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What factors should you consider when selecting a data classification policy?

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Data classification is the process of organizing data into categories based on its sensitivity, value, and risk. A data classification policy defines the criteria and rules for assigning data to different levels of protection and access. As a system administrator, you need to consider several factors when selecting a data classification policy for your organization. Here are some of the most important ones.

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JHIMLI GHOSH

Strategic HR operational specialist for more than two decades with focus on bringing business impact in cross…

1 Business objectives

Your data classification policy should align with your business objectives and support your strategic goals. For example, if your organization handles sensitive customer information, your policy should ensure compliance with relevant laws and regulations, as well as enhance customer trust and loyalty. If your organization relies on data-driven innovation, your policy should facilitate data sharing and collaboration, as well as protect your intellectual property and competitive advantage.

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2 Data types and sources

Your data classification policy should reflect the diversity and complexity of your data types and sources. For example, you may have structured data, such as databases and spreadsheets, or unstructured data, such as documents and emails. You may also have data from internal or external sources, such as employees, customers, partners, or vendors. You should identify the characteristics and requirements of each data type and source, such as format, content, ownership, and lifecycle.

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3 Data risks and impacts

Your data classification policy should assess the potential risks and impacts of data loss, theft, or misuse. For example, you should consider the legal, financial, operational, and reputational consequences of a data breach or a data error. You should also evaluate the likelihood and severity of different threats and vulnerabilities, such as hackers, malware, human error, or natural disasters. You should assign data to different categories based on the level of risk and impact, such as public, internal, confidential, or restricted.

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4 Data protection and access

Your data classification policy should define the appropriate level of protection and access for each data category. For example, you should specify the encryption, backup, retention, and disposal methods for each data type and source. You should also determine the access rights and roles for each data user and stakeholder, such as read-only, edit, or delete. You should implement and enforce data security controls and policies, such as passwords, firewalls, or audits.

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JHIMLI GHOSH

Strategic HR operational specialist for more than two decades with focus on bringing business impact in cross functional industries #Talent Acquisition # Talent Management # People Connect #People & Productivity#
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It is very essential to determine the access right of data to individuals . Everybody need not have access to all or full information so it is required to cut or filter the data / information in the form of data before transmitting. If selected data is passed then it will also help others to take prompt and to the point action. Unnecessary data may confuse the person and thereby there will be delay in action. At times people may not understand the excess data provided and thereby take wrong action which can be really harmful and very expensive.

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5 Data quality and accuracy

Your data classification policy should ensure the quality and accuracy of your data. For example, you should verify the validity, completeness, consistency, and timeliness of your data. You should also monitor and update your data regularly, as well as correct any errors or anomalies. You should establish and follow data quality standards and procedures, such as validation, cleansing, or transformation.

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JHIMLI GHOSH

Strategic HR operational specialist for more than two decades with focus on bringing business impact in cross functional industries #Talent Acquisition # Talent Management # People Connect #People & Productivity#
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Classification of data is very important. It is utmost important to check the validity and authenticity of the data as they will in turn show the business results and trends.Data should be first hand and protected from external tampering Like when we are obtaining data from internal sources then the person handling the data need to be very authentic and trustworthy . To handle data with utmost sincerity is an ethical quality of a true professional.

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6 Data governance and accountability

Your data classification policy should establish the roles and responsibilities for data governance and accountability. For example, you should assign data owners and custodians who are accountable for the creation, maintenance, and protection of data. You should also involve data users and stakeholders who are responsible for the use, analysis, and reporting of data. You should communicate and educate your data community about the data classification policy, as well as review and revise it periodically.

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JHIMLI GHOSH

Strategic HR operational specialist for more than two decades with focus on bringing business impact in cross functional industries #Talent Acquisition # Talent Management # People Connect #People & Productivity#
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It is very important to create and preserve the authenticity of the data in any organisation. Therefore it is very essential that the people who handles data or create them have ethical ownership Like for HR the person who creates the MIS for the management should be a person who has ownership and at the same time he should not do loud talks with other departments to spread the internal trends and performance of HR.This applies to all other critical departments and role holders who are into data creation and handling. Likewise the people who maintain the data should follow proper guidelines. The protection of data is equally important and mishandling is very harmful. Communication to all stakeholders and review of the data policy is needed

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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What factors should you consider when selecting a data classification policy?

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1 Business objectives

2 Data types and sources

3 Data risks and impacts

4 Data protection and access

5 Data quality and accuracy

6 Data governance and accountability

7 Here’s what else to consider

System Administration

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What factors should you consider when selecting a data classification policy?

1

2

3

4

5

6

7

1 Business objectives

2 Data types and sources

3 Data risks and impacts

4 Data protection and access

5 Data quality and accuracy

6 Data governance and accountability

7 Here’s what else to consider

System Administration

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