Trends
What is a data governance framework and what are its models?
The purpose of a data governance framework is to ensure the integrity, internal distribution, and security of data. The lack of a framework leads to poor data quality and compliance issues, resulting in data silos and inconsistent reporting. Data governance frameworks help organisations standardise …
Headline
The purpose of a data governance framework is to ensure the integrity, internal distribution, and security of data. The lack of a framework leads to poor data quality and compliance issues, resulting in data silos and inconsistent reporting. Data governance frameworks help…
Context
The purpose of a data governance framework is to ensure the integrity, internal distribution, and security of data. The lack of a framework leads to poor data quality and compliance issues, resulting in data silos and inconsistent reporting. Data governance frameworks help organisations standardise and unify data by democratising data accessibility and trust. A data governance framework is a set of rules, processes, and responsibilities that dictate how an organisation collects, organises, stores, and uses its data. The goal of a data governance framework is to set a standard on how data is managed to ensure its integrity, leveraged by internal teams, and protected from security risks.
Evidence
Pending intelligence enrichment.
Analysis
Also read: 5 data governance roles and responsibilities Without a data governance framework in place, companies can’t guarantee data quality or compliance with privacy regulations. This opens the door to mismanaging customer data, which could land you in hot water legally (resulting in hefty fines and reputational damage). In the absence of a data governance framework, individual departments follow their own standards and processes, creating data silos that quickly snowball into inefficiencies. Instead of consulting a single source of truth within an organisation, employees only have insight into the data collected with their own tools. This creates blind spots in understanding, and sometimes mismatched reporting between databases – resulting in a distrust of data altogether. Also read: Strategic checklist for effective cloud data migration
Key Points
- Infrastructure automation is an alternative to manually configuring and orchestrating infrastructure in cloud and on-premises environments.
- The benefits of infrastructure automation are mainly reliability, repeatability, and reduced cost of evaluating and resolving errors.
Actions
Pending intelligence enrichment.
