WHY DATA GOVERNANCE MATTERS; DISCUSSING ITS TOPMOST SIGNIFICANT BENEFITS.

With the ever-increasing proliferation of data, the need to protect and secure and uphold this vast amount of data is a concern for many businesses. Data gets generated through various means; whether through business processes, human devices, or IoT, the matter has taken us to a level where simplifying this data and making sense of it is of prime importance.

However, need for sound data governance is a must for every business to secure the generated valuable data and keep the trust of their stakeholders intact. With the help of specific policies, processes, and an organizational structure, enterprises are well on their way to supporting and maintaining a well-developed data management. The role of the data governance structure is to render understanding, security, and build trust among the organization's stakeholders, especially when handling data sources has become a matter of concern.

Data governance involves establishing infrastructure and technology, maintaining specific processes and policies, and identifying various positions within the enterprise that have both the authority and responsibility for protecting and handling specific types of data.

 It lays the foundation of an organization's overall strategy for data management purposes and is a significant part of DataOps practice. Moreover, data governance provides a complete picture to businesses based on what data they have, where that data rests, and how it can be utilized. 

Benefits of data governance 

Data governance practices equip an organization to get deeper insights while protecting data. Its benefit enables stakeholders to achieve cross-organization success; some of the benefits are laid down below:-

1. BETTER DATA SECURITY AND COMPLIANCE; the data governance practices promote security and compliance by helping enterprises mitigate the risk of breaches and fines while protecting customer trust. Its rules allow knowing what personally identifiable information (PII) exists and automates compliance through policy and management. 
2. IMPROVED DATA QUALITY; data often gets pulled from diverse data sources, hindering analytics and sabotaging important projects through inconsistencies. Therefore, the input data needs to be cleaned and managed correctly to make business decision-making effortless. Data governance assists in connecting information and identifying relationships across systems to get the most out of an enterprise's data.  
3. ACCELERATED AUTOMATION; data governance practices ensure the input data's accuracy and protection, enabling the analytics team to accelerate automation tasks and processes with quality and proper data organization. 

Conclusion 

Data governance and its practices lay the foundation of the further data analytics process. It is a set of policies processes and provides structure to an organization's data; it connects information and sets a relationship among different data sets to ensure the quality of the input data is refined and up to a great extent. It protects the data, maintains security and compliance, and even helps in sustaining customers' and stakeholders' trust in the organization. 

It aids in data analytics and plays a critical part in DataOps practices. Without data governance, it is almost impossible to maintain data management. Additionally, it helps mitigate the risks that certain kinds of breaches often cause. Its compliance with rules and regulations ensures complete protection from inside or outside sources.