Components of successful data governance

Components of successful data governance

  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 of the models, policies, standards and rules that govern the collection of storage, arrangement and use of data in organizations. It simple 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 to begin is to focus on data and analytics to improve the quality of the data as the business grows. Data governance provides policies that maximize the investment that businesses put in data and analytics and content in multimedia platforms. Data governance is way more data-oriented rather than business oriented.  
  1. Data management; data management works towards the execution of data governance strategy, which in turn 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 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 company various solutions to be used. 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 set up a 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’s need to thoroughly examine and trace data to find out where it comes from, where it is and who has access to the data and how it is getting used? data security governance defines your organization’s rules and procedures and prevents potential risk of losing the sensitive data to competitors or cyber-criminals.  
  1. Compliance; As the organization grows, it becomes more challenging to adhere to rules an regulations  created by government and government institutions to protect data from reaching to 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, there are certain acts which 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 big fine statement or prison sentence. Data compliance governance makes sure to adhere to these regulations  and to keep the customer data safe and secure.  
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