Gable Blog | Automated Data Governance
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The increased adoption of AI and machine learning is getting a lot of press lately—for good reason. But, in total, there are quite a few other factors driving organizations to automate their data governance processes.
The shift toward cloud-based data solutions necessitates robust data governance frameworks to manage data across diverse environments. And the need for real-time data governance exponentially grows as organizations seek to respond immediately to changes in data.
Ensuring high data quality is also increasingly essential for organizations to get the reliable analytics and decision-making they need to remain competitive. But as these data needs grow both in scale and complexity, the ability for organizations to track data lineage and metadata management with a high degree of fidelity grows more critical as well.
To add to these issues, we have the growing movements of data democratization and data as a product—to which the benefits of automated data governance are crucial, too.
Therefore, the need for automated governance processes has certainly arrived. So why are some data professionals still relying on manual data governance practices? Well, as it turns out, there are actually some very good reasons.
We’ll explore what’s holding some teams back and look at how data contracts might offer a way forward for most. But first, we’ll break down the advantages automated data governance promises most organizations.
Benefits of automated data governance
Let's explore the common benefits of automated data governance, from internal flow to tangible savings and advantages.
Continuous monitoring and compliance
Automated systems continuously monitor data handling practices. In doing so, they ensure compliance with important regulations (e.g., GDPR, CCPA) around the clock.
Moreover, automated data governance tools create detailed logs and audit trails—facilitating more reliable and, frankly, easier audits.
Increased efficiency and cost savings
When data leaders automate routine governance tasks, it frees up team-member bandwidth, allowing data professionals to focus on higher-value, more strategic opportunities.
In addition to this resource optimization, governance automation further streamlines the data management process, lowering operational costs.
Faster decision-making
Automated governance systems provide real-time data quality checks and governance metrics. Together, this information enables faster and more informed decision-making.
Additionally, these automated processes are designed for growth—scaling easily as the data needs of an organization ebb and flow.
Enhanced data security
Automated data governance also helps data teams manage personnel scaling, enforce strict access controls, and monitor data access patterns.
This reduces the risk of unauthorized access, which can be especially challenging in large organizations. Automated governance helps teams detect data breaches and governance policy violations faster, enabling them to mitigate potential damages.
Support for advanced analytics and AI
As mentioned above, high-quality, well-governed data is mission-critical for advanced analytics and AI initiatives (and the essential insights they increasingly provide).
An emerging concern is also ensuring that organizations' use of AI remains compliant with ethical standards and regulations. By automating data governance processes, organizational leadership gains the assurance that they're supporting responsible AI development.
Competitive advantages
Finally, gaining and maintaining a competitive advantage is always a priority for organizations. However, doing so increasingly requires the fidelity of reliable, well-governed data that manual data governance can struggle to provide.
Data governance automation helps organizations build trust with customers, who need to be increasingly assured their data is handled with professional consideration and care.
Why some data pros haven't gone all-in on automating their governance processes (and how data contracts can help)
So, in the face of this comprehensive collection of potential benefits, why haven’t all data professionals embraced automating their organization’s data governance?
Well, like many practical aspects of data engineering, it can be complicated. There are some very valid issues that engineering teams need to tackle as part of automating their data governance processes. We’ll tough on the seven that are most consequential.
To be clear (because we’re certainly a bit biased), data contracts are not a panacea—solving each and every challenge related to embracing automated data governance. However, as you’ll see, a well-drafted data contract can turn seemingly prohibitive mountains into intrinsically manageable molehills.
1. Cost concerns
To be fair, implementing automated data governance solutions tends to require at least some upfront investments in new software, infrastructure, and potentially new hardware.
With these initial investments come additional needs for maintenance, updates, and costs associated with the integration and scaling of automated systems.
How a data contract can help:
- Drafting a data contract involves clearly defining data expectations and interfaces. This streamlines the organizational integration process as a whole—which, by extension, can reduce the complexities and costs required to establish automated data governance.
- Well-defined data contracts also enable data governance processes to scale. As a result, extensive manual adjustments are then no longer required to adapt governance processes to a growing data environment, further lowering costs.
2. Complexity and integration challenges
It’s also common for organizations to have already invested in legacy systems, which may not easily integrate with newer automated governance tools. To be very fair, the complexities of integrating various data sources and systems to enable data governance automation can be a major undertaking.
As part of these challenges, automated solutions might require extensive customization to fit the specific needs of a given organization, potentially consuming time and being complicated in their own regard.
How a data contract can help:
- The clarity data contract drafting brings to data quality definitions and expectations facilitates easier integration with existing systems. Once in place, they also promote standardization across data sources and systems, making it easier for teams to integrate and manage data from diverse origins.
- Teams can further simplify the integration process by implementing data contracts in a modular fashion, starting with critical data flows and gradually expanding.
3. Lack of expertise and resources
It takes specialized skills in data management, data science, and IT to implement and manage automated data governance effectively. Not all organizations have that specialized expertise in-house.
Alternatively, organizations (smaller organizations in particular) may lack the resources to dedicate to a substantial overhaul of their data governance processes.
How a data contract can help:
- One of the many inherently democratizing aspects of data contracts is how they encapsulate complex governance rules and requirements into manageable components. Doing so makes it easier for teams with limited expertise to implement and maintain organizational data.
- As for the implementation of data contracts themselves, vendors like Gable.ai make it a point to offer support, training, and resources to help organizations implement their contracts effectively.
4. Perceived risks and uncertainty
Fear of the unknown: Some organizations are rightly concerned about security implications regarding automated systems, especially governance tools that may involve the cloud.
We say “rightly” here because data teams in every organization need to ensure they thoroughly understand new and emerging technologies, how they'll retain control of valuable and often personal information, whether or not they’ll become too dependent on automation, and/or how new tools may contribute to system failures or downtime.
How a data contract can help:
- In these cases, organizations benefit from the proven frameworks for managing data governance tasks that data contracts provide.
- Along with the reduced uncertainty and perceived risks such frameworks provide, data contracts enhance data security and compliance by clearly defining data access and usage policies.
- Furthermore, data contracts that offer automated enforcement ensure consistent application of governance policies, reducing the risk of human error.
5. Change management and organizational resistance
Even super-progressive people can be a little resistant to change. So, unsurprisingly, employees accustomed to manual processes can be a bit resistant to substantial changes (like completely automating data governance processes). This resistance often stems from understandable sources: fear of job loss, change in routine, or lack of understanding of the new system's benefits.
If organizational resistance isn’t an issue, data leads still need to ensure that the training required to implement data governance automation doesn't become a roadblock in itself.
How a data contract can help:
- First off, data contracts demonstrate clear benefits quickly. When error rates drop and data quality quickly improves, stakeholder buy-in for further changes and improvements gets easier to maintain.
- By defining roles, responsibilities, and expectations, data contracts can also help alleviate fears about job loss or how changes in routine will and will not affect individual employees.
- Moreover, the consistent data handling practices that contracts establish and enforce across organizations ultimately make it easier for employees to adapt to (and learn) new systems.
6. Regulatory and compliance hesitation
Some industries have more stringent regulatory requirements than others. Organizations in these industries may be wary of adopting new technologies without clear guidance on compliance.
Automated systems in these organizations often must be configured precisely to ensure compliance, as mistakes can lead to substantial penalties.
How a data contract can help:
- By nature, the structured framework that data contracts enforce explicitly defines how data should be handled in compliance with specific regulations. This clear guidance ensures that all automated systems (including those handling governance processes) are configured precisely to meet regulatory requirements.
- In addition to forming a centralized point of control for keeping automated systems compliant, contracts enable the implementation of fine-grained data controls and data usage policies that can adapt as regulatory landscapes evolve.
7. Short-term thinking related to existing manual processes
“If it ain't broke, why automate it?” Certainly, some organizations are doing just fine right now, operating with entirely manual data governance processes.
Additionally, organizational leadership focused on short-term ROI may struggle to see theoretical upsides in these situations, especially when framed against sunk costs and established workflows.
How a data contract can help:
- In business, it can be prohibitive to argue against ROI in general, whether short- or long-term. Instead, quantify how leveraging data contracts to define data expectations, quality standards, and usage guidelines will enhance ROI by marshaling consistent, high-quality data over time.
- As organizations grow and data volumes increase, manual processes will sooner or later prove untenable. At this point, data contracts will already demonstrate the value scalable frameworks have within the organization, setting the stage for how automated data governance will further these longer-term benefits.
Enable the enablement of automated data governance
Automated data governance offers significant advantages, including enhanced compliance, improved efficiency, cost savings, and better support for advanced analytics and AI. Despite these exceptional advantages, though, challenges such as budget, complexity, and organizational resistance remain. Data contracts present a viable solution to mitigate these issues.
Organizations looking to stay competitive in today’s data-driven world should consider starting their journey toward automated data governance by assessing their current capabilities, investing in the necessary tools and training, and gradually integrating automated processes. By doing so, they can ensure their data governance frameworks are robust, scalable, and ready to meet future demands.
Chad Sanderson
August 1, 2024