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  • Our Company
    • About Us
    • Team
    • Life @ Arush Infotech
    • Office Locations
    • Company Policy
  • Industries
    • Healthcare
    • Finance
    • E-Commerce
    • Technology
    • Manufacturing
    • Retail
  • Resources
    • Blog
    • Case Studies
  • Services
    • Data Science
      • Data Analysis
      • Data Visualisation
      • statistical Modeling ​
    • Python development
      • WebApplication
      • Data Analysis
      • Automations ​
    • Machine Learning & Artifical Intelligence
      • Predictive Analytics
      • Natural Language Processing
      • computer Vision​
    • Drupallers
  • Tools
    • BI & Analytics
      • Business Intelligence & Analytics Overview
      • Visualizations & Dashboards
      • Reporting & Self-service Analytics
      • Product AI
      • Data Science & Machine Learning
      • Embedded Analytics
    • Data Integration
      • Data Integration Overview
      • Data Sources
      • Drag-and-drop ETL
      • Cloud Data Warehouse Integration
    • App Creation Tools
      • Business Apps Overview
      • Build Low-code Apps
      • Develop Pro-level Apps
      • Create No-code Process Automation
      • Find Pre-built Business Apps
    • Governance & Security
      • Governance Overview
      • Security & Compliance Overview
      • Governance Toolkit
  • Contact Us
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Company Policy

Data Science Policy

1. Data Collection and Usage:

Purpose: Data should be collected and used solely for business purposes, supporting decision-making and improving products/services.

Legal Compliance: Adhere to all applicable laws and regulations governing data collection, storage, and usage.

Data Quality: Ensure data accuracy, relevance, and reliability before utilization.

2. Data Security and Privacy:

Confidentiality: Safeguard sensitive and proprietary data from unauthorized access or disclosure.

Access Controls: Limit access to data based on job roles and necessity. Implement robust access control mechanisms.

Anonymization and De-identification: Prioritize anonymization or de-identification techniques where applicable to protect individual privacy.

3. Ethical Use of Data:

Bias Mitigation: Continuously assess and mitigate biases in algorithms and data models to ensure fairness and inclusivity.

Transparency: Strive for transparency in data processes, model outcomes, and decision-making to build trust with stakeholders.

Avoidance of Harm: Take measures to prevent the misuse of data that could cause harm to individuals or groups.

4. Data Governance and Compliance:

Responsibility: Designate accountable parties for overseeing data governance practices and compliance adherence.

Documentation: Maintain clear documentation of data sources, processes, and transformations for auditability.

Regular Audits and Assessments: Conduct periodic audits and assessments to ensure compliance with internal policies and external regulations.

5. Collaboration and Communication:

Cross-functional Collaboration: Encourage collaboration between data science teams and other departments to ensure alignment with business goals.

Clear Communication: Communicate data findings, methodologies, and limitations effectively to stakeholders with varying levels of technical expertise.

6. Policy Compliance:

Acknowledgment and Compliance: All employees involved in data-related activities must acknowledge and adhere to this policy. Non-compliance may result in disciplinary action.

Note: This policy serves as a guideline and may be subject to updates or modifications based on changing industry standards, technological advancements, or legal requirements.

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CONTACT US

  • +1 (341) 221-9451
  • +91 8585955704
  • info@arushinfotech.com

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  • 19, c6b, Janakpuri, Delhi, 11580
    INDIA

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