"Secure Your Data: Shift Left Data Governance Now

Mastering proactive data governance is necessary in an era of daily data breaches, stringent privacy laws, and AI-driven decisions. Let’s explore why now is the time to ‘shift left’ our data governance strategy.

Understanding Shift Left Data Governance

Imagine preventing car accidents before they happen rather than just cushioning the impact, which is what shift left data governance aims to do with your data. It’s a proactive approach, focusing on implementing data governance early in the data lifecycle. It is analogous to embedding safety features in a vehicle’s design rather than adding them after production.

Aligning with Global Standards as a Best Practice

In data governance, aligning with established global standards is often viewed as only a means to achieve compliance; it’s also about embracing best practices that signal the maturity of your data management program. Several essential standards and frameworks underscore the importance of early data governance and robust data classification:

• ISO/IEC 27001 emphasizes managing information security risks and supporting early data governance by advocating for identifying, classifying, and managing these risks from the beginning.
• GDPR mandates a thorough understanding of data (data inventory) and its nature (data classification), requiring protective measures to be embedded early in the data processing cycle.
• NIST Framework highlights the identification and classification of data as essential steps in cybersecurity risk management.
• COBIT recommends early data governance to ensure data integrity, confidentiality, and availability.
• DAMA-DMBOK explicitly emphasizes early data governance, advocating for a data inventory to manage data assets throughout their lifecycle and classifying data for appropriate management and use.
• CMMI suggests that higher maturity levels in organizations are associated with effective data governance, including understanding data assets and the need for data classification.
• ITIL supports having a detailed understanding of data assets and the need for data classification to provide effective IT services that align with business needs.
• USA Federal Law Sarbanes-Oxley Act (SOX) Though specific to financial reporting, SOX indirectly mandates stringent data governance practices, including detailed financial data inventory and classification.

These standards collectively advocate for a proactive approach to data governance, emphasizing the importance of establishing data governance early in the data lifecycle.

Why Shift Left Data Governance is a Game-Changer

• Proactive Data Protection: By integrating governance early, businesses are positioned to preemptively safeguard data, addressing potential issues immediately.
• Regulatory Compliance Made Easy: In a world of GDPR and CCPA, this approach ensures compliance from the get-go, eliminating last-minute scrambles.
• Enhanced Data Quality: Early governance leads to cleaner, more accurate data, paving the way for more informed business decisions.

Tangible Benefits of This Proactive Strategy

• Early Detection and Resolution of Data Issues: Implementing shift left data governance, allows organizations to identify and address data anomalies as they occur and minimizes the ripple effects of data inaccuracies across business operations, reducing the time and resources spent on rectifying data-related problems. For example, in customer data management, early error detection can prevent issues in customer sales or service delivery, directly impacting customer satisfaction and retention.
• Seamless Compliance: With the increasing complexity of data regulations like GDPR and CCPA, a shift left approach keeps organizations ahead of legal requirements. By integrating compliance measures at the data entry point, businesses can avoid the extensive efforts often required for retrofitting compliance into established data systems. This approach reduces the risk of non-compliance and associated penalties and streamlines the audit processes, making them more efficient and less disruptive.
• Minimized Data Breaches: By knowing exactly where data is stored and processing it with appropriate security measures from the onset, based on its classification, organizations can effectively guardrail against the risk of a data breach. A proactive security posture is central to protecting sensitive and personal data, maintaining customer trust, and protecting the organization’s reputation.
• Data-Driven Business Growth: High-quality, well-governed data is a cornerstone of informed decision-making and strategic business growth. A shift-left approach secures accurate, consistent, and reliable data from the outset, forming a solid base for analytics and business intelligence. This leads to precise forecasting, enhanced product development, and targeted marketing strategies, fueling business growth. Earlier access to contextually valid data can help identify emerging market trends, enabling businesses to capitalize on new opportunities more rapidly than competitors.

Enhanced Key Features of an Effective Data Governance Platform

An ideal platform for shift-left governance are capabilities designed to streamline and secure your data management process. It should include:

• Granular Access Controls enable precise management of who can view, modify, and distribute data. Think of it as giving out specific keys to different rooms in a data mansion, ensuring only authorized personnel can access sensitive information.
• Clear Data Lineage: Representing a transparent journey map of your data, tracking its ‘life story’ from origin to endpoint, revealing where it has traveled, how various processes have altered it, and who has interacted with it. This ‘chain of trust’ clarity is invaluable for maintaining accurate audit trails, ensuring compliance, and thoroughly understanding your data’s transformations.
• Auto-Documentation and Smart Suggestions: Automated guidance for data classification saves time and resources while improving data accuracy and usability.
• Real-Time Alerts: Provide instant notifications about discrepancies or anomalies in your data landscape. They allow for swift responses, mitigating potential issues before they become significant problems.
• Tools for Data Quality Maintenance: Continous monitoring, discovery, classification and quality maintenance tools work to ensure your data remains clean, accurate, and reliable are essential for informed decision-making and operational efficiency.

The Shift Left Data Governance Journey 

• Embarking on the shift left journey in data governance involves strategic steps: Establishing a comprehensive data governance framework is analogous to building the architecture for your data management house – it must be sturdy, well-planned, and adaptable to future expansions or renovations.
• Implement a Data Catalog: This is like setting up a central library or database where all your data assets are cataloged and easily accessible. Centralizing your data assets not only streamlines management but also aids in maintaining consistency and accuracy across the organization.
• Begin with a Pilot Project: Start with a manageable, smaller-scale project to test and refine your strategy. This approach allows you to learn, adapt, and demonstrate the value of shift-left data governance without overwhelming your team or resources.
• Scale Up Gradually: Like nurturing a plant, expand your strategy across the organization systematically and thoughtfully. This measured approach ensures that each area of your business can adapt to and fully integrate the new governance practices without disrupting existing operations.

In conclusion, shift left data governance emerges as a strategy and an essential defense in an increasingly data-centric world. In an era dominated by AI and digital transformation, the necessity of staying proactive is undeniable. It’s about more than whether we should adopt such practices but how swiftly we can integrate them to ensure compliance, secure data integrity, and harness the full potential of high-quality data. Embracing a shift-left approach is a pivotal step towards thriving in a landscape where data is the currency of success. Today, data governance is the cornerstone of business resilience and innovation.

References

1. ISO/IEC 27001: International Organization for Standardization. (2013). ISO/IEC 27001:2019 Information technology — Security techniques — Information security management systems — Requirements. ISO. https://www.iso.org/standard/27001
2. General Data Protection Regulation (GDPR): European Parliament and Council of the European Union. (2016). Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on protecting natural persons concerning the processing of personal data and the free movement of such data (General Data Protection Regulation). Official Journal of the European Union. https://eur-lex.europa.eu/eli/reg/2016/679/oj
3. NIST Framework: National Institute of Standards and Technology. (2018). Framework for Improving Critical Infrastructure Cybersecurity (Version 1.1). NIST. https://nvlpubs.nist.gov/nistpubs/CSWP/NIST.CSWP.04162018.pdf
4. COBIT: ISACA. (2018). COBIT 2019 Framework: Introduction and Methodology. ISACA. https://www.isaca.org/resources/cobit
5. DAMA-DMBOK: Data Management Association International. (2017). DAMA Guide to the Data Management Body of Knowledge (DAMA-DMBOK Guide). Technics Publications.
6. CMMI: CMMI Institute. (2018). CMMI for Development, Version 2.0. CMMI Institute. https://cmmiinstitute.com/cmmi/dev
7. ITIL: AXELOS. (2019). ITIL Foundation: ITIL 4 Edition. TSO (The Stationery Office).
8. Sarbanes-Oxley Act (SOX): United States Congress. (2002). Sarbanes-Oxley Act of 2002. Public Law 107-204. https://www.congress.gov/bill/107th-congress/house-bill/3763
9. IBM. IBM Cloud Pak for Data [Software]. Available from https://www.ibm.com/products/cloud-pak-for-data
10. IBM. (n.d.). IBM Security Discover and Classify. https://www.ibm.com/products/ibm-security-discover-and-classify