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Last updated on Dec 21, 2024
  1. All
  2. Engineering
  3. Data Visualization

You're sharing sensitive visualizations with external partners. How can you ensure data privacy and security?

When sharing sensitive visualizations with external partners, protecting data privacy and security is paramount. Here are strategies to secure your information:

- Employ robust encryption methods for both storage and transmission of data visuals.

- Utilize access controls to restrict data visualization sharing to authorized individuals only.

- Implement watermarking to trace unauthorized distribution and maintain accountability.

How do you tackle the challenge of data privacy in your external collaborations?

Data Visualization Data Visualization

Data Visualization

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Last updated on Dec 21, 2024
  1. All
  2. Engineering
  3. Data Visualization

You're sharing sensitive visualizations with external partners. How can you ensure data privacy and security?

When sharing sensitive visualizations with external partners, protecting data privacy and security is paramount. Here are strategies to secure your information:

- Employ robust encryption methods for both storage and transmission of data visuals.

- Utilize access controls to restrict data visualization sharing to authorized individuals only.

- Implement watermarking to trace unauthorized distribution and maintain accountability.

How do you tackle the challenge of data privacy in your external collaborations?

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23 answers
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    Jalpa Desai

    ⭐14X Top LinkedIn Voice 🏆 || 12K +LinkedIn ||Gen AI || DS || LLM || LangChain || ML || DL || CV || NLP || MLOps || SQL💹 || PowerBI 📊|| Tableau || SNOWFLAKE❄️|| Corporate Trainer||Researcher || Mentor

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    To tackle the challenge of data privacy in external collaborations, I implement robust encryption methods for both storage and transmission, ensuring that sensitive visualizations are protected. I also set up strict access controls, sharing data only with authorized individuals, and use watermarking techniques to track any unauthorized distribution. Additionally, I ensure that all partners adhere to confidentiality agreements and implement secure collaboration platforms to further safeguard the data.

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    Arivukkarasan Raja, PhD

    IT Director @ AstraZeneca | Expert in Enterprise Solution Architecture & Applied AI | Robotics & IoT | Digital Transformation | Strategic Vision for Business Growth Through Emerging Tech

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    To ensure data privacy and security when sharing visualizations: 1. **Data Anonymization**: Remove or mask sensitive information. 2. **Secure Platforms**: Use encrypted, secure platforms for sharing. 3. **Access Controls**: Implement strict access permissions and authentication. 4. **Watermarking**: Add watermarks to prevent unauthorized use. 5. **Compliance**: Ensure adherence to data privacy regulations. 6. **Audit Trails**: Maintain logs of who accesses the visualizations.

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    Simran Bansal

    Data Scientist | IIT-M Certified | Expert in Exploratory & Predictive Analysis with Visualization | Building Advanced Machine Learning Models Daily | Unleashing creativity and innovation as pathway to success

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    According to Gartner, securing sensitive visualizations shared with external partners involves robust encryption, strict access controls, and watermarking to prevent unauthorized distribution. By implementing these measures, organizations protect data integrity and maintain trust. This comprehensive approach ensures that collaborative efforts remain secure, safeguarding both proprietary information and stakeholder confidence.

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    Gayatri Sharma Kurmatey

    Data Science Engineer @ Fremont Unified | Researcher | Pacific Gas and Electric | Tesla | Power BI | Tableau | SQL | Python | Machine Learning

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    Row-Level Security (RLS) controls access to specific data rows based on user roles or attributes. It ensures that users only see data they are authorized to view, adding an extra layer of security. In tools like Power BI or Tableau, RLS can be configured to enforce these restrictions, protecting sensitive information while sharing visualizations.

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    Nalini Singh

    Azure Data Engineer @Fractal.ai || NIT Agartala

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    It is first and most important things, there are many ways to achieve this some of them are by implementing access controls,using secure platforms with encryptions,usage of watermarks to visualisations,two factor authentications etc. But the major things is keeping all these parameters handy in order to avoid any mistake because such data privacy scrutiny is important for better practices and to avoid leakage of any sensitive informations.

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    Devisha Parekh

    Data Analyst | Ex-IBMer | 4xAzure Certifications | 1xIBM Cloud Certification

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    Ensuring Data Privacy in Visualization Collaborations: - Data Encryption: Protect your visuals with encryption during storage and sharing. - Access Control: Share only with trusted individuals using Power BI’s permissions. - Audit Logs: Monitor activity to track access and usage. Power BI offers powerful tools, but the key is using them thoughtfully. #DataPrivacy #Collaboration #SecureSharing

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    Syed Shahzad Ali Hamdani

    Terminal Operations & Logistics Expert | Six Sigma Green Belt & Kaizen Certified | Power BI Pro | 11+ Years in Port Operations & Supply Chain | Driving Efficiency & Cost Savings

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    When I'm working with others outside my organization, keeping sensitive visuals safe is a top priority. I use encryption and strict access controls, and I remove identifying information from sensitive data whenever possible. We use secure platforms and watermarks to prevent misuse, and regular checks and confidentiality agreements help build trust and make sure we're following the rules. This way, we can work together effectively without compromising security.

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    Renata Cecconi

    🇧🇷🇮🇹 Physicist | Data Science Master's Candidate | Analytics | Model Risk | Risk Management | Machine Learning

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    When sharing sensitive visualizations with external partners, it’s crucial to prioritize data privacy and security measures. Start by limiting access to authorized stakeholders only, ideally by using secure authentication protocols and role-based permissions. Encrypt the data both at rest and in transit, and, if possible, anonymize or aggregate sensitive information to prevent exposure of personal or proprietary details. Additionally, maintain a strict governance policy by regularly auditing access logs, applying version control, and consistently reviewing the latest security standards and compliance regulations. This comprehensive approach helps safeguard confidential insights while fostering a trusted collaboration environment.

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    Mercy Ileti Ogwuche (MPH)

    Data Analyst,GIS specialist, MEL, CQI Specialist(Trainer), and A public health specialist

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    To tackle data privacy in external collaborations, I ensure compliance with data protection laws (e.g., GDPR, CCPA) and establish clear data-sharing agreements outlining roles, data usage, and privacy clauses. I minimize data collection, anonymize data when possible, and implement secure systems like encrypted channels and access controls. Regular audits and stakeholder training help maintain privacy standards. Transparency with partners and clear consent processes are essential. I also maintain an incident response plan for potential breaches and keep privacy policies updated.

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    Himank Choudhary

    State Coordinator - Digital India Corporation (Ministry of Electronics and Information Technology)

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    When sharing sensitive visualizations with external partners, I will ensure data privacy and security by implementing encryption, access controls, and anonymization. I will use secure file-sharing platforms with permission-based access and ensure compliance with data protection regulations. Regular audits and security training are also key components for my approach.

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