In this article we will explore what data governance tools are, and their importance in helping companies leverage data as a strategic asset. We will also cover the key capabilities organizations require within data governance tools to effectively manage responsible data use. These capabilities can also help derive value from enterprise applications, while lowering risk exposure through data stewardship.
A Definition of Data Governance Tools and Their Purpose
Data governance tools are primarily software solutions designed to administer, monitor, control and report on the entire lifecycle of data. This would be from creation or acquisition through curation to finally archival or deletion. These tools help organizations establish and enforce policy-based principles. They enable standards and practices to be implemented that help ensure data is reliable and consistent. Data governance tools allow data stakeholders – both business and technical – to collaborate in order to orchestrate processes and procedures. These may include data management, data quality, data mastering, security, and privacy that aligns with enterprise policy compliance objectives and goals.
The purpose of data governance tools is to help implement transparent, reliable and common standards for data handling processes and procedures throughout your organization. The tools help data producers and consumers achieve and maintain responsible use of data. These tools also help automate and streamline efficient data governance processes and procedures. They can establish a framework to give greater context to data, such as where it originated and whether it is fit for business use. They can help put in place user access controls that determine how data can be exposed for use. This can allow for a balance of data utility with protection. These access controls can further enable organizations to identify and resolve data-related issues quickly to improve data quality and reliability to increase data trustworthiness. Data governance tools leverage AI and ML to provide automation to effectively counter the complexities of managing large volumes of data. These complexities include diverse data types, disparate data sources and ever-changing regulatory policies that impact appropriate uses. With the help of data governance tools, data stewards and data analysts can inventory and classify large-scale data volumes. Data quality and protection status can be monitored effectively. Data lineage can be tracked to understand movement and impact and to make data meaningful through insights with transparency. This helps determine security and access control expectations are compliant with policies.
Why Does Data Governance Matter? Transforming From Data Chaos to Data Intelligence
An unprecedented amount of data is captured and generated by businesses every day. The ability to handle large volumes of high velocity, high variety data from an increasingly complex combination of sources presents a unique challenge for organizations. To this end, enterprise data governance is one of the most critical business functions that CDOs and other stakeholders are investing in. With reliable data governance, companies can manage the data deluge and transform data into a valuable strategic asset while minimizing unnecessary risks. It is no surprise that data governance strategies have unwavering attention from CDOs and data leaders across the globe to maximize the ROI of this valuable asset.
A strong data governance strategy that builds a foundation of trusted data can establish robust data management practices that scale for the future. A sound approach can enhance data quality, mitigate risks, help ensure regulatory compliance and maximize the value of data. Without it, regulatory fines and penalties, brand degradation, customer churn and financial losses are just a few of the consequences. Data governance tools are fundamental in helping operationalize the data governance strategy for organizations. The right tools can help unlock data intelligence. These tools help to deliver products and services more quickly from insights that meet customer needs better. They can also help make the business stronger through accelerating productivity with streamlined access to business-critical data.
What Are the Key Capabilities Modern Data Governance Tools Must Have?
Data governance tools have evolved significantly. Meeting regulatory risk and compliance policies for trust assurance were the predominant focus a few years ago. Today, data governance tools play a pivotal role in helping to ensure enterprise data is reliable, accessible and utilized efficiently. To support increasingly diverse business needs and manage data across all parts of its lifecycle, data governance tools must offer a comprehensive suite of capabilities to empower data users.
Below are the critical capabilities that data governance tools for modern enterprises must deliver on:
- Data Cataloging
Data cataloging allows organizations to create a detailed, organized inventory of data assets across an enterprise ecosystem. Based on metadata-driven intelligence, data cataloging helps you to identify and classify data. Organizations can then find, understand and manage their data assets across diverse data sources, types and formats. You cannot manage data if you do not know what it is, where it is located and how it can be used effectively to achieve business outcomes and generate value. Thus, data cataloging provides the starting point for data discovery, understanding and improving data quality. Data cataloging makes data accessible to data consumers across lines of business for analytics and intelligent decision making.
- Data Lineage
Data lineage capabilities allow organizations to track the flow of data from its source to its target destination. Without complete visibility into where data originated, the processes involved in transforming it and knowing its delivery end points, it is difficult for data users to assess its quality and trustworthiness. With the increase in complexity of data infrastructures, such as cloud, multi-cloud and hybrid, monitoring the movement of data across the organization is critical to ensure compliance with regulations, data privacy and data security standards.
- Data Quality
Tools that address data quality help organizations improve the accuracy, completeness and consistency of their data. They accomplish these objectives by identifying and resolving data-related issues. Inconsistent data can lead to erroneous analytics downstream and misinformed decision-making. Therefore, it is important that data governance tools can implement data quality rules, processes and procedures centrally to capture and remediate data anomalies early. Through data profiling, IT and data users can easily assess the quality of data sets and deploy data cleansing and data enrichment processes. The results can lead to higher confidence in decision-making and increased operational efficiency.
- Data Mastering
Data mastering capabilities enable organizations to create a single, authoritative view of their data by combining and reconciling data from various sources. As data continues to proliferate, evolve and be utilized across the organization, ensuring a single source of truth becomes fundamental to its accuracy and reliability. With data matching, merging and consolidation capabilities, data mastering improves data accuracy and consistency. It reduces data redundancy and helps enable better decision-making by providing an accurate view of data.
Data security and privacy capabilities are a must-have for every organization to protect data for responsible use. Tools help govern data to avoid unauthorized access, misuse and theft. These tools provide data risk remediation, such as encryption and data masking capabilities, and enable access controls for safe data sharing. Their purpose is to help ensure compliance with policies and regulatory mandates. Through the enforcement of controls that balance data utility with protection, these tools help manage exposure of sensitive data and deliver customer trust assurance.
6 Factors to Consider When Choosing the Right Data Governance Tools
- Does the data governance tool provide scalability and extensibility?
- Can the data governance tool integrate with existing systems?
- Is the data governance tool easy to implement and use?
- Is the data governance tool customizable?
- What kind of vendor support comes with the data governance tool?
- What is the actual cost and procurement process of the data governance tool?
As data volume and complexity continue to increase, your chosen tool should be able to handle growing demands of additional use cases, more data consumers, and future requirements without requiring major architectural and system overhauls. Pro-tip: Evaluate a tool’s ability to scale and extend its functionality to adapt to evolving data governance needs. Cloud-native data governance tools help organizations benefit from the inherent cloud-based flexibility, agility, resiliency and cost effectiveness through achieving economies of scale.
Not only are data volumes increasing, but so is the diversity of data and the technology required to manage it. Hence, it is important for data governance tools to be vendor agnostic and provide connectivity to a wide range of infrastructure and technology providers. Data governance tools should integrate seamlessly with existing systems to ensure a smooth transition and prevent disruption to existing workflows. Pro-tip: Assess the tool’s ability to connect with the widest variety of data sources and target systems, as well as compatibility with your existing data management tools and platforms.
In other words, think about time to value, which is critical when implementing data governance tools. Tools that do not require complex, lengthy implementations, and have minimal disruptions to daily operations, are key. Additionally, with data literacy increasing across the organization, more non-technical users might be expected to be familiar with data operations. Hence, data governance tools that are business-user friendly will see greater adoption rate. Pro-tip: Evaluate the tool’s usability, user interface and onboarding processes to ensure the quickest time to value and appropriateness to solve modern use cases, such as analytic insights and customer experience programs.
As your data governance maturity increases, you are likely to encounter more complex use cases. To add to the complexity, dynamic demands of the market and ever-changing regulatory requirements pertaining to use of data makes a one-size-fit-all approach to governance obsolete. Say you have unique data governance requirements, and the chosen tool is not flexible enough to meet your needs. That will just add to your technical debt. Pro-tip: Evaluate the tool’s ability to customize according to workflows, perform metadata management, and establish custom data quality rules and policies to meet specific requirements. Get full insights into customizability with details that are relevant to your organization as use cases are expected to evolve.
Vendor support is a critical factor to consider in any type of extensive and impactful technology purchase. Organizations must evaluate the vendor’s expertise, support and response time to ensure timely and effective issue resolution. Pro-tip: Assess the vendor’s professional services, including training, consulting and technical assistance to ensure that the chosen tool will have the necessary support your organization requires. A single vendor solution provides advantages around procurement, consistent service level agreements, and flexibility to scale, while minimizing integration hurdles.
Organizations should evaluate the tool’s cost relative to its features and functionality and consider the total cost of ownership. Pro-tip: Assess the procurement process, including licensing models, contracts and negotiation processes to ensure a fair and transparent agreement (and no hidden costs). Factor for the future. A consumption-based pricing model may serve well if and when you plan to bring more data into the fold by enabling you to expand as needed while organizational needs grow over time.
Data Governance Tools: Sturdy Reinforcements to Help Bring Your Data to Life
In today’s data-driven world, companies cannot afford to neglect their data governance strategies. Data governance tools are sturdy reinforcements of policies, processes and procedures that need to be enforced to balance data utility and trust assurance that can help companies bring their data to life with confidence. By implementing the right tools, companies can ensure that their data is accurate, reliable and secure. Good data governance practices and data stewardship can foster a culture of trust in data and enable faster decision-making and unlock new opportunities for growth.
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