Data Governance
1. What is Data Governance?
Data Governance refers to the process related to the formal management of data within an organization. Data management, data security, etc. are sub-topics of the data governance that companies need to consider to ensure that their data is used safely and appropriately.
Data governance is the basis for classifying and defining data, assigning ownership and integrating day-to-day business processes. Assigning decision-making authority and responsibilities through effective data governance can encourage good data use. However, if the data governance is not effective, problems arise in areas related to data quality management and security.
Maintaining the reliability and quality of data is paramount in order to effectively use artificial intelligence and machine learning. Effective data governance is required to ensure good data use and to maintain data reliability and quality.
2. Importance of Data Governance
Accurate data governance enables monitoring of the data sources involved in decision making. This allows businesses to see data at a glance and gain insight in a consistent form. If the data governance is not properly implemented, there will be problems in data management and security, and it will not be easy to obtain meaningful insights from the data. Data governance focuses on three key elements.
- Data accessibility: An ability to obtain correct data when necessary.
- Data reliability: How confident the organization is about the quality, accuracy, and security of data.
- Data activation: How easy it is to take action based on the collected data.
3. Data management system with CLICK AI
Poor data governance can lead to unreliable conclusions in machine learning models. The data management system is critical to successful AI transformation. It’s important to understand where your data comes from, how it’s processed, the goals that AI platforms and machine learning models set to achieve.
