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Plan Your Firm’s Data Governance Framework: New Trends Await in 2024!

2023 was indeed an insightful year for data owners and data processors. Effective data governance guarantees data integrity and drives better decision-making and business outcomes. During December 2023, the monthly data analysis from a global IT governance research study found nearly 1,351 publicly disclosed security incidents. They also found 2,241,916,765 records breached. By January 2024, research had discovered the ‘mother of data breaches’ with 26 billion data records that were exposed! The round-up of the breach incidents sends out a strong message to Chief Data Officers (CDOs) and data governance policy enforcement teams to reevaluate technologies and organizational measures. Therefore, it is never too early to prepare for the unknown by exploring the latest predictions to build a watertight data governance framework this year.  

If you still need to decide about making the data governance framework a real deal for your organization’s compliance, let’s brush up on some basics.  

Why Data Governance Framework Important for Your Firm? 

Any data that flows into the enterprise systems and applications to the cloud data warehouse or analytics tools, its usage, access, storage, and security must align with the internal data standards and data privacy laws like the California Consumer Privacy ACT (CCPA). An organization’s CDO, the data governance team of a data governance lead, the company executives, IT teams, and data owners work together to build, implement, and enforce data governance procedures. The governance framework is shared internally with all the stakeholders.   

The data governance framework includes activities and procedures like building a data catalog, data mapping, and maintaining a record of standard jargon used across the business to aid with compliance. Many cutting-edge technology platforms and tools are available to automate governance workflows. Platforms such as the OpenPages Data Privacy Management (DPM) solution enable the automation of private data reporting to improve accuracy and reduce audit time. It increases risk reporting by leveraging natural language processing (NLP) that helps translate data from over 50 languages. The solution empowers data teams and scientists to trust the compliance efforts by bringing a more compliance-centric focus to the data governance practices. Governance tools for building governance policies and creating data catalogs are used along with solutions for metadata and master data management (MDM).  

The primary reason for conducting data governance is to ensure that critical data does not end up in silos within individual data processing systems or data architectures. The data governance framework allows for solid data collection and processing hygiene by preventing data errors or misuse of sensitive data like customers’ personally identifiable information (PII). Ultimately, this team collaboration effort leads to improved data quality, and timely data access by data analysts and teams. It enables continuous monitoring to ensure data consistency and compliance with the latest privacy mandates.  

Eleven Predictions of 2024 for Creating Effective Data Governance Framework

With AI and GenAI growing to unprecedented levels, data governance from the organizational and regulatory standpoint will continue to evolve. It will redefine how businesses will treat their data and compliance. Here are the most awaited data governance shifts to expect in the days ahead: 

  1. Shift Left Principle in Data Governance: Shift left in data governance and data security involves implementing superior governance and security features available on the cloud data warehouse to protect sensitive data and its integrity throughout the journey. It helps detect and address any issue early, enabling data teams to apply proper data governance and protection approaches. This year, all companies dealing with PII or its processing will prioritize a shift left approach to reduce the risk of exposure before it reaches the cloud data warehouse.  
  2. Regulatory Actions Against AI/ML and LLM-based Decisions: Recently, the uproar over biased and unethical models supporting AI decisions called for stringent regulatory actions for model governance to foster ethical and equitable use of AI applications. Last year, the U.S. Consumer Finance Protection Bureau (CFPB), the Federal Trade Commission (FTC), the Equal Employment Opportunity Commission (EEOC), and the DOJ Civil Rights Division collectively issued a statement to protect against bias in automated and AI systems. Moreover, the insider threats of misuse of AI and LLMs loom large, driving organizations to implement robust data governance frameworks for secure data access controls, security audits, employee training, anonymization, and encryption practices. Regulators will continue to be the watchdogs using the existing enforcement actions.  
  3. Slow GenAI Adoption by Federal Agencies: To accelerate AI tool adoption by the U.S. government and manage associated risks, the U.S. Office of Management and Budget issued a new draft policy in November last year. OMB proposed guidance to the federal agencies based on three tenets: strengthening AI governance, advancing responsible AI, and managing risks from using AI. Already, 700 ways of using AI have been identified and the number is expected to increase. However, given the scope of technological upgrades needed to support mainstream AI and GenAI use cases along with data governance efforts, the pace of adoption will be slow but gradual.  
  4. Move from On-prem to Cloud: Cloud-based workloads make up 75% of workloads for one-fifth of organizations, according to a study by Fortinet. Last we checked, about 2.5 quintillion bytes of data generated daily. It is mindboggling to find that approximately 1,000 exabytes of data are stored on-prem, and businesses can lower the total cost of ownership (TCO) by 40% by migrating to the public cloud. The native data security features available in cloud environments are beneficial in mitigating risks, scaling data governance efforts, and enabling data access and team collaboration.  
  5. Quitting Legacy Tools and Applications: A high-priority item on the checklist is to quit legacy tools or modernize them to improve their integration with modern software, performance, functionality, and data security. According to IDC, most of the legacy applications will likely get a modern upgrade in 2024 and 65% will leverage cloud services to keep up with the latest industry requirements and data security standards.  
  6. Decentralized Data Governance: Unlike having a central authority to define and manage compliance with data policies and standards, decentralized data governance models will soon help organizations decide how they independently wish to treat data assets. This approach helps custom-build governance practices per business goals and other requirements. It enables flexibility, innovation, and collaboration among business teams and stakeholders.  
  7. Reevaluation of Messaging and Communication Channels: As a part of the new data governance plans for 2024, firms are likely to consider the evaluation of messaging platforms and off-channel communication tools used by their teams to conduct business. In the financial services sector alone, the Commodities Future Trading Commissions (CFTC) and the Securities and Exchange Commission (SEC) imposed a penalty totaling $2.8 billion for firms and associates for using unapproved channels, increasing their privacy and cybersecurity risks. Those communication channels include personal text messages and ephemeral messaging apps to regulate risks.  
  8. Data Warehouses with Data Lakes and Data Catalogs: Earlier data governance practices and frameworks included data stored in traditional data warehouses and relational databases. With the advent of data lakes and data catalogs, organizations will leverage and combine the two for building and governing diverse data sets. Data lakes are storage environments with large amounts of big data retained in their native form until they are used for analytics applications. It is built on a flat architecture that allows data scientists, analysts, and engineers to access data from a central location for analysis. The data in data lakes are more structured and tagged using metadata tags, making it easy to identify. Data catalogs are an inventory of data assets for data discovery and easy access. Data lake governance keeps it in control and ensures ethical and secure use of data. In 2024, firms will witness an uptick in combining data warehouses with data lakes.  
  9. Metadata Management: As more companies focus on being data-driven, metadata management will continue to play an integral role in improving the data quality and relevance. It includes best practices and the use of technologies to understand data relationships, track its usage, discover data, and monitor potential data usage risks across the enterprise. In 2024, metadata management will be a crucial aspect of data governance practices for most firms.  
  10. Heightened Focus on Data Ethics: The ethical implications of AI and ML platforms and their data analyses have been the topic of concern for the regulatory and consumer communities. To establish trust and commitment towards ethical and fair use of data, businesses will implement data governance strategies and data privacy policies that comply with the General Data Protection Regulation (GDPR) and CCPA measures. The latest mandates emphasize building data transparency and accountability on processing measures. 
  11. Data Democratization: Data democratization trend aims to make data more accessible to users in the organization including non-technical users without going through long request loop across the data team. Data democratization prevents data silos and makes them readily available for analysis and decision-making. Data governance policies will regulate the users and their activities across the enterprise to ensure compliance and security.  

Your Data Leaders Need iTech GRC’s OpenPages Experts! 

Every organization will have a nuanced approach to data privacy management and building a solid data governance framework in 2024. We cannot stop short by looking at a handful of trends. The outlook of the organizations, consumers, and governments shifts with active events and catalysts that dynamically shape data security. Experts at iTech GRC understand what it takes to stay ahead in this field using OpenPages Data Privacy Management, IT Governance, Regulatory Compliance Management, and more.  

If you are interested in knowing how we can elevate your organization’s data governance using OpenPages products, let’s connect now! 

 

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