Data governance refers to the process of managing a data set’s integrity, security, relevance, and availability within an enterprise system.
What Data Governance Means and Why You Need It
This governance is typically based on existing standards or policies that dictate data usage but can also be used to identify areas of weakness to implement these standardizations.
The trademark of effective data governance systems is consistent, quality data that is never misused and never discarded without proper analyses.
As business intelligence practices continue to develop due to data science technology innovation, modern organizations must adjust to adhere to protective standards.
Data governance is a primary component in any business strategy.
However, data governance can present itself in a number of ways, so organizations must examine their specific goals and implement a data governance program that can meet those requirements without compromising the efficiency of workflow.
Why Is Data Governance Necessary?
Many modern organizations have a portfolio of applications that make up a network. Some of these applications may be primarily used internally.
Still, in other cases, consumers may be able to access them as well, for example, in a retail company that has an in-store CRM system and an on-site shopping platform.
Since many retail companies utilize reward programs or membership incentives, customer information must be recognized across all platforms.
When making an online purchase, the site should remember customer data that the in-store clerk entered during an in-person sale.
Disparities in these data sets could result in errors that cause customers to miss out on rewards and businesses to receive inaccurate information regarding purchases and customer data.
Additionally, in organizations requiring strict guidelines or jurisdictional regulations like insurance companies, poor data governance can violate laws or compliance initiatives.
Many of these regulations are in place to protect customers’ sensitive data and protect organizations from security threats. A sound data governance system can eliminate harmful errors in data collection and management.
Why Is Data Quality Important?
Data quality refers to the measurement of data in areas such as completeness, accuracy, and consistency.
Data quality is important because data is the backbone of every business intelligence initiative.
Data governance improves operations management and helps executives make decisions through statistical algorithms that provide insight.
Data integrity directly affects the accuracy and efficiency of the insight and predictions provided to business intelligence tool users.
Data quality analysts help ensure that the data being fed to each of these analytical systems is relevant and complete.
Essentially, data quality sets the groundwork for each subsequent form of data management.
What Makes Up a Data Governance System?
Data governance frameworks are complex structures. The organizational structure of a data governance program includes the regulations or policies implemented within an organization, such as company procedures or governmental regulations.
Next, it considers the goals or initiatives of the particular business. Since every organization is different, data governance programs will fluctuate despite the core similarities they have with one another.
Success measurement techniques, or milestones, will also be implemented in a data governance system.
This specification of measurement techniques can ensure the consistency of quality standards across an organization.
Another aspect of a data governance initiative is accountability. Strict data vigilance can provide insight as to specific areas of strength or weakness.
Data governance can also examine current business processes and find efficient means of automating aspects of them.
From an operational standpoint, data governance can help identify means of improving accuracy and consistency regarding workflow.
These types of insights can help businesses prioritize their resources and eliminate unnecessary waste.
TIBCO, the data science software leader, provides several helpful resources for business owners and students interested in data science methodology.
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