CertNexus Certified

Data Ethics for Business Professionals

DEBIZ enables business professionals to identify, explain, and document how their organization identifies ethical principles, sources of risk, and creates sustainable ethical decision-making processes.

Download Brochure Exam Details Course Modules

Oct 2021 Launch

25 Questions

80% Pass Rate

Career Paths with DEBIZ

DEBIZ is intended for business leaders, stakeholders, product and project managers, and anyone delivering ethical, data-driven solutions.

Who should earn DEBIZ?

DEBIZ is designed for business professionals at all levels who work with data and want to understand the ethical dimensions of their decisions. This includes product managers, project leads, executives, policy professionals, and anyone who influences how data is collected, used, or governed. No technical background required — DEBIZ makes ethical principles accessible to all.

DEB-110 Exam Details

The DEBIZ credential demonstrates foundational knowledge of ethical data use in emerging technologies with practical business application.

Exam Code

DEB-110

Launch Date

October 2021

Duration

20–45 Minutes

Questions

25 Items

Passing Score

80% (20/25)

Exam Platform

CHOICE LMS

Target Candidate

Open to new and established professionals seeking to learn about data ethics in the modern business world. Candidates may retake the DEB-110 exam as many times as desired.

Why Get DEBIZ Certified?

DEBIZ makes ethical principles accessible and risk mitigation possible for all your data-driven business initiatives.

🛡️

Build Trust

Define processes to stay abreast of dynamic trustworthy tech requirements as regulations evolve globally.

🚀

Lead Ethical Data Initiatives

Verify that your data stakeholders have the knowledge to design and deliver ethically aligned projects.

⚖️

Manage Risk

Identify sources of risk including bias, discrimination, surveillance, and safety concerns in data-driven technologies.

📊

Drive Business Value

Commercial justifications for acting ethically — talent retention, consumer loyalty, investor relationships, brand enhancement.

Data Ethics for Business Training

CertNexus DEBIZ training covers foundational terminology, technical concepts, and business use cases so you can actively participate or lead your next ethical data project.

3-Module Practical Curriculum

54 video classes covering ethical principles, business considerations, and sources of risk in data-driven decisions.

Business-Focused Approach

Real-world scenarios exploring GDPR, bias, transparency, fairness, and organizational accountability.

37 Working Hours

Flexible video package with download access, plus live online class with recording available.

Unlimited Exam Retakes

The DEB-110 exam via CHOICE LMS can be retaken as many times as needed — learn at your own pace.

Course Modules

Three comprehensive modules covering ethical principles, business considerations, and sources of risk.

Data privacy — privacy models (comprehensive, sectoral, co-regulatory, self-regulatory), GDPR, HIPAA, Privacy by Design

Accountability — data governance frameworks, DPIAs, ACM Code of Professional Ethics, ethical design

Transparency and explainability — data transparency, AI decision notices, secondary uses of data, auditability

Human-centered values and fairness — procedural and outcome fairness, protected classes, community involvement

Inclusive growth and sustainable development — tech for good, human agency, indigenous data governance, global inclusivity

Trade-off analysis — methodology for identifying and assessing competing ethical criteria

Legal compliance — product liability, GDPR, BIPA, anti-discrimination laws (Fair Credit Reporting Act, Title VII)

Social and behavioral effects — disinformation, nudging, social rating systems, user profiling algorithms

Responsible business practices — stakeholder management, data hygiene, credibility and reliability

Business reputation impact — talent attraction, consumer loyalty, investor relationships, brand enhancement

Organizational values along the data value chain — ethical culture, decision-making, ethical supply chain management

Business case for ethics — commercial justifications, value alignment, regulatory lag vs. technology innovation

Bias in emerging tech — statistical bias, historical/structural/sampling bias, technocentrism, bias mitigation

AI discrimination — disparate impact, unintentional data discrimination, fairness above analytics

Safety and security — data protection principles, cyber security, unauthorized disclosure, adversarial machine learning

Abnormal AI outputs — concept drift, human in the loop, detecting abnormal behaviors

Data surveillance — online tracking, biometric data, facial recognition, smart home/city, employee surveillance