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Big Data Governance: Best Practices for Managing and Securing Your Data Featured

Big Data Governance: Best Practices for Managing and Securing Your Data Miguel Bruna

In the world today, data is often considered the new oil because of what it can help businesses do. It has become a valuable asset for businesses and organizations of all sizes. While everyone knows the result of properly managed data, managing and securing it is a challenge many still face. This is where Big Data Governance comes into play.

Big Data Governance refers to the policies, procedures, and technologies businesses and other institutions deploy to manage and secure their data. It ensures that the data collected and stored is not only accurate and complete but is also consistent and can be trusted as well. Here are some best practices organizations can follow to manage and secure their data through Big Data Governance.

  1. Define your Data Governance Policies

Before you do anything else, the first step in implementing your Big Data Governance is to define the policies that will govern your company’s data. Create a framework that defines how data is collected, processed, and analyzed. The framework should include guidelines on how to use data to make decisions, and who has access to it. The policies should be documented and communicated to all relevant stakeholders, including employees, partners, and customers.

  1. Establish Data Management Procedures

Once you have defined the policies, establish data management procedures. To achieve this, create processes for collecting, processing, analyzing, and storing data. As an organization, you need to define the data types you collect, how it is used, and how long it is stored. Additionally, you need to define how data is collected, who has access to it, and how it is processed. You can achieve this using data management tools and technologies.

  1. Create a Data Quality Framework

Not all data is equal, and that is why you need to focus on data quality because this determines the success of any big data governance program. To ensure data is accurate, complete, and consistent, you must create a data quality framework. Identify the data quality standards and define the data validation and cleansing procedures. Additionally, you should establish a process for monitoring data quality and ensuring that it meets the established standards.

  1. Implement Data Security Measures

Any data governance program revolves around data security. Therefore, you should implement measures to protect data from unauthorized access, theft, and loss. You can achieve this using encryption, firewalls, and access control mechanisms. Additionally, you should implement data backup and disaster recovery plans to ensure your organization’s data is recoverable in case of a breach or other disaster.

  1. Comply with Regulations

Compliance with laws and regulations can save your organization millions in fines and disturbance. Comply with laws such as the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA). You must also regularly review your data governance policies and procedures to ensure they comply with relevant regulations.

  1. Implement Data Privacy Measures

With the rise of breaches and cyber-attacks, data privacy has never been this important. You need to ensure that your organization is protecting the privacy of its customers’ data. Implementing measures like anonymization and pseudonymization ensures that personally identifiable information is not exposed. Develop a process for notifying customers in the event of a data breach.

  1. Invest in Employee Training

Training ensures that big data governance policies and procedures are being followed. Therefore, you need to invest in employee training. Employees should understand the importance of data governance, policies, and procedures in place—train staff on identifying and reporting potential data breaches.

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Scott Koegler

Scott Koegler is Executive Editor for Big Data & Analytics Tech Brief

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