3 Ways to Implement Data Governance in Your Company

Navigating the various ways of implementing data governance can be a challenge. This statement is especially true for those new to the data science software field or who have recently experienced unprecedented growth within their organization. Thankfully, several resources are at your disposal to help you understand the role of data governance in your business process. Industry leaders in the data science software field like TIBCO host a number of informational resources on their websites for students and business owners alike.

Data governance bridges the gap between strategic business processes and informational policy. While it is supported by software technology, the term data governance actually refers to implementing and enforcing policies associated with data storage, generation, usage, and maintenance.

Utilizing effective data governance strategies can enable your organization to pull essential data from different systems and rationalize it to achieve consistency and insight. Where there is consistency and insightfulness, there is innovation and growth.

1. Examine your current data practices.

The first step to effective data governance is knowing how to use it and why you need it. It sounds simple, but it requires a bit of introspection regarding your current business processes and overall workflow. The best practice is to target specific aspects of your existing data governance model that your organization can work towards improving.

Prioritize these facets of your workflow when you are researching data governance software and techniques. This accountability can help ensure you customize your data governance needs and choose a business model that enhances the specific areas that need it.

2. Leverage integration technology.

Leverage integration technology

Before you can accurately execute data governance, your organization must be able to access and maintain data across the systems it employs. Many modern organizations retain an extensive portfolio of software applications that each has unique functions to uphold.

As more and more applications are moving to the cloud, businesses are beginning to shift their networks to accommodate both on-cloud and on-premise applications. This accommodation creates the need for efficient data integration to avoid switching between systems to retrieve information.

A network that lacks effective data integration may also utilize human and hardware resources for custom coding and application development, and publishing. This business strategy can include data analysts, data architects, software developers, and, accordingly, a complicated and expensive operating model. Some organizations have an entire governance team dedicated to cohesive data management. By utilizing data integration systems like iPaaS, aPaaS, and SaaS, you can ensure your organization has a solid foundation for effective data governance.

3. Consider your data’s integrity.

Data integrity

The quality of enterprise data can make or break your data governance initiative. Predefined quality metrics can help your organization differentiate between quality data and “bad” data. Your organizational standards for data collection and maintenance can influence the successful implementation of a data governance technique.

If there is room to enrich your data by enhancing or extending your existing data with complementary information, consider taking action before implementing a data governance strategy. The above-referenced methods may sound minimal, but every aspect of data governance builds on itself and interacts with each other to create one big picture.

Once you have finally accomplished your mission statement of effective data governance, there is one more step to ensure continued success. A profitable practice you may consider adding to your governance program is a feedback mechanism. By continually reviewing your data quality, integration, and security assessments, you can effectively monitor performance.

Paying close attention to each aspect of your data governance process can provide your organization with valuable operational insights. You can then utilize these insights to improve upon existing business processes and identify areas of strength and weakness within your organizational structure.

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