Logically Speaking May 2023
May 31, 2023
 Growth Opportunities

Getting Behind the Wheel of Your Digital Transformation

​​Jeff Felice, President, CertNexus

Jeff Felice

We shared an article in March explaining how and why it’s important to get business leaders trained and accredited in the areas of AI, machine learning, data science, and beyond. You can view that article here. As a continuation to that article, we compiled this article explaining the “Now what?” after getting business leaders trained up. It’s then time to trickle down that knowledge to the manager-level roles to ensure that your company is fully implementing the digital transformation journey.

Manager-level roles like project managers, product owners, leaders of data teams, and so forth are the drivers on your digital transformation journey.

These team members act as translators between business leaders and the engineers who work hands on with the technology. For the engineers, drivers can communicate the goals of the business from a strategic perspective. For business leaders, drivers can explain how technology can be used to achieve those goals from a technical perspective. A Driver’s job is to align everyone to the same goals and expectations—the destination and the route you will take to get there.

AI, Machine Learning, Deep Learning, and Data
Drivers need a deeper technical understanding than the passengers (business leaders). They need to know the pros and cons of different approaches to machine learning and deep learning. They should understand the data lifecycle and how the tool will evolve over time.

Most importantly, drivers should be able to articulate why and how a particular digital solution will facilitate the business goals. Drivers will need to communicate why their team is going about pursuing the project in a particular way. The appropriateness of a particular solution depends on several factors:

  • What types of data will you be working with?
  • What data sources are available to the business?
  • How much computational load can your infrastructure handle?

Developing a Data Ethics Policy
The responsibility of being a good driver falls to this managerial role. Behind the wheel of a car, there are written rules of the road that enforce safe driving. There are also unwritten rules of courtesy. Data ethics address the moral element of gathering and employing data. It doesn’t ask, “Can we?” but “Should we?” In this area, some of the biggest companies in the world have gotten it massively wrong and suffered severe reputational damage. In formulating your data ethics policy, you must fully understand the rights that every individual possesses around their data — the rights of ownership, transparency, and privacy, to name a few.

Drivers must also understand the process of building an AI solution to avoid unethical outcomes. For instance, AI that unintentionally targets vulnerable populations or exhibits racial bias. Many businesses think of data ethics as an obstacle, as red tape they have to finagle their way around, but a good data ethics policy offers myriad benefits to the business:

  • Customers are more aware than ever of the ways they can be taken advantage of through technology. A commitment to the ethical use of technology can make a company stand out and appeal to customers.
  • If the AI is biased or unethical, it will not deliver a clear, accurate picture of the business or industry landscape. As a result, you may chase the wrong opportunity or let the right opportunity slip by under the radar.
  • As problems result from unethical tech and data practices, laws like the General Data Protection Regulation, the California Consumer Privacy Act, and the EU Artificial Intelligence Act are coming into place to protect consumers. Ethical data practices mitigate compliance risk.

Technology will continue to become more powerful and more synonymous with business strategy. It is vital to use this great power responsibly and ethically.

What Makes a Good Driver
At the end of the day, the best drivers reach the right destination within a reasonable timeframe. The car arrives intact, and no one is hurt along the way.

When the time comes to take the next trip, they’ll turn to you for a smooth ride.

Learn more about credentials for drivers (manager-level roles):

  • Data Science for Business (DSBIZ) offers business leaders, sales and marketing managers, project managers, and other stakeholders a streamlined course to help make decisions and drive organizational data science strategies. DSBIZ candidates will learn data science concepts, methods of use, challenges, and benefits using relevant business examples.
  • Data Ethics for Business (DEBIZ) is designed for business leaders and decision makers, including C-level executives, project and product managers, HR leaders, marketing and sales leaders, and technical sales consultants, who have a vested interest in the representation of ethical values in technology solutions.
  • Artificial Intelligence for Business (AIBIZ) offers business leaders, project managers, and other stakeholders a streamlined course and associated credential to drive their AI strategy. AIBIZ candidates will learn AI concepts, approaches to machine learning and deep learning, fundamentals of AI implementations, and the impact of AI including business use cases.
  • Internet of Things for Business (IoTBIZ) offers business leaders a streamlined course and associated credential to open collaboration and drive informed business decisions for their IoT strategy. IoTBIZ candidates will learn IoT terminology to understand the components of IoT infrastructure, uncover challenges for consideration, and discover the impact that IoT has on their organization.
  • Emerging Technologies for Business (ETBIZ) is a combination of three CertNexus credentials (AIBIZ, DSBIZ, and IoTBIZ) which cover the most often used technologies to generate data, extract insights from data, and leverage data to predict future outcomes. Upon successful completion of this credentialing assessment, candidates will earn the capstone ETBIZ credential and receive a badge which can be posted on social media platforms to identify your dedication to emerging technologies.



Getting Under the Hood of Your Digital Transformation

​​Jeff Felice, President, CertNexus

Jeff Felice

We recently shared two articles comparing your digital transformation to a journey, with your business leaders as the passengers and manager-level roles as the drivers. When we talk about your digital transformation “journey,” it’s an apt analogy. The future state of your business is your destination, and your digital transformation is the vehicle that will deliver you there. Everyone must play their role, whether they are business leaders, managers, or technical roles like data scientists and machine learning engineers. In this final article, we’ll help you think about your organization’s path forward and how to attain the knowledge and technical skills you need to keep your digital transformation on course.

There’s one more role to fill in your digital transformation—the mechanic who makes your vehicle run. Mechanics are the technicians who will create and implement the technology for your business.

Roles like data scientists and machine learning engineers will function as the mechanics on your digital transformation journey. They ultimately own the data and development of AI-driven solutions.

The Technical Skills Needed

While the passengers and drivers of your digital transformation need knowledge, mechanics need hard skills to bring AI strategies to life.

Programming Capabilities
The ability to use programming languages such as Python® is a fundamental skill for data scientists and machine learning engineers. Although not used in the traditional sense to develop applications, Python skills are used to wrangle and engineer data into usable models.

Ethical Considerations
AI is built to reflect and learn from what it’s given. In this way, bias and prejudice can be baked right into the very core of a tool. If an algorithm is trained with biased data, it will only amplify that bias as it learns. If those using the tool exhibit prejudicial preferences, the algorithm will reflect that prejudice in its future results.

A good mechanic can see these issues coming and implement guardrails that keep the AI on an ethical, effective course.

The Ability to Transform Data into Insights
The role of a data scientist is more consultative than prescriptive. Rarely will they receive the instruction to “Use x data and method y to determine z.” More often, the question will be something like “How can we streamline our workflow to lower the cost of our work product by 10%?”

The data scientist must be able to translate this need into a data-driven solution. To do that, the scientist must understand the problem at hand, why it’s important to solve it, what data is available to work with, and what outcomes are possible.

Ultimately, the data doesn’t speak for itself. Data technicians act as both stewards and storytellers, interpreting the data into actionable insights.

What Makes a Good Technical Mechanic

The best mechanics have a unique blend of technical ability and business acumen. They’re good communicators who are naturally curious. Most importantly, they can keep your digital transformation firing on all cylinders.

Learn more about certifications for people in technical roles:

  • Certified Data Science Practitioner (CDSP) develops knowledge, skills, and abilities required to answer questions by collecting, wrangling, and exploring data sets, applying statistical models and artificial-intelligence algorithms, to extract and communicate knowledge and insights.
  • Certified Ethical Emerging Technologist™ (CEET) is designed for individuals seeking to demonstrate a vendor-neutral, cross-industry, and multidisciplinary understanding of applied technology ethics that will enable them to navigate the processes by which ethical integrity may be upheld within emerging data-driven technology fields, such as artificial intelligence (AI)/machine learning, Internet of Things (IoT), and data science.
  • Certified Artificial Intelligence Practitioner (CAIP) and the corresponding training program is designed for information technology practitioners entering the field of artificial intelligence who are seeking to build a vendor-neutral, cross-industry foundational knowledge of AI concepts, technologies, algorithms, and applications that will enable them to become capable practitioners in a wide variety of AI-related job functions.
  • With Cyber Secure Coder® (CSC), candidates will learn about vulnerabilities that undermine security and how to identify and remediate them in projects. Candidates will also learn general strategies for dealing with security defects and misconfiguration, how to design software to deal with the human element in security, and how to incorporate security into all phases of development.
  • The CyberSec First Responder® (CFR) certification validates the knowledge and abilities to combat the changing threat landscape and protect critical information systems before, during, and after an incident. This course has been developed to ANSI/ISO/EIC 17024 standards and is approved by the U.S. Department of Defense to fulfill Directive 8570/8140 requirements.
  • Certified Internet of Things Practitioner (CIoTP) and Certified Internet of Things Security Practitioner (CIoTSP) are geared to give you a vendor-neutral, cross-industry skill set for implementing and managing a secure IoT ecosystem.

Recap: Starting Your Engine

To recap:

  • Passengers (business leaders) need a general understanding of the terminology and concepts, plus the opportunities and limits of the technology. They are responsible for defining the goals of the business and the strategy around meeting those goals.
  • Drivers (project managers and product owners) need to understand the business strategy and possess a more practical grasp of how the technology may be applied toward that strategy. They are responsible for ensuring the strategy is translated to the technical application of your digital transformation.
  • Mechanics (data scientists and machine learning engineers) need to understand the how and why behind the business strategy, and the extent of the resources at their disposal. They are responsible for using their deep knowledge of the technology to construct AI and data-driven solutions that advance business strategy.

Digital transformation only works when everyone is aligned to the future state of the business. When everyone has the knowledge they need from others and has provided the knowledge that others need from them, you’re ready to hit the road.


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Content Revisions

Logical Operations revises student and instructor materials based on technical changes, customer feedback, and our own assessment of necessary changes. The revision notes for the most recent updates are posted on the Content Revisions page. 

Recent revisions:
  • Advanced Programming Techniques with Python® (094022) 
    • For version 1.2, released June, 2023, changes were made to activity steps for Lessons 5 and 8 to correct a recent issue with installing Flask libraries. For more information, visit our Content Revisions page.
  • Certified CMMC Assessor (CCA) (093201​​​​​​)
    • The 1.1 revision, released April, 2023, corrected a few errata. For more information, visit our Content Revisions page.
  • Certified CMMC Professional (CCP) (093200)
    • The 2.2 revision, released April, 2023, corrected a few errata. For more information, visit our Content Revisions page.
  • CMMC: Organizational Foundations (093202)
    • The 2.2 revision, released May, 2023, the course has been retitled and a few errata corrected. For more information, visit our Content Revisions page
  • Microsoft® SharePoint® Modern Experience: Advanced Site Owner (091097) 
    • For version 2.0, released May, 2023, the course has been completely revised and re-designed in response to customer input as well as software changes. For more information, see the Bridge Document on our Content Revisions page.