How can you secure data across all platforms?

2 Solution 1: Data cataloging

One of the best practices to address data fragmentation is data cataloging, which means creating and maintaining a comprehensive inventory of all the data assets across all platforms, along with their metadata, lineage, and usage. Data cataloging can help you identify, classify, and document your data sources, understand their relationships and dependencies, and track their changes and movements. Data cataloging can also help you enforce data security policies, such as access control, encryption, and masking, based on the data type, sensitivity, and location.

3 Challenge 2: Data compliance

Another challenge of securing data across all platforms is data compliance, which means ensuring that data meets the legal, regulatory, and ethical standards and obligations of the organization and its stakeholders. Data compliance can be difficult to achieve and maintain, as data laws and regulations vary by country, industry, and domain, and can change frequently and unpredictably. Data compliance also requires transparency and accountability, as data must be traceable, auditable, and reportable.

4 Solution 2: Data governance framework

One of the best practices to address data compliance is data governance framework, which means establishing and implementing a set of policies, procedures, roles, and responsibilities for data management and security across all platforms. Data governance framework can help you define and align your data strategy, objectives, and principles, as well as your data quality, privacy, and ethics standards. Data governance framework can also help you monitor and measure your data performance, risks, and issues, and take corrective actions when needed.

5 Challenge 3: Data culture

A third challenge of securing data across all platforms is data culture, which means fostering a shared understanding, appreciation, and value of data among all the stakeholders, from data producers to data consumers, from data owners to data users. Data culture can be hard to create and sustain, as data can be perceived as complex, intimidating, or boring by some people, or as a threat, a burden, or a liability by others. Data culture also requires collaboration and communication, as data must be shared, exchanged, and leveraged across different teams, departments, and functions.

6 Solution 3: Data literacy

One of the best practices to address data culture is data literacy, which means developing and enhancing the skills, knowledge, and confidence of all the stakeholders to use data effectively and responsibly across all platforms. Data literacy can help you educate and empower your data stakeholders, by providing them with the relevant tools, training, and support to access, analyze, and act on data. Data literacy can also help you engage and motivate your data stakeholders, by showing them the benefits, opportunities, and impact of data for their roles, goals, and outcomes.

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?