Need to know data governance tools and unstructured data governance

Data governance is an important aspect of data management that ensures the availability, usability, integrity, and security of data. In today’s world, organizations are collecting and storing vast amounts of data, including both structured and unstructured data. While structured data is easy to manage, unstructured data presents unique challenges that require specialized tools and processes.

What are data governance tool and unstructured data governance

Unstructured data includes data that is not organized in a specific format, such as text files, audio files, video files, images, and social media posts. This type of data is often generated in large volumes and can be difficult to analyze using traditional data management tools.

To manage unstructured data, organizations need to implement an effective data governance strategy that includes specialized tools and processes. In this article, we will discuss data governance tools and unstructured data governance in more detail.

Data Governance Tools:

Data governance tool are software applications that are designed to help organizations manage their data effectively. These tools provide a centralized platform for data governance that allows organizations to manage data policies, standards, and procedures. They also help organizations to manage their data quality, metadata, and data lineage.

Here are some of the commonly used data governance tools:

Ohalo: Ohalo is a data governance platform that provides tools to help organizations manage their data in a secure and compliant manner. The platform offers a range of features that allow organizations to manage data throughout its lifecycle, from data discovery and classification to access controls and auditing. One of the key features of Ohalo is its ability to automatically discover and classify data. The platform uses machine learning algorithms to scan an organization’s data stores and identify sensitive information such as personally identifiable information (PII) and financial data. Once the data has been classified, organizations can apply policies and controls to ensure that the data is handled appropriately.

Collibra: Collibra is a popular data governance tool that provides a centralized platform for managing data governance policies, standards, and procedures. It helps organizations to manage their data quality, metadata, and data lineage. Collibra offers a range of features, including data cataloging, data lineage, and data stewardship.

Informatica: Informatica is a powerful data governance tool that provides a comprehensive platform for managing data governance policies, standards, and procedures. It offers a range of features, including data cataloging, data profiling, and data lineage. Informatica also provides tools for data quality management, data masking, and data integration.

IBM InfoSphere: IBM InfoSphere is a powerful data governance tool that provides a comprehensive platform for managing data governance policies, standards, and procedures. It offers a range of features, including data cataloging, data lineage, and data stewardship. IBM InfoSphere also provides tools for data quality management, data masking, and data integration.

Unstructured Data Governance:

Unstructured data governance refers to the process of managing unstructured data to ensure its quality, security, and compliance with regulatory requirements. Unstructured data governance is becoming increasingly important as organizations continue to generate large volumes of unstructured data.

Here are some best practices for managing unstructured data:

Develop Policies and Procedures: Develop policies and procedures that define how unstructured data will be managed within the organization. This includes defining the types of data that will be managed, how it will be stored, how it will be secured, and how it will be accessed.

Implement Data Classification: Implement data classification to identify the types of unstructured data that require the highest level of protection. This can be done by categorizing data based on its sensitivity, value, and legal requirements.

Conduct Data Inventory: Conduct a data inventory to identify all sources of unstructured data within the organization. This includes identifying where the data is stored, who has access to it, and how it is being used.

Implement Access Controls: Implement access controls to ensure that only authorized users have access to unstructured data. This includes using role-based access control and implementing strong authentication mechanisms.

Implement Data Retention Policies: Implement data retention policies to ensure that unstructured data is retained for the appropriate time. This includes defining the retention periods for different types of data and implementing procedures for deleting data that is no longer required.

Conclusion

Data governance is an essential aspect of data management that helps organizations to manage their data effectively. Unstructured data presents unique challenges that require specialized tools and processes to manage effectively