Data Governance And Data Management

Is data governance part of data management?

No. Data governance is a function of information risk management (IRM) and is different from information management (IM). IM involves protecting and storing information; IRM looks at information use, ensuring it is accurate and appropriate.

Data governance has been called the glue that holds data management together. As such, we would expect data governance to be included as part of Delphix data management.

Indeed, some data managers use data governance tools within their data management software and some data governance tools are specifically designed to fit into data management software. However, we think that a data manager is wise to look at data governance as a separate function within their organization and consider how this can be performed outside of the context of a specific data management solution.

Why do we think that data governance should not be considered part of data management?

Because data governance is about much more than data.

Data governance is about ensuring that data is used in the right way and that the right processes are in place to protect the integrity of the data and its creators. Data governance covers legal requirements, the collection and maintenance of data, the rights of people who create and use data, and the ethical management of data.

The fact that data management software is specifically designed to manage a particular type of data does not mean that the data management software will automatically understand the data governance processes that need to be put in place around the data. For example, if you have a spreadsheet file, you will not be able to set up data governance rules around it. But you might be able to set up data governance rules that apply to a database table or view.

The fact that data management software offers the capability to import data does not mean that the data management software will automatically understand the data governance processes that need to be put in place around the data. For example, the data governance processes for an Oracle database table are likely to be different from those for a Microsoft Access database.

What can you do?

Data governance can be applied to many types of data. You can ensure that the data is stored safely, correctly, and appropriately. You can make sure that the data is properly maintained, archived, and secured. You can check that the data meets the legal, privacy, and ethical requirements for the data. You can make sure that the data is accessible by the right people at the right times. And you can make sure that the data is not shared inappropriately.

Some data governance tools have been developed specifically for data management software and they offer specific capabilities that can be applied to the data managed by the data management software. However, data governance tools can be used independently of data management software.

If you use data management software, then you might have the opportunity to learn how to use a data governance tool. You can also use data governance tools to manage data independently of data management software.

How is it different from data management?

IRM is a process of managing risks and improving controls over data and information. It includes processes such as risk assessment and threat modeling to evaluate the impact of data handling on the organization.

It helps companies to prepare for cyberattacks, data loss, or other security issues. A risk-based approach helps companies to minimize the risk of data breaches and can be implemented by using a combination of tools and techniques.

Why should we be concerned about data governance?

There are many types of data to be considered and it is important to take a holistic approach to the collection and protection of personal information. This means looking at the processes and systems that manage and store data and how this impacts the people who use the data. There are also legal and ethical considerations to be addressed, such as the collection of personal data and the right to request a copy. It is important that these are clearly defined and that the right processes and systems are in place to ensure the appropriate level of protection is maintained.

The introduction of the GDPR has brought a whole new set of challenges for organizations. The aim of the legislation is to create greater transparency for organizations regarding the personal data they hold and to increase accountability for how this data is handled. While it is unlikely that the organization will be fined, the introduction of these new requirements has meant that there are now many more things to consider. 

How can we ensure that our data governance is effective?

You should regularly review your data governance strategy and make sure it remains current. This will involve making sure that your systems and processes are secure, safe, and robust. As part of this, you should regularly review your data management policies and procedures to ensure that they cover issues such as data ownership, retention, and confidentiality.

It is important to make sure that your organization is following the correct data protection laws. There are also other types of risks that your data governance strategy needs to address. For example, when you have data that is collected from an external source, you need to make sure that you are compliant with the data protection legislation in the country where the data originated. If you are collecting data from customers, then you should make sure that you follow any contractual obligations that you have agreed to. You may also need to consider the security of your data when it is being processed or stored. Data governance is important for all types of organizations and can help to ensure that you are meeting the legal requirements in your particular circumstances. 

Who should be responsible for data governance?

You should ensure that senior managers are aware of and support the data governance strategy and that the team is well trained and experienced in the operation of the systems and processes involved.

The data governance team should also be involved in the project from the beginning to ensure that the project is implemented in a way that does not compromise the integrity of the data.

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