Preventing Data Leaks & Data Breaches from Happening

Useful Measures and Practices for Safeguarding Your Business Assets

In a distant realm of the Kingdom of Bonanza stood the Vault of Veritas, a great repository where every citizen’s secrets were kept safe. Scholars, merchants, and nobles alike entrusted their most precious scrolls—birth chronicles, financial records, trade agreements, and family histories—to its iron-constructed chambers. The Guardians of the Vault of Veritas – 4 vigilant sentinels in gleaming armor – watched over thick oak doors. Each sentinel represented a layer of protection: the Outer Gate (firewalls), the Watchtowers (intrusion detection), the Sealed Chambers (encryption), and so on. Together, they formed an unbroken circle around the Vault of Veritas. One moonlit night, a lowly apprentice named Novicia tightened his belt too firmly, leaned against the eastern door, and inadvertently loosened a hidden hinge. A very thin crack formed in the ironwork—barely perceptible, but enough for a soft whistle of air to slip through. The Vault of Veritas Door was imperceptibly cracked through a minuscule breach. From that tiny fissure, the hush of the Vault of Veritas escaped in wisps of parchment and ink. Outside the shielded premises of the Vault of Veritas, couriers and other messengers on the road caught fragments of letters, traders pieced together snippets of invaluable contracts, and foreign spies smelled opportunity. Each stolen secret fed the next, until rumors swelled like a gathering storm through the whispers in the wind. Within weeks, the secrets of the Vault of Veritas flooded the market stalls of the Kingdom of Bonanza. Citizens found their financial records and inheritance claims undermined, rivals weaponized family scandals, and the Kingdom of Bonanza’s reputation was in tatters. The silent crack had blossomed into a roaring breach fueling information eruption. Outside the shielded premises of the Vault of Veritas, couriers and other messengers on the road caught fragments of letters, traders pieced together snippets of invaluable contracts, and foreign spies smelled opportunity. Each stolen secret fed the next, until rumors swelled like a gathering storm through the whispers in the wind. Within weeks, the secrets of the Vault of Veritas flooded the market stalls of the Kingdom of Bonanza.

Citizens found their financial records and inheritance claims undermined, rivals weaponized family scandals, and the Kingdom of Bonanza’s reputation was in tatters. The silent crack had blossomed into a roaring breach fueling information eruption.

With reference to Preventing Data Leaks & Data Breaches from Happening – the subject matter of our current August 2025 Newsletter –, the moral lessons to be learnt from the above leaks and disclosures of the Vault of Veritas could be circumscribed as follows: (1) inspect every hinge and hinge-pin: continuous monitoring can catch the smallest faults; (2) train every apprentice: human mistake can weaken the mightiest defenses; (3) reinforce multilayered barriers: by himself, no single sentinel can hold back a gathering tide; (4) seal and re-seal with precision and care: prompt patches can close cracks before they indiscernibly widen; (5) prepare for worst-case breaches: an Incident Response Plan (IRP) can help your businesses adjust and rebuild.

Multi-Sectorial Impacts of Data Leaks on Multi-Layered Data Content

In Canada, data leaks can affect a wide range of information depending on the organization’s sector and data practices. Privacy laws like PIPEDA and provincial regulations govern how data must be protected, especially in sensitive areas like healthcare and the public sector. Data breaches can lead to serious legal, financial, and reputational consequences for organizations that fail to safeguard personal information.

Health data, or Personal Health Information (PHI), is one of the most sensitive categories, including medical records and patient treatment medical histories. Health data is regulated under laws such as Ontario’s PHIPA, and breaches can result in heavy penalties and loss of public trust. Similarly, Personally Identifiable Information (PII)—such as names, SINs, and biometric data—is highly vulnerable. Exposure can lead to identity theft and fraud, and under PIPEDA, organizations must report breaches that pose significant harm.

Businesses also face risks from data leaks of trade secrets and proprietary data like source code, algorithms, and strategic plans. Such breaches can erode competitive advantage and lead to lawsuits. Client databases containing behavioral and transactional data are frequently targeted, and their exposure can result in reputational damage and phishing attacks. Organizations may also be held liable under privacy laws or contractual obligations for failing to protect such data.

Other high-value targets include legal documents, financial records, and government data. Data leaks of contracts or classified information can disrupt negotiations, expose liabilities, and even threaten national security. Cyber attackers also seek authentication credentials and IT infrastructure data, which can enable deeper IT system access and facilitate ransomware attacks. Protecting these assets is critical to maintaining operational integrity and public confidence.

Data Leaks: An Abridged Conceptual Overview

The 19 monographs [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19] cited in the Resources and References Section of this August 2025 Newsletter have been consulted, summarized and adapted for the writing of several parts of this document.

From a holistic computer science point of view, data leaks are unauthorized disclosures of sensitive, confidential, or personal information from an organization’s IT systems or networks to an external party. Data leaks imply there are data losses, which are the unintentional removal or destruction of sensitive information, making it inaccessible or unrecoverable.

Data leaks can be accidental—such as misconfigurations or human error—or intentional, when insiders purposely expose information. They may happen without direct exploitation of security vulnerabilities and can lead to serious consequences, including reputational damage, legal penalties, and competitive disadvantages.

Furthermore, data leaks occur when complex, confidential, or protected information is inadvertently exposed to an unapproved party. Such an exposure can materialize through digital channels—such as email, cloud computing storage, or application logs—or via physical media, and typically arises from security oversights rather than deliberate cyberattacks.

Data Leaks: Some Major Characteristics

Data leaks can originate from within the organization (internal sources) but they can also result from misconfigured storage, human errors, or involuntary insider actions. Data leaks differ from data breaches, which typically involve an external attacker exploiting a vulnerability. Generally speaking, data leaks may not involve hacking tools or malware because sometimes data simply sits exposed.

Differences Between Data Leak and Data Breach

Why is it important to differentiate data leak from data breach? Recognizing whether an incident is a leak or a breach can shape both technical remediation—patching versus policy enforcement—and legal obligations such as public disclosures under regulations like PIPEDA, GDPR and HIPAA.

On the one hand, a data breach refers to an event where an external or internal actor intentionally exploits IT systems vulnerabilities or stolen credentials to gain unauthorized access to confidential information for malicious purposes.

On the other hand, a data leak occurs when sensitive data is unintentionally exposed—often due to misconfigurations, human error, or inadequate controls—without a direct cyberattack or malicious intent.

Figure 1: Main Differences Between Data Leak and Data Breach

While data leak and data breach are two distinct computer science concepts, the two columns below are not mutually exclusive in terms of information technology.

Helpful Strategic Measures and Best Practices for Preventing Data Leaks from Happening

1. Governance and Policy Framework

Establishing a solid policy foundation ensures everyone in the organization understands their roles in protecting data.

Policies should be living documents reviewed at least annually or whenever major tech changes occur.

• Define data classification levels (e.g., public, internal, confidential, restricted).
• Mandate data handling procedures per classification (storage, sharing, retention).
• Enforce least-privilege principle: grant users only the access they need.
• Require vendor and third-party security assessments before integration.
• Permanently remove data that is no longer relevant to operations or compliance requirements.

2. Identity and Access Management (IAM)

Robust IAM controls reduce the attack surface by tightly managing who can see or move sensitive information.

• Implement multi-factor authentication (MFA) for all privileged accounts.
• Use role-based access control (RBAC) to align permissions with job functions.
• Automate onboarding/offboarding workflows to avoid orphaned accounts.
• Regularly audit and recertify privileges—ideally quarterly.

3. Technical Controls

Deploying the right tools and configurations prevents accidental exposures and thwarts common exploits.

Figure 2: Technical Controls for Data Leaks Prevention

4. Employee Training and Awareness

Human error remains one of the top causes generating data leaks. Ongoing education can transform your staff into your first line of cyber defense.

• Conduct mandatory security awareness training at the hiring of new employee, and annually.
• Simulate phishing and data-handling exercises to measure readiness.
• Publish quick-reference guides on how to report suspected leaks.
• Celebrate and reward “good catches” when employees spot potential issues.

5. Monitoring, Auditing, and Incident Response Plan

Early detection and structured response minimize the impact of a data leakage.

1. Continuous Monitoring
   • Inspect logs from endpoints, network devices, cloud services, and applications.
   • Leverage User Behavior Analytics (UBA) for anomaly detection.
2. Regular Audits
   • Perform quarterly configuration and access reviews.
   • Engage external auditors for unbiased security assessments.
3. Incident Response Plan

• Define triage, containment, eradication, and recovery steps.
• Establish communication protocols internally and with regulators.
• Run tabletop exercises to validate and refine the Incident Response Plan.

6. Continuous Improvement and Compliance

Cybersecurity is a journey and not a destination. Harmonize your regular efforts with evolving standards and cyber threat landscapes by applying the following approaches:

• Track and remediate findings from vulnerability scans and penetration tests.
• Stay updated on relevant regulations (PIPEDA, GDPR, HIPAA) and incorporate new requirements.
• Benchmark against industry frameworks (ISO 27001, NIST CSF, CIS Controls).
• Invest in emerging defenses: zero trust architecture, data sandboxing, and confidential computing.
• Consider homomorphic encryption and how it enables computations on encrypted data.
• Use automated Data Leak Prevention (DLP) with machine-learning–driven content inspection.
• Think about Privacy-Enhancing Technologies (PETs) for secure data sharing and analytics.
• Build a security-focused culture: leadership buy-in, security champions, and cross-department collaborations.
• Leverage Secure Access Service Edge (SASE) to converge network and technical security controls.

Real-World Effectiveness of Data Leaks Prevention Measures and Best Practices

How effective are the above-described measures and best practices in real-word scenarios? Shortened below are our answers to that question:

Governance and Policy Framework

Organizations that implement formal data classification and handling policies see accidental leak incidents drop significantly. A 2021 Study by UpGuard found that half of Fortune 500 companies were leaking sensitive information through misconfigured public documents—underscoring how governance frameworks reduce human and system oversights.

Identity and Access Management

Multi-factor authentication (MFA) and Role-Based Access Controls (RBAC) are highly efficient at preventing unauthorized data access. Industry analyses show MFA blocks over 99% of automated credential-theft attacks, while regular privilege recertification curbs “orphaned” accounts and limits too much privilege given to some staff.

Technical Controls

Encrypting data at rest and in transit ensures that exfiltrated files remain unreadable. Modern DLP solutions that inspect content across networks, endpoints, and cloud repositories can detect and block up to 95% of unauthorized transfers.

Tracking your Data Loss or Leakage Prevention Rate—the ratio of blocked incidents versus total attempts—is key to quantifying tool performance.

Employee Training and Awareness

Human error drives many data leaks. Organizations running periodic phishing simulations report a 50–70% reduction in click-through rates on malicious emails.

Continuous security awareness programs also accelerate incident reporting, helping shrink both Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR) against suspicious activities.

Monitoring, Auditing, and Incident Response Plan

Continuous monitoring—using SIEM, UEBA, and DLP analytics—enables real-time anomaly detection. Best-in-class security teams achieve MTTD under one hour and MTTR under two hours, restraining leaks before major data loss occurs. Quarterly configuration audits and tabletop exercises further refine Incident Response Plan workflows.

Limitations and Challenges Pertaining to Data Leaks Prevention Measures

• False positives can lead to alert fatigue and policy workarounds.
• Insider threats and third-party misconfigurations may slip past standard DLP controls.
• Evolving environments (cloud computing migrations, remote work) demand continuous policy, regular monitoring, consistent audits, and tool updates.

When thoughtfully combined—governance and policy framework, IAM, encryption, staff training, monitoring—these measures can reduce accidental data leak incidents by over 60%, lower breach remediation costs, and bolster compliance with regulations such as PIPEDA, GDPR, and HIPAA. Unceasing improvement, robust metrics, and alignment with frameworks like ISO 27001 or NIST CSF keep your defenses ahead of emerging cyber threats.

2 CASE STUDIES of Data Leaks Prevention for Organizations in Canada

The following case study has been summarized and adapted from a data leak awareness article (Investigations into Businesses) published on the website of the Office of the Privacy Commissioner of Canada [19]. It is entitled Investigation into Desjardins’ Compliance with PIPEDA Following a Breach of Personal Information Between 2017 and 2019.

Useful Tools for Preventing Data Leaks from Affecting SMEs

This section of our August 2025 Newsletter has been meticulously researched and carefully written for the utmost safety benefits of SMEs doing their best to deliver the goods amidst prevailing cyber threats and unexpected cyber attacks. Succinctly described below is a curated selection of cost-effective, SMEs-friendly solutions across major data leaks prevention domains. Each tool is precisely chosen for ease of deployment, scalability, and strong technical support for smaller IT teams working within SMEs. Due to the nature of this newsletter, only free tools are highlighted.

Why Do SMEs Need Data Leaks Prevention?

Data breaches can cripple small and medium-sized enterprises through financial penalties, lost customer trust, and reputational damage. For example, in 2023 a major tech company was fined $1.3 billion under GDPR—an expense few SMEs could withstand. The categories highlighted below can help you assemble a multi-layered cyber defense. Please feel free to mix and match based on your own SMEs work environments and related budgets.

Open-Source Data Loss Prevention (DLP) Solutions

Data Loss Prevention (DLP) encompasses strategies, processes, and tools designed to proactively identify, monitor, and control sensitive information to prevent unauthorized access or sharing.

Figure 3: Free Tools for Preventing Data Leaks in SMEs

Code and Secret Leakage Prevention

Accidental exposures often happen when API keys, tokens or credentials are hard-coded into repositories. Continuous scanning tools integrate into CI/CD pipelines to catch these leaks before code merges:

• Piiano Flows: Tracks data flows and PII exposures, with daily scans and AI-driven analysis.
• GitGuardian (free tier): Monitors public GitHub repositories for exposed secrets and alerts on incidents and potential cyberattacks.
• TruffleHog: Searches Git history for high-entropy strings indicative of secrets.
• GitLeaks: Uses regex patterns to detect credentials in data leaks and breaches history.

Web and Dark Web Monitoring

Regularly checking whether customer or corporate accounts appear in public breach databases helps mitigate damage early. Free services include:

• Have I Been Pwned: Monitors email addresses against known data breaches.
• SpyCloud (Community): Offers basic breach alerts for compromised credentials.

Encryption and Endpoint Defense

Securing data at rest and thwarting malware-based exfiltration are critical layers:

• VeraCrypt: Open-source full-disk and container encryption.
• BitLocker: Built-in Windows Pro/Enterprise full-disk encryption.
• ClamAV: Free antivirus engine to detect infostealer malware.

Implementation Tips

• Integrate secret scanners into pull request workflows.
• Define and enforce DLP policies on shared drives and email gateways.
• Schedule regular dark-web and breach database checks.
• Encrypt all sensitive data at rest and in transit.
• Train staff on handling credentials and recognizing phishing attempts.

Data Leaks Prevention Tools: Selection Criteria for SMEs

• Simplicity: Look for SaaS or cloud-native options with guided onboarding.
• Cost: Favor per-user or tiered pricing that scales with growth.
• Integration: Ensure compatibility with your existing stack (e.g.: Microsoft 365, AWS, popular POS systems).
• Support & Documentation: Strong vendor resources shorten resolution times for small IT teams.
• Lightweight Agents: Minimize performance impact on endpoints and servers.

Data Leaks Prevention Tools: Implementation Roadmap for SMEs

1. Assess & Prioritize
   • Map your crown-jewel data and classify sensitivity.
   • Identify high-risk channels: email, cloud shares, USB devices.
2. Deploy Core Controls
   • Start with DLP policies on email and cloud storage.
   • Enable MFA via an IAM solution (e.g.: Okta) for all privileged accounts.
3. Implement Layer Monitoring
   • Roll out dark-web monitoring for leaked credentials.
   • Configure user-activity alerts to catch anomalous file access.
4. Apply Continuous Tuning
   • Review false positives monthly and refine policies.
   • Conduct quarterly tabletop exercises to validate incident response.
5. Scale and Adapt
   • Extend coverage to new data stores (IoT logs, dev environments).
   • Integrate threat-intelligence feeds to pre-empt emerging data leaks vectors.
6. Pilot, Subscribe, Schedule & Explore
   • Pilot a DLP trial with one business unit to measure blocked incidents and admin overhead.
   • Subscribe to a managed dark web monitoring service to get early warnings on exposed credentials.
   • Schedule a cybersecurity awareness workshop focused on data management best practices.
   • Explore integration with CASB or SASE platforms for unified cloud and network controls.

By carefully and selectively combining the above-mentioned targeted data leaks prevention tools with practical policies and ongoing staff training, SMEs throughout Canada can dramatically reduce accidental and malicious data disclosures while keeping costs and complexity within manageable boundaries.

Data Leaks Prevention Tools Implementation within SMEs: 6 Actionable Recommendations

Conduct an attack surface audit to inventory all internal assets and key third-party touchpoints. Implement continuous monitoring to flag misconfigurations before they result in leaks. Follow and apply the following actionable recommendations:

1. Pilot AI-enhanced DLP solutions that leverage behavioral analytics. Focus first on the most critical data repositories (customer PII, financial records, intellectual property) to measure ROI quickly.
2. Roll out a Zero Trust pilot for high-risk applications. Enforce multi-factor authentication and role-based access controls, expanding to additional systems over a 6- to 12-month window.
3. Deploy MDM and endpoint encryption across laptops and mobile devices. Include remote-wipe and geofencing features to secure data on lost or stolen hardware.
4. Update or craft a comprehensive DLP policy covering classification, handling, retention, and archive procedures. Pair policy with regular employee training and simulated phishing exercises.
5. Integrate compliance-automation tools that scan your processes against local, national, and sector-specific data-protection laws, generating real-time audit trails.
6. Establish a Data Leaks Incident Response Plan, complete with escalation workflows and post-mortem analyses, ensuring continuous improvement and rapid recovery.

Conclusion

How will data leaks prevention methods potentially evolve in the future? Shortened hereunder are some future trends and prospects related to preventing data disclosures from happening and striking SMEs:

Intelligent, Context-Aware DLP Systems

Organizations are moving beyond static rules toward behavior-driven, contextual heuristics that infer intent and flag anomalies in real time. By correlating login times, device fingerprints, mouse trajectories, and access patterns, advanced DLP solutions can automatically quarantine or revoke access when suspicious activity surfaces. Artificial intelligence and machine learning models continuously learn what “normal” looks like, reducing false positives and adapting to new threats without manual tuning. Integrations with UEBA (User and Entity Behavior Analytics) and SIEM platforms further enrich incident triage and enforcement workflows.

Privacy-Centric and Regulatory-Integrated Controls

Future DLP architectures embed compliance directly into data flows, automatically tagging personal data (PII, PHI) and enforcing region-specific rules such as Schrems II or CCPA. This fusion of data governance and DLP ensures real-time blocking of non-compliant transfers and generates audit-ready reports on demand. Semi-automated classification engines will populate dynamic compliance dashboards, minimizing manual effort and shrinking regulatory risk. Organizations that master this integration gain both transparency and agility as privacy laws evolve.

Protection of Emerging Data Types

The next frontier for DLP extends analysis beyond documents to audio, video, and live streams. Advances in NLP and speech-to-text enable real-time inspection of boardroom conversations, voicemails, or video conferences for confidential keywords and patterns. As multimedia becomes a primary business channel, DLP tools will leverage OCR, pattern-matching, and AI-driven metadata extraction to secure every format. Early adopters in finance and healthcare are already piloting live-audio exfiltration defenses.

Zero Trust and Distributed Architectures

Zero-trust principles are reshaping DLP by treating every request as untrusted until verified. Data-centric zero trust enforces micro segmentation, continuous authentication, and just-in-time permissions at the file and object level. When combined with Secure Access Service Edge (SASE), organizations can unify networking and security controls, ensuring policy consistency across on-premises, cloud, and remote endpoints. This holistic model dramatically reduces the attack surface for lateral movement.

Cloud-Native and Hybrid Environment Solutions

With the majority of workloads now in public or multi-cloud computing environments, DLP solutions are evolving into cloud-native services or Cloud Access Security Brokers (CASBs). They deliver scalable, API-driven visibility across platforms like Google Workspace, Microsoft 365, AWS, and Salesforce. Built-in encryption, continuous backups following the 3-2-1 rule, and real-time anomaly detection ensure that millions and millions of data remain protected at rest, in motion, and in use. Automated policy enforcement spans SaaS, IaaS, and PaaS with minimal operational overhead.

Predictive and Proactive Measures

Predictive analytics, powered by threat-intelligence feeds and historical breach data, will forecast high-risk scenarios before they materialize. Machine learning models trained on global telemetry can anticipate attacker tactics and pre-position countermeasures on critical assets. Simultaneously, continuous cyber attack surface monitoring—covering both internal infrastructure and third-party vendor ecosystems—will uncover latent misconfigurations and blind spots, closing proactively data leaks vectors.

Emerging Technologies on the Horizon

• Homomorphic Encryption and Confidential Computing: Enable secure processing of encrypted data without decryption, shrinking the window for leaks.
• Blockchain-Based Integrity: Immutable ledgers will log every data access and transfer, simplifying audit trails and tamper detection.
• Agentic AI in IAM: Autonomous agents will dynamically adjust user privileges based on risk posture and behavioral signals.

Data Leaks Prevention Measures: An Abridged Outlook

In the course of the next 5 years, data leaks and breaches prevention will converge with Extended Detection and Response (XDR), decentralized identity frameworks, and quantum-resistant cryptography. All types of organizations that embrace AI-driven, privacy-first strategies and invest in adaptive, cloud computing-native architectures will be best positioned to outpace emerging cyber threats and regulatory demands. Further exploration might include the intersection of DLP with Privacy-Enhancing Technologies (PETs), the role of digital twins in simulating data leaks scenarios, and strategies for securing machine-generated data in IoT and edge computing environments.

By 2030, SMEs embracing these prognoses will view data leak prevention not as a cost center but as a competitive differentiator. Automated, intelligence-driven defenses will scale security in line with growth, while proactive compliance tooling will demystify complex regulations. Organizations that combine cyber attack surface visibility, AI-powered data leaks forecasting, and a mature Zero Trust posture will achieve an adaptive cybersecurity model—one that learns from each attempt and remediates before invaluable data ever walks out the door. Beyond these forecasts, SMEs should also explore: (1) security culture metrics to track how well IT teams follow policies over time; (2) return on security investment (ROSI) frameworks to justify new tooling to stakeholders; (3) cyber threat intelligence sharing within industry consortia to benefit from collective insights. Mapping these elements into an integrated roadmap will prepare SMEs not just for tomorrow’s data leaks incidents, but for the shifting cyber threat landscape of the years to come.

Resources and References

1. Guy Bunker and Gareth Fraser-King. Data Leaks for Dummies: Making Everything Easier. 1^st Paperback Edition published on the 24^th of February 2019, O’Reilly Media Inc. – American Learning Company, Headquarters: Sebastopol, California, USA, 432 pages. Data Leaks For Dummies: Making Everything Easier – 1^st Paperback Edition – Book – O’Reilly Media Inc – American Learning Company
2. Joe Reiss and Matt Housley. Fundamentals of Data Engineering: Plan and Build Robust Data Systems. 1^st Paperback Edition published on the 26^th of July 2022, O’Reilly Media Inc. – American Learning Company, Headquarters: Sebastopol, California, USA, 450 pages. Fundamentals of Data Engineering: Plan and Build Robust Data Systems – Book – O’Reilly Media Inc – American Learning Company
3. National Institute of Standards and Technology (NIST). United States Department of Commerce. NIST Internal Report—NIST IR 8496 IPD. Data Classification Concepts and Considerations for Improving Data Protection, Initial Public Draft, November 2023, 17 pages. Data Classification Concepts and Considerations for Improving Data Protection – NIST Document for Continuous Learning
4. Harvard University. PrivSec – Information Security and Data Privacy. The Data Lifecycle: About Policies, Standards, Awareness and Education. Cambridge, Massachusetts, USA. The Data Lifecycle: About Policies, Standards, Awareness and Education | Harvard University Information Security and Data Privacy – PrivSec
5. Oleg Gusikhin, Slimane Hammoudi and Alfredo Cuzzocrea (Editors). Data Management Technologies and Applications: Conference Proceedings, 12^th International Conference, DATA 2023, Rome, Italy, July 11–14, 2023, Revised Selected Papers. Published on the 6^th of September 2024, Springer Nature Academic Publisher, German-British Publishing Company, Headquarters: London, United Kingdom, 242 pages. Data Management Technologies and Applications: 12th International Conference, DATA 2023, Rome, Italy, July 11–13, 2023, Revised Selected Papers | SpringerLink
6. K. Selçuk Candan and Maria Luisa Sapino. Data Management for Multimedia Retrieval: Knowledge Management, Databases and Data Mining for Computer Science, Software Engineering and Development. Print Hardcover Edition of July 2010 and Online Edition of July 2014, Cambridge University Press, Cambridge, United Kingdom, 500 pages. Data Management for Multimedia Retrieval: Knowledge Management, Databases and Data Mining for Computer Science, Software Engineering and Development
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8. David Feng, W.C. Siu & Hong Jiang Zhang (Editors). Multimedia Information Retrieval and Management: Technological Fundamentals and Applications. Paperback Edition published on the 15^th of December 2010, Springer Nature Academic Publisher, German-British Publishing Company, Headquarters: London, United Kingdom, 476 pages. Multimedia Information Retrieval and Management: Technological Fundamentals and Applications | SpringerLink
9. Ravi Jay Gunnoo. Cybersecurity Education Compendium: Harnessing Digital Safety Best Practices Across the World. 1^st Original Edition published in Paperback—Large Print Format and e-Book Version. Publication date: the 18^th of September 2024. Publishing Company: Amazon USA Publishing, Seattle, State of Washington, USA, 728 pages, ISBN: 9798336620344. CYBERSECURITY EDUCATION COMPENDIUM: Harnessing Digital Safety Best Practices Across the World: Gunnoo, Ravi Jay: 9798336620344: Books – Amazon.ca
10. John Ladley. Data Governance: How to Design, Deploy and Sustain an Effective Data Governance. 2^nd Edition published in paperback on the 8^th of November 2019, Academic Press—an imprint of Elsevier, Salt Lake City, Utah, USA, 350 pages. Data Governance: How to Design, Deploy and Sustain an Effective Data Governance – 2nd Paperback Edition | Elsevier Shop
11. Mohan Subramaniam. The Future of Competitive Strategy: Unleashing the Power of Data and Digital Ecosystems. Hardcover Edition published on the 16^th of August 2022. The Massachusetts Institute of Technology (MIT) Press, Cambridge, Massachusetts, USA, 312 pages. The Future of Competitive Strategy: Unleashing the Power of Data and Digital Ecosystems. Hardcover Edition – Massachusetts Institute of Technology Press – Result List – MIT Press
12. Barbara Canton, Wayne Erdman, Jeff Irvine et al. Mathematics of Data Management Textbook—12 Student Editions. Paperback Edition published on the 19^th of August 2002, McGraw-Hill Ryerson Publishing, Milton (Ontario), Canada, 676 pages. McGraw-Mill Ryerson Publishing 2002 – Mathematics of Data Management Textbook – 12 Student Editions : Free Download, Borrow, and Streaming : Internet Archive
13. Vijay Govindarajan and Venkat Venkatraman. Fusion Strategy: How Real-Time Data and AI Will Power the Industrial Future. 1^st Hardcover Edition published on the 12^th of March 2024, Havard Business Review (HBR) Press, Boston, Massachusetts, USA, 224 pages. Fusion Strategy: How Real-Time Data and AI Will Power the Industrial Future (E-Book and Mini Masterclass with Vijay Govindarajan) – 1^st Hardcover Edition – Harvard Business Review (HBR) Press
14. Alex Berson and Larry Dubov. Master Data Management and Data Governance: Latest Techniques for Building a Customer-Focused Enterprise Environment. 2^nd Hardcover Edition published on the 6^th of December 2021, McGraw-Hill Osborne Media, New York City, New York, USA, 537 pages. https://www.mhebooklibrary.com/doi/book/10.1036/9780071744591
15. Michael E. Kirshteyn. Data Governance Framework: A Comprehensive Guide to Success. Hardcover Edition published on the 30^th of January 2024, Amazon USA Publishing, Seattle, State of Washington, USA, 277 pages. Data Governance Framework: A Comprehensive Guide to Success. Hardcover Edition. ISBN: 9798877992245: Computer Science Books @ Amazon.com
16. David Plotkin. Data Stewardship: An Actionable Guide to Effective Data Management and Data Governance. 2^nd Paperback Edition published on the 31^st of October 2020, Academic Press—an imprint of Elsevier, Salt Lake City, Utah, USA, 248 pages. Data Stewardship: An Actionable Guide to Effective Data Management and Data Governance – 2nd Paperback Edition | Elsevier Shop
17. Morgan Templar. Get Governed: Building World Class Data Governance Programs. Paperback Edition published on the 13^th of September 2017, Ivory Lady Publishing, 274 pages. Get Governed: Building World Class Data Governance Programs – ISBN: 978-0692951750: Templar, Morgan: Amazon.ca: Books
18. Thomas C. Redman. Getting in Front of Data: Who Does What? 1^st Paperback Edition published on the 13^th of August 2016, Technics Publications, Sedona, Arizona, USA, 190 pages. Getting in Front on Data: Who Does What – 1^st Paperback Edition – Technics Publications
19. Office of the Privacy Commissioner of Canada. OPC Actions and Decisions – Investigations into Businesses. Investigation into Desjardins’ Compliance with PIPEDA Following a Breach of Personal Information Between 2017 and 2019. Published on the 14^th of December 2020. PIPEDA Findings #2020-005: Investigation into Desjardins’ compliance with PIPEDA following a breach of personal information between 2017 and 2019 – Office of the Privacy Commissioner of Canada

Contributions

Special thanks for the financial support of the National Research Council Canada (NRC) and its Industrial Research Assistance Program (IRAP) benefitting innovative SMEs throughout the 10 provinces and 3 territories of Canada.

Newsletter Executive Editor:

Alan Bernardi, SSCP, PMP, Lead Auditor for ISO 27001, ISO 27701 and ISO 42001, B.Sc. Computer Science & Mathematics, McGill University, Canada, Graduate Diploma in Management, McGill University, Canada

Author-Amazon USA, Computer Scientist, Certified Professional Writer & Translator:

Ravi Jay Gunnoo, C.P.W. ISO 24495-1:2023 & C.P.T. ISO 17100:2015, B.Sc. Computer Science & Cybersecurity, McGill University, Canada, B.Sc. & M.A. Professional Translation, University of Montreal, Canada

This content is published under a Creative Commons Attribution (CC BY-NC) license.