课程: How to Build and Execute a Successful Data Strategy

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Establishing data quality processes, data cleansing, and data validation techniques

Establishing data quality processes, data cleansing, and data validation techniques

课程: How to Build and Execute a Successful Data Strategy

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Establishing data quality processes, data cleansing, and data validation techniques

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- Now that we have explored how to define and build a framework, it is time to explore data classification and metadata management. Firstly, let's understand data classification. Data classification involves organizing and categorizing data assets based on their sensitivity, criticality, and other relevant attributes. It helps to establish clear guidelines for how data should be handled, protected, and shared within the organization. Data classification also supports compliance with regulatory requirements and enables effective data management practices. My four key areas for data classification are data sensitivity, data criticality, data ownership, and data handling guidelines. Let's go through each one. First, data sensitivity. Determine the level of sensitivity of the data based on factors such as personal identifiable information, PII, and financial information. Classify data into categories, such as public, internal, confidential, and highly confidential. Now onto data…

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