Trusted by Market Leaders in Education, Travel, Finance and E-commerce since 2007
We put excellence, value and quality above all - and it shows
A Technology Partnership That Goes Beyond Code
“Arbisoft has been my most trusted technology partner for now over 15 years. Arbisoft has very unique methods of recruiting and training, and the results demonstrate that. They have great teams, great positive attitudes and great communication.”
Data Governance and Security
Without governance, data silos and inconsistencies make insights unreliable and decision-making risky. Data governance becomes even more critical for AI use cases because it prevents sensitive information from infiltrating AI training datasets. Failing to establish robust data governance can lead to severe consequences, including data breaches, regulatory non-compliance, reputational damage, and financial losses. So, let’s start strengthening your data governance today.
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Our Approach to Data Governance & Security
At Arbisoft, we focus on improving data discoverability, strengthening access control, and streamlining lineage & auditing to establish a robust data governance mechanism.
Data Discovery
Effective data governance and security begin with a thorough understanding of your data. We work with you to improve data discovery by identifying, locating, and cataloging data and AI assets, automatically generating documentation of data and AI assets, and managing metadata and relationships of data objects.
Lineage and Auditing
Data lineage and auditing provide the necessary transparency into the data's lifecycle. We provide tools that help your organization understand where data comes from, how it transforms, and where it goes. All this visibility is paramount for maintaining data quality, trust, and accountability.
Security and Compliance
To protect data against unauthorized access, use, disclosure, disruption, modification, or destruction, we make sure that users only access the data they are authorized to. Our hierarchical privilege model enables us to grant fine-grained access to data and AI assets. We also ensure that our data processing activities align with data protection regulations, such as GDPR, CCPA, HIPAA, and other industry-specific mandates.
Unity Catalog in Databricks
As a Databricks consulting partner, we help organizations leverage Unity Catalog, a centralized centralized data catalog that provides fine-grained access control for tabular and unstructured data in multiple formats on multiple platforms, along with governance for AI assets like machine learning models. It also includes built-in capabilities to discover data, track usage, capture lineage, and monitor data quality.
Best Practices for Data Governance & Security
At Arbisoft, we ensure effective data governance and security through clear ownership, refined access policies, and appropriate classification of data. Our frameworks enforce data quality standards and implement security controls that allow the right stakeholders to access the right data with confidence. We also maintain comprehensive data lineage and auditing practices to help you track down any data security breaches.
Define clear roles, responsibilities, and policies for managing data and AI assets throughout their lifecycle.
Implement mechanisms to track the origin, transformations, and usage of data and AI assets to ensure transparency and accountability.
Enable comprehensive audit logging to track data access and platform events, facilitating compliance and security monitoring.
Establish and enforce standards for accuracy, consistency, completeness, and timeliness of data.
Use groups and service principals for granting permissions, avoiding direct grants to individual users for better manageability and security. Apply the principle of least privilege while granting access.
Use dynamic data masking and encryption principles and manage encryption keys on secret managers.
Review all data handling against compliance on regular intervals and use automated retention policies to archive or purge old data securely based on legal or regulatory needs.
Why Choose Arbisoft for Data Governance and Security
18+
Years building custom solutions and applications
550+
Projects Delivered
100+
Technologies Employed
800+
Specialists with decades of experience
Arbisoft Success Stories
What is edX
An online MOOC platform accessible to everyone with over 20 million learners and 140 partners making it a reliable and robust open-source platform.
Technologies
What is Philanthropy University
For enhanced course engagement and peer-to-peer knowledge exchange for Philanthropy University, Arbisoft enabled smooth integration between NodeBB and Open edX which transformed social impact education and empowered over 100,000 registered users to make a difference in their communities.
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What is Predict IO
Arbisoft developed an award-winning parking prediction app for Predict.io that accurately detects the driver's parking behavior using real-time sensor data, optimizing SDKs without being resource-intensive.
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What is CodeKer
An AI-powered alternative to platforms like Phind, Github Copilot, and ChatGPT Plus, designed to optimize the software development lifecycle.
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What is Travelliance
A robust web platform for accounting, reporting, and operations solutions with load-balanced servers and a modern tech stack.
Technologies
Frequently Asked Questions
Data governance improves data quality by enforcing consistency, accountability, validation, and transparency throughout the data lifecycle by ensuring data is accurate, complete, and reliable for BI and AI use cases.
Yes, defining standards, data ownership, access policies, and quality rules can take time initially. However, once governance is established, the benefits far outweigh the initial delays.
Mid-sized companies can build trust and confidence in data, often by implementing data governance. Such companies grow through multiple systems (CRMs, ERPs, spreadsheets, cloud apps). Implementing data governance ensures data accuracy, consistency, and integrity across those systems.
Yes, even if an organization is compliant with regulatory standards, it still needs a data governance framework. Compliance is the “destination,” whereas Data Governance is the “vehicle” that enables you to reach your destination.
Lack of data governance in AI poses many risks, such as loss of stakeholder trust in AI-driven decisions. Without strong governance, AI systems can produce biased, unreliable, or even non-compliant results. When training AI models on massive datasets, sensitive information can inadvertently become embedded in AI models, creating hidden vulnerabilities or inaccurate reasoning.
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