Components of successful data governance

Top 6 Components of successful data governance

What is data governance? Well, for one thing, it’s a buzzword. And with buzzwords, we often forget to slow down and examine what they mean. This article is dedicated to the essential elements of data governance and emphasizes the importance of implementing them from start to finish. 

  1. Data architecture: data architecture is the soul component of data governance, as it provides high defined data quality in architectural design. It makes data governance reliable and gives insights in data analysis to the enterprise in making far more well-defined business goals. According to TOGAF (The Open Group Architecture Framework), data architecture shows the entire structure of an organization’s logical and physical assets and data management resources. It comprises the models, policies, standards, and rules that govern the collection of storage, arrangement, and use of data in organizations. It simply works to define the places where data exist and travels throughout the organization’s ingress data connections. It also highlights the changes in the data track to detect its changing forms and transformation within the system.   
  1. Quality of data: data governance encourages businesses to make smarter decisions with the right data and analytics. A good start is to focus on data and analytics to improve the data quality as the business grows. Data governance provides policies that maximize businesses’ investment in data and analytics and content in multimedia platforms. Data governance is way more data-oriented rather than business-oriented.   
  1. Data management: works towards executing data governance strategy, which sets up the responsibility to implement the policies inculcated by the framework. Some of the common tasks of data management are   
  • Creating Role-Based Access rules (RBAC)  
  • Implementing database rules  
  • Establish and maintain data security  
  • Minimize risk associated with storing sensitive data  
  • Creating a single view of data across the enterprise.  

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  1. Data software tools; data governance ensures the availability, usability, and integrity of data. To keep the data safe and secure, DGT and CDO’s must constantly monitor and analyze the organization’s data and its policy to maintain it. This can be achieved only with proper data software tools, which provide the company with various solutions. These solutions, in turn, provide the users a set of consistent policies, processes, and ownership of data assets, which enables them to monitor, manage, and control data movement effectively.   
  1. Security; drastic breaches can leave organizations vulnerable to losing data which can cost businesses millions of dollars. There must be a setup security tool to protect data against cyber-criminals of all kinds. Data governance is vital to analyze and cover confidential data thoroughly. DGT and CTO need to thoroughly examine and trace data to find out where it comes from, where it is, who has access to the data, and how it is getting used? Data security governance defines your organization’s rules and procedures and prevents the potential risk of losing sensitive data to competitors or cyber-criminals.   
  1. Compliance; As the organization grows, it becomes more challenging to adhere to rules and regulations created by government and government institutions to protect data from reaching the wrong hands. It becomes a primary responsibility of organizations to adhere to regulations passed by NIST and other such institutions. Under the European Union, certain acts are very well-known in the digital data community of economy GDPR(General Data Protection Regulation), PCI DSS in U.S., HIPAA, SOX act or Sarbanes-Oxley Act of 2002. All organizations must comply with these rules and regulations; any violation could result in a big fine statement or prison sentence. Data compliance governance makes sure to adhere to these regulations and keep the customer data safe and secure.   


From time to time, technical problems may arise, and it is important to be proactive in responding. Such problems are difficult to detect manually but very easy to test for automatically using the baseline tests provided by iSmile Technologies Data Quality Manager. 


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