows MLOps and Trustworthy AI by building confidence in data, models, and processes. Many of the above-mentioned capabilities assist to build trust in data by delivering high-quality data that is suitable for self-service consumption by those who should have access. Model trust is founded on MLOps-automated data science tools that provide openness and accountability at every level of the model lifetime. Finally, trust in processes delivered by AI governance results in consistent repeatable processes that help not just with model transparency and traceability, but also with time-to-production and scalability.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

Posted in IBMTagged IBM Cloud Services, IBM Training1 Comment on Four use cases that define the new phase of data management

AI Ethics Driving better business and a more equitable society

Posted on May 24, 2022July 26, 2022 by Marbenz Antonio

Experts Doubt Ethical AI Design Will Be Broadly Adopted as the Norm Within the Next Decade | Pew Research Center

As AI technology advances past its limitations in new real-world applications, regulators, investors, and the general public are questioning what type of relationship we want with AI and how to ensure its safe usage. As a result, companies and institutions are incorporating AI ethics into existing business practices. But a new report from IBM suggests there’s still a lot of work to do.

Surprisingly, just 40% of surveyed customers believe businesses would be responsible and ethical in their use of new technology such as AI. Their concern may be justified, given fewer than 20% of CEOs strongly think that business policies and actions on AI ethics are consistent with their organizations’ declared principles and values.

According to research undertaken by the IBM Institute for Business Value, the task of adopting an AI ethical strategy has moved significantly from technical experts to CEOs.

AI is increasingly recognized as a cross-industry, multi-stakeholder project. It is more than just an IT issue. HR, procurement, and legal are all on board as well. AI has developed to be business-led, requiring the most senior levels to manage its appropriate management.

A growing AI ethical framework promotes social justice, equity, and trust

As AI reaches more organizations, ensuring the trust and transparency of these systems will become essential to their success. Through predictive justice, the study of large amounts of data to create predictions on case outcomes, AI technology in the courts can have even more far-reaching consequences on individuals and institutions.

One of the best examples of this is the system of justice in New Jersey, where algorithms analyze millions of case files to minimize bail decision prejudice. The system not only saved USD 10 million, but it also resulted in a 40% decrease in the jail population with no discernible rise in the crime rate. The system works because people trust the data and the suggestions it produces.

AI ethics are important for maintaining democracy. And, according to IBM’s research, it’s also beneficial for business. According to an IBM study, businesses that place a higher priority on AI ethics enjoy higher levels of trust from customers and workers.

How IBM operationalizes trustworthy AI

IBM has always maintained the position that AI should be advanced responsibly in a way that ensures ethical principles are at the center of the technology. This effort began in 2015, when world-renowned AI ethics researcher Francesca Rossi joined IBM, bringing 40 colleagues with her to help IBM embrace AI ethics as a core business tenet. To operationalize AI, IBM established trust and transparency principles and established an AI Ethics Board to review all AI efforts across the company. It now assures that IBM-owned technology follows five principles: openness, explainability, fairness, robustness, and privacy. A 2021 World Economic Forum case study details the company’s pioneering leadership.

Put AI ethics into action

AI restrictions are coming. And less than a quarter of responding organizations have put AI ethics into action. The good news is that 79% of business leaders are now ready to include AI ethics into their AI processes. According to the research, this is up from 20% in 2018, with moreover half now publicly endorsing common AI ethics standards.

Getting to the finish line needs a very well plan, which begins by bringing together a broad collection of stakeholders. Then, create an organizational and AI lifecycle governance framework. Finally, provide interoperability so that all ecosystem partners may participate. The sooner corporations get started, the more global individuals will be able to reap the benefits of AI.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

Posted in IBMTagged IBM Cloud Services, IBM TrainingLeave a Comment on AI Ethics Driving better business and a more equitable society

How Serious Is the Transportation Cyber Attack Risk?

Posted on May 24, 2022July 26, 2022 by Marbenz Antonio

Cybersecurity in rail transport: digital protection against real-life threats | Knorr-Bremse Group

If an attacker breaches a transportation agency’s systems, the impacts may extend well beyond server failure or exposed emails. Assume an attack on a transportation authority in charge of train and subway routes. The outcomes might be terrible.

The transportation industry saw a 186% increase in weekly ransomware attacks between June 2020 and June 2021. In one incident, attackers gained access to the systems of the New York Metropolitan Transportation Authority (MTA). Luckily, no one was harmed, but incidents like this are concerning. Transportation organizations require high levels of security to keep their systems and passengers safe.

Important Public Infrastructure

Ransomware was the top attack type globally in 2021, according to the latest X-Force Threat Intelligence Index, for the third year in a row.

According to the research, “malicious insiders emerged as the main threat type against transportation businesses in 2021, accounting for 29% of attacks on this industry.” In 2021, ransomware, [remote access Trojans], data theft, credential harvesting, and server access assaults all had a part in transportation.” We’ll return to the issue of ‘malicious insiders’ later.

Transportation is uniquely vulnerable since it is part of important public infrastructure. Most people and businesses depend on transportation to go to work on time, send goods, or get medical supplies. If an assault interrupts transportation, whole supply networks may collapse. Physical harm might result from an interruption in traffic lights or rail transit.

New Rules for Digital Defense

In response to the growing threat, the Transportation Security Administration (TSA) of the Department of Homeland Security released new cybersecurity rules for surface transportation owners and operators.

The rules should apply to higher-risk freight railroads, passenger rail, and rail transit. They need owners and operators to do the following:

  • Appoint a cybersecurity coordinator.
  • Within 24 hours, report any events to the Cybersecurity and Infrastructure Security Agency.
  • Create and put into action a cybersecurity incident response strategy to minimize the risk of operational disruption.
  • Completing a cybersecurity vulnerability assessment will allow them to detect potential gaps or weaknesses in their systems.

Motives Behind Cyber Attacks

Attacks against transportation agencies might be motivated by a variety of factors. Attackers may steal information or use ransomware to make money. However, some attackers may seek support from foreign states wishing to create chaos or damage to promote foreign policy goals. While any incident might create system interruption, foreign attacks can increase the chances of equipment faults and accidents.

Rogue Foreign Actors

The attackers in the New York MTA incident made no money demands. Instead, it appears that the hack was part of a recent wave of broad breaches by experienced attackers. According to FireEye, a private cybersecurity firm that helped in the identification of the hack, the hackers were most likely supported by the Chinese government.

Another attack in late 2018 resulted in the conviction of two Iranian men by a federal grand jury. They were suspected of holding the computer system of the Colorado Department of Transportation (CDOT) hostage as part of the SamSam malware scheme. The Iranian-based attackers allegedly requested a Bitcoin payment to unlock stolen CDOT data. The issue forced the shutdown of 1,700 staff computer systems. It took six weeks and almost $2 million to restore the department’s systems.

Therefore, the CDOT did not pay the ransom. The government had digital backups that allowed them to recover encrypted data. Additionally, segmented network operations helped in the protection against viruses spreading to other departments or organizations. As a result, servers managing traffic signals and other road systems in Colorado were unaffected.

What Should Transport Leaders Do?

Given the extensive and ongoing threat to the transportation industry, the TSA has created a toolset. When we look at the rail, public transportation, and surface transportation directions, we see that cybersecurity coordination, reporting, and response strategies are important. Vulnerability assessment is also a top concern, and the TSA advises organizations to use the NIST Cybersecurity Framework as a guide.

As more devices and equipment are deployed in the industry, vulnerability assessments should incorporate Internet of Things (IoT) security. IoT devices are required to coordinate the various moving elements and logistics of any transportation system. However, device connections are possible entry sites for attackers, and you should consider this risk as well.

Transportation Attack Risk Mitigation

Transportation organizations, like any other company, are vulnerable to hacking, but the stakes may be higher. One of the reasons, according to Homeland Security Secretary Alejandro Mayorkas, “ransomware now poses a national security danger.” While TSA rules address incident response, where can one receive risk reduction advice?

The X-Force Threat Intelligence Index not only analyses the current risk environment but also offers suggestions for minimizing the risk of breach. The X-Force study makes the following recommendations to reduce cyber risk:

  • Zero trust: This method assumes that a breach has already happened and seeks to make it more difficult for an intruder to move across a network. Zero trust knows where important data is stored and who has access to it. Strategy is focused methods (multifactor authentication, least privilege, identity access management) are deployed across a network to ensure that only the appropriate individuals have access to the correct data in the right way. This is important in transportation since malicious insiders are responsible for approximately one-third of agency attacks.
  • Security Automation: Security automation is crucial in the face of international threats, different attack types, and many levels of security. Machines can execute things far more quickly than any human analyst or team. Automation also helps in the identification of processes for optimizing workflows.
  • Extended detection and response (XDR): Detection and response systems that combine multiple solutions provide a significant advantage. XDR helps in detecting hackers from a network before they complete their attacks, such as ransomware distribution or data theft.

Keeping Transportation Safe

Government efforts are helping in creating awareness and reducing the chance of risk. Individual transportation companies have also taken on the responsibility of protecting their systems and ensuring the safety of their passengers. The threat of an assault on transportation organizations will almost definitely remain, and passenger safety is important.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

Posted in CybersecurityTagged cybersecurityLeave a Comment on How Serious Is the Transportation Cyber Attack Risk?

How to Handle Non-Malicious Data Breach

Posted on May 24, 2022July 26, 2022 by Marbenz Antonio

Data Breach Spreads To Six Web Hosts

It’s easy to believe that most, if not all, data breaches are malicious. Attackers must strike on intentions. However, over two-thirds of data breaches are the result of human error rather than malicious intent. According to Ponemon’s Cost of Insider Threats Report, careless workers cause around 62% of security incidents, costing an average of $307,111 per event.

You could also believe that unexpected breaches would be less dangerous. Insider data breaches may cost up to 20% of annual sales, according to a study done by Aberdeen and commissioned by Code42. Regardless of the cause of the attack, the impact may be comparable. However, the best approach to handle a non-malicious breach differs from the best way to handle a malicious breach.

What Is a Non-Malicious Data Breach?

A non-malicious data breach happens when an employee makes a mistake and creates a breach. Non-malicious attacks, as compared to malicious attacks, in which an insider utilizes their access to create damage, are usually the result of an accident or negligence.

For example, if an employee clicks on a phishing email, the network may get attacked with ransomware. Breaches can also occur when an employee accidentally exposes data that is eventually taken. Perhaps an employee accidentally sends an email to the wrong person, as shown by the 2022 Psychology of Human Error Study, which indicated that 58 percent of employees have done it at work.

How Should Businesses Respond?

An insider breach may not be found for days or months after the attack. And how they react might set the tone for future employees to come forward. Employees may be unaware that they committed a mistake or may be afraid to inform management. Every day that a corporation is unaware of the breach causes additional damage.

Companies must develop a culture in which workers feel comfortable acknowledging that they may have participated in a breach. After all, it can help minimize the damage. Employees made mistakes that resulted in breaches due to distraction, stress, and tiredness, according to the 2022 Psychology of Human Error Study. When businesses respond negatively to a non-malicious breach, it can add to the stress. This just increases the likelihood of future problems.

According to the report, 43% of respondents have committed work mistakes that have compromised cybersecurity. However, age contributed to employees acknowledging that their mistakes may have compromised cybersecurity. 50% of employees aged 18 to 30 stated they would accept mistakes, compared to 10% of those over the age of 51. Taking this tendency into account, you might work with older employees to ensure that they feel comfortable approaching management about possible breaches.

When a breach happens, executives should appreciate the employee for warning them of the possible issue. Assure them that everyone makes mistakes. By keeping the employee’s identity hidden, other employees will be more likely to come forward in the future. After all, they won’t be concerned about public humiliation or blame from employees. Following that, the organization should collaborate with the employee to acquire all of the specifics of the breach. This allows them to limit the breach and restore any damage as effectively as possible.

Should Businesses Announce an Accidental Data Breach?

One of the most important aspects of managing a breach is communicating with the media and affected customers. When your organization gets breached, one of the most serious consequences is that customers and potential customers lose faith in your brand. According to the Institute for Public Relations, businesses should apologize as soon as the breach becomes public. Additionally, they advocate for companies to be transparent. If clients learn more details from another source, they will be far more able to recover trust.

Internal Changes to Make After a Non-Malicious Breach

So you’ve prevented the breach and started the recovery process. What will be the next step? First, analyze why the breach happened. Next, consider how to reduce the likelihood of non-malicious breaches in the future. With non-malicious breaches, many companies skip this step. It is much more important in these types of breaches because the issue was caused by a human error rather than an attacker.

Here are two usual improvements made by businesses after non-malicious breaches:

  • Training – Analyze your current training to see whether you need to add extra information in a given area. Assume that the breach was caused by spamming. You may need to review your examples and warning signals before clicking on links. You should also consider the frequency with which you train. Instead of once-a-year training, many organizations decide to increase the frequency of cybersecurity training and search for methods to include it in employee interactions.
  • Tools – Analyze your current cybersecurity tools to see whether you need to add any more to help prevent the sort of error that caused the breach. By using tools and training, you can usually minimize errors that lead to breaches. Phishing technologies, for example, that analyze links in emails and alert employees to possible vulnerabilities, can help reduce non-malicious breaches.

Employees frequently conceive of a breach in a single category. Non-malicious breaches, on the other hand, are kind of different. Leaders may create a culture in which people feel responsibility for cybersecurity and are comfortable acknowledging mistakes by taking a careful approach to the first reaction and long-term changes.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

Posted in CybersecurityTagged cybersecurityLeave a Comment on How to Handle Non-Malicious Data Breach

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