“Data initiatives never live up to their full potential without appropriate governance behind [them].”
This quote, from a senior data strategist interviewed in the new Best Practices Report on Modern Data Governance from TDWI, encompasses precisely why organizations should be prioritizing a data governance framework. Yet, just 38% of report respondents have ever created or enforced data governance policies by serving on a data governance board — and of those, two-thirds say their data governance program needs to be modernized. As organizations move to the cloud and accelerate user adoption, data access governance strategies must also undergo a modernization process.
Why are we sacrificing data-driven results simply due to weak or nonexistent data governance?
According to TDWI’s report, most organizations still face substantial barriers when trying to implement or improve their data governance strategies. From the data sets to the teams governing and using them, challenges abound for organizations aiming to operationalize data for analytics — particularly sensitive data.
What is the current state of data governance?
Organizations in every industry implement data governance frameworks with the goal of maximizing their datas’ value. By establishing a set of policies, procedures, processes, and best practices for securing, managing, and utilizing data, data teams are able to efficiently operationalize even the most sensitive data so that it can be used to derive data-driven insights — insights that can be significant competitive advantages in today’s marketplace.
Still, TDWI’s research shows that although 84% of organizations consider data governance “extremely important,” few have actually created and enforced data governance policies and nearly all see modernizing their data governance program — or what they have of it — as an opportunity. So, despite the many success stories demonstrating the value of strong data governance frameworks and data access governance strategies, taking the steps to move from concept to implementation remains a challenge.
Why is modernizing data governance challenging?
TDWI’s research spells out a range of barriers to successful data governance program modernization. From scenarios that hinder adaptability — like large-scale data sharing, evolving regulatory requirements, and adoption of multiple cloud data platforms — to people that may interfere with the process — such as employees who do not understand compliant data use or a siloed data governance board — it’s clear that organizations don’t struggle with modernizing data governance programs for a single reason. This creates a ripple effect that impacts and complicates data access governance.
Yet, if data engineering and data governance teams are unable to overcome challenges like enabling self-service data access, maintaining adherence to policies, understanding policies, or aligning on approval workflows, how can they make data secure and accessible? Consequently, if it takes months to access data, how much value does it really provide?
When faced with these barriers, it’s important for leaders who task data teams with data-driven initiatives to ask themselves if the time and energy spent on establishing processes to overcome these challenges is worth the unique, proprietary insights they stand to unlock from their data. In almost all cases, the answer is yes.
What should data teams do to modernize data governance?
Given the rate at which sensitive data and advanced machine learning, AI, and analytics technologies are becoming available, organizations looking to operationalize sensitive data in a secure and timely manner have no choice but to modernize their data governance and data access control strategies and frameworks.
TDWI’s report spells out 12 actionable best practices for modernizing a data governance program. Among them is leveraging dedicated data platforms that automate policy enforcement to enable cross-platform scalability, efficiency, and compliance. The report specifies:
“TDWI continues to be surprised that so few vendors within the software marketplace offer applications specifically for data governance (39%). This is only one of the few areas in the software market where vendor supply has not caught up to user demand…. To “future-proof” a data ecosystem and enable secure data use at scale, organizations should look for [data governance] tools that automate sensitive data discovery, dynamic policy enforcement, and data usage monitoring and auditing. Ideally, [data governance] tools should operate consistently across all data platforms — both modern and legacy, cloud-based and on premises….[Data governance] is not modern or complete unless application and tool security are complemented by data security.”
Immuta enables data teams to automate data access governance for modern, cloud-native analytics platforms. With more than half of organizations planning to adopt two or more cloud data platforms within the next two years, modernizing data governance, and by extension data access governance, will require an automated solution that enables consistent cross-platform data protection.
For data teams looking to modernize their approach to data access governance, Immuta provides:
- A centralized, active data catalog from which to apply privacy policies uniformly across cloud data platforms.
- Simple data access controls written in plain English that stakeholders of any technical skill level can understand.
- Attribute-based access controls that automatically apply strong data security with every query based on dynamic attributes, enabling self-service data access to only authorized users.
- Sensitive data discovery that detects, classifies, and tags sensitive data across platforms, reducing the need for manual processes that increase risk.
- Consistent, dynamic data masking that uses cross-platform policies and advanced privacy enhancing technologies (PETs) to standardize privacy controls and eliminate the need to author policies more than once.
See the full list of best practices and learn what else TDWI’s research uncovered by downloading TDWI’s Best Practices Report on Modern Data Governance.