A data governance tool is a tool that helps organizations in creating and maintaining a structured set of policies, procedures, and protocols that manages an organization’s data in storing, using, and controlling.
The main aim behind the data governance tool is to create policies that include ownership roles, delegations, and data policies, which passes through the decision of stakeholders and different department of the organization. Data governance enables consistent and confident decision-making based on trustworthy reports of data, analytics, and assets.
STEPS IN DEVELOPING DATA GOVERNANCE TOOL FRAMEWORK
- Figuring out the mission; address the marketing goals, budget allocation, and define your mission statement at this stage.
- Defining the success metrics; determine and set your metrics before the creation of the framework.
- Identifying data assets; identify various access places where the data is getting entered or is leaving. Also, having detailed information about the data itself would be quite handy at this step.
- Creating data rules and definitions; this step involves getting inputs from employees from various departments, such as top-level managers and executives, sales team, legal team, IT administrators and develops team, etc., To make new rules and policies.
- Assigning data rights and ownership; once the rules are created, the next step would be to assign the data asset to a specified owner. This owner has control and ownership over the piece; therefore, he/she must go through it as they will be accountable for any further changes in the given framework.
- Formulating control mechanisms; control mechanisms create, maintain, and delete various data assets to ensure consistency across the system.
- Creating roles; at this step, data access and control get allocated among different employees concerning their roles in the organization.
- Creating knowledge transfer and training programs; once the roles and responsibilities associated with the rules are provided, and then the training of each department from customer-facing teams to programming teams must be conducted regarding data governance policies to ensure the proper functioning of the data standards.
TOP 5 DATA GOVERNANCE TOOLS
1. ASG TECHNOLOGIES; ASG technologies’ enterprise data intelligence (ASG DI) platform for meta-driven data that provides a 360-degree view of the entire data. Its main features include data cataloging, data management, data ownership and stewardship capabilities, self-service, visualization, data lineage, compliance audit readiness, and so on. Its DI tool interface has a learning curve, and its deployment isn’t easy with adverse climate conditions. Its price is quite reasonable.
2. ATACCAMA; is a self-driven data management and governance platform. It renders ai-driven automated capabilities to make the work of data management smooth and easy to operate. Its main features include data cataloguing, data management, metadata management, data policy management, flexibility and compatibility, and so on. The only adverse complicated issue with this tool is that it lacks an intuitive visualization department, but it is expected to improve soon with better features. The company offers a month free trial, and its price is available on request.
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3. COLLIBRA; is an enterprise-directed data governance platform known for its automated data governance and management provider. Its main features include data cataloguing, meta management, visualization, data lineage, data ownership, stewardship capabilities, etc.; Users often report flexibility and neatly customized services. Deployment is reported to be difficult, but technical support is always available. The company offers a free demo, and its price is available on request.
4. ERWIN BY QUEST SOFTWARE; just like COLLIBRA, Erwin by quest software program offers almost the same collection of products in use that can drive data governance frameworks. It provides Erwin data modeller, data intelligence, data catalogue, smart data connectors, and data literacy. It includes the same features such as compliance audit readiness, data policy management, visualization, data cataloguing, data lineage, and self-service. Customers and users have reported that its interface is not that intuitive. This tool is very affordable, with a price available on request. The company also offers a free trial.
5. IBM; this is the most established useable tool in the market. It offers the flexibility of supporting various data governance frameworks. Its main features include data cataloguing, data management, self-service, visualization, data lineage, business glossary, flexibility and compatibility, PHI and GDPR compliance audit readiness, and data management policy. Its catalogue is easy to use and navigate through, whereas there is some difficulty in integrating third-party solutions. For individual deployment, the prices may vary.