DATA GOVERNANCE — TODAY’S REALIZATION SOONER RATHER THAN LATER
Data is becoming the core corporate asset that will determine the successes of your business. Digital transformation is the practice of today. You can only exploit your data assets and do a successful digital transformation if you govern your data. Essentially, it is imperative to deploy a data governance framework that fits your organization and your future business objectives and business models. That framework must control the data standards needed for this journey and delegate the required roles and responsibilities within your organization and concerning the business ecosystem where your company operates. A well-managed data governance framework will underpin the business transformation toward functioning on a digital platform at many levels within an organization.
Data Governance fundamentally is a set of principles and practices that ensure high quality through the complete lifecycle of your data. Deriving value through well-governed processes requires meticulous planning on usage data and consistent handling throughout the business to support business outcomes. For example, proper managing of Data processing activities, increasing efficiency in decision making, reducing storage costs, and enabling compliance with laws and regulations.
Entities that constructively make considerations for the How and 5W’s of Data (Who, What, When, Where, Why) ensure security, compliance, and extract value from the information collected and stored across the business, thereby improving business performance. Essentially, that is what Data Governance embodies. The 4th Industrial Revolution represents a fundamental change in how we live, work, and relate to one another. It is ongoing automation of traditional manufacturing and industrial practices using modern digital technology. Industry 4.0 is a fusion of advances in Artificial Intelligence (AI), robotics, blockchain, the Internet of Things (IoT), genetic engineering, quantum computing, to mention but a few.
These technology trends of Machine Learning and AI rely on data quality that sequentially raises the necessity of appreciating and understanding the relevance of data governance and how it impacts today’s business stakeholders, environments, and company goals.
Data Governance can aid your organization in the following ways;
- Meet regulatory requirements and avoid fines by documenting the lineage of the data assets and the access controls related to the data
- Improve data security by establishing data ownership and related responsibilities
- Define and verify data distribution policies that include the roles and accountabilities of involved internal and external entities
- Assign data quality responsibilities to measure and follow up on data quality KPIs related to the general performance KPIs within the enterprise
- Plan better by not having to cleanse and structure data for each planning purpose
- Eliminate re-work by having data assets that are trusted, standardized, and capable of serving multiple purposes
- Optimize staff effectiveness by providing data assets that meet the desired data quality thresholds
- Evaluate and improve by raising the data governance maturity level- phase by phase
- Make consistent, confident business decisions based on trustworthy data aligned with all the various purposes for the use of the data assets within the enterprise
- Use data to increase profits (everybody likes this one). Data monetization starts with having data stored, maintained, classified, and made accessible in an optimal way.
- Acknowledge gains and build on forward momentum to secure stakeholder continuous commitment and a broad organizational support
You can learn a lot from others who have been on a data governance voyage. Nevertheless, every organization/entity is unique, and you need to adapt the data governance practices to propel you move to the next step.
The writer is a Research Analyst at ANJ Data Management Solutions (A) Ltd
