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How can you use data discovery tools to identify and protect sensitive data in real-time?

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Data is one of the most valuable assets of any organization, but it also comes with risks and responsibilities. Sensitive data, such as personal information, financial records, or intellectual property, can be exposed, stolen, or misused by malicious actors or unauthorized users. To prevent data breaches, comply with regulations, and maintain trust with customers and stakeholders, you need to know where your sensitive data is, who has access to it, and how it is protected. This is where data discovery tools can help you.

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Deepak Seth

Data Privacy and Cyber Security Professional | Solution Design and Architecture | Cloud Security | AI Governance | AI…

1 What are data discovery tools?

Data discovery tools are software applications that scan, analyze, and classify data across your data sources, such as databases, cloud storage, data lakes, or data warehouses. They use techniques such as pattern matching, machine learning, natural language processing, or metadata analysis to identify and label data elements based on their type, content, and sensitivity. For example, a data discovery tool can detect data that contains names, email addresses, phone numbers, credit card numbers, social security numbers, or other personally identifiable information (PII) and assign them a high-risk score.

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Deepak Seth

Data Privacy and Cyber Security Professional | Solution Design and Architecture | Cloud Security | AI Governance | AI Security | Data Compliance | Risk Management
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Ong of the very important yet often missed tool is Dictionary. Every organisation needs to define a dictionary of keywords, data elements based on their unique business requirements and outcomes needed from the discovery scans. This dictionary can vary based on whether compliance to laws and regulations is the main outcome or whether the data needs to be used by marketing team in order to understand their customers and their unique buying behaviours/patterns. These outcomes would feed into the appropriate dictionary that needs to be created and then feed into the data discovery solutions. This will make sure discovery scans are targeted and provide immediate value to the business.

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2 Why do you need data discovery tools?

Data discovery tools can offer several benefits related to data governance and security, such as discovering and inventorying sensitive data assets, monitoring data access and usage, enforcing and automating data policies, complying with data privacy regulations, and improving data culture and awareness. With these tools, you can understand the location, format, quality, and lineage of your sensitive data assets. You can also identify anomalies or violations in access or usage patterns. Furthermore, you can demonstrate adherence to auditors and regulators when it comes to GDPR, CCPA, HIPAA, or PCI DSS. Finally, you can empower your data owners, stewards, and consumers to take responsibility for data protection.

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3 How can you use data discovery tools in real-time?

Data discovery tools can operate in different modes, such as batch, scheduled, or real-time. Batch mode involves scanning and analyzing data sources periodically, while scheduled mode runs on demand or is triggered by a specific event. Real-time mode monitors and processes data streams continuously and dynamically. Real-time data discovery offers several advantages over batch or scheduled modes, such as the ability to detect and respond to data incidents faster, keep up with the velocity and volume of data sources, support data-driven decisions with current data, and integrate the tool with other data management and security tools.

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4 What are the challenges of real-time data discovery?

Real-time data discovery can also pose some challenges that you need to consider and address. For instance, you need to have sufficient computing power and network bandwidth to handle the high volume and velocity of your data streams, as well as robust data quality and data validation processes. Additionally, you need flexible and scalable data discovery tools that can handle different data formats, schemas, and languages. Moreover, it is important to have clear and consistent data policies and rules that align with your business objectives and regulatory obligations.

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Deepak Seth

Data Privacy and Cyber Security Professional | Solution Design and Architecture | Cloud Security | AI Governance | AI Security | Data Compliance | Risk Management
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Data discovery can be very time, resource and thus cost sensitive process. Discovering objects containing commercially sensitive as well as personal identifiable information(PII) using data elements, keywords over terabytes of data requires lots of compute as well as network resources. Some of these discovery scans specifically on unstructured data sources can take months to complete. Thus, it becomes quite crucial for the data governance team to work collaboratively with the business stakeholders and define a Organisation’s specific data dictionary having the right keywords or data elements that can be scanned. This would lead to better and faster outcomes for the business and ROI from the solution.

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5 How can you choose the right data discovery tool for your needs?

When selecting a data discovery tool for your needs, you need to consider several factors, such as the sources and types of your data, the methods and techniques that are most appropriate and effective for your data, the scope and frequency of your data discovery, and the outputs and outcomes that you need. Your data sources may be on-premise, cloud-based, or hybrid, and your data types may be structured, semi-structured, or unstructured. You should select a tool that can use pattern matching, machine learning, natural language processing, or metadata analysis to provide you with high accuracy, precision, and recall rates. Additionally, the tool should cover your desired data discovery scope and frequency (whether you need to scan your entire data landscape or only specific data domains) and run in batch, scheduled, or real-time mode. Finally, it should provide you with the outputs and outcomes that you need (such as data inventory, classification, risk assessment, policy enforcement, or compliance reporting) and integrate them with other data management and security tools.

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Deepak Seth

Data Privacy and Cyber Security Professional | Solution Design and Architecture | Cloud Security | AI Governance | AI Security | Data Compliance | Risk Management
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In order for the discovery scanning tools to be effective, it should provide the following information: 1. As these discovery scans can run for over weeks and sometimes even for months so it becomes very crucial for the discovery scanning tool to share the real time status of the scans. For example, in case of SharePoint sites, the scanning tool should show how many SharePoint sites scanning is completed and expected time to complete the remaining sites. 2. Easy and effective way to define data elements using keywords or regular expressions. 3. Should allow to import organisations specific templates so these can be scanned against the entire data source. 4. Rich and Power API’s (preferably GraphQL based API) for integrating the results.

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6 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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How can you use data discovery tools to identify and protect sensitive data in real-time?

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1 What are data discovery tools?

2 Why do you need data discovery tools?

3 How can you use data discovery tools in real-time?

4 What are the challenges of real-time data discovery?

5 How can you choose the right data discovery tool for your needs?

6 Here’s what else to consider

Data Governance

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How can you use data discovery tools to identify and protect sensitive data in real-time?

1

2

3

4

5

6

1 What are data discovery tools?

2 Why do you need data discovery tools?

3 How can you use data discovery tools in real-time?

4 What are the challenges of real-time data discovery?

5 How can you choose the right data discovery tool for your needs?

6 Here’s what else to consider

Data Governance

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