Data Governance Services

Amplify your business initiatives and operations by making data easily available to your teams and applications while keeping it safe and secure

Streamline Digital & AI transformation and accelerate the pace of data- and analytics-driven innovation in your business

Gartner predicts that by 2025, 80% of organizations that seek to reinvent and expand their business through Digital and AI transformations will falter due to the outdated approach to data governance. Chief Data Officers (CDOs) also recognize this, with an MIT CDOIQ survey revealing that 45% of respondents are looking to democratize data while keeping safety controls in place.

At Provectus, we recognize that a modern data governance practice should balance data access with control. Excessive control leads to data silos and shadow IT systems, compromising data integrity and security. Excessive access runs the risk of data leaks. Provectus’ Data Governance Services help maintain a perfect balance, instilling trust in data while facilitating innovation and ensuring data protection.

Benefits of Data Governance

Data governance is a comprehensive set of methodologies and standards for managing data throughout its lifecycle. It impacts the people handling and using data, the processes they adhere to, and the tools they utilize.

Efficient Decision-Making
Business users across your organization can quickly and easily access essential data, empowering them to engage with and serve customers, innovate on new and existing products and services, and capitalize on opportunities for driving business value.
Improved Regulatory Compliance
Strong data governance practices enable your organization to avoid noncompliance risks and proactively implement new regulations. This is key in a regulatory environment that prioritizes prevention of data leakage and misuse, despite data silos.
Agile Risk Management
Data governance mitigates the risk of sensitive data exposure to unauthorized entities, breaches from external adversaries, and risks of insiders accessing data beyond their purview. Complete visibility over all data entities makes it easy to manage risks.
Cost-Efficient Resource Management
Efficient data management streamlines resource utilization. By eliminating data access and control inefficiencies, such as data duplication and silos, your organization can avoid unnecessary expenditures on costly hardware and cloud compute resources.
Strong Relationships with Clients
Auditable compliance of cross-organizational processes with internal and external data policies ensures that your organization can efficiently build trust with customers and partners, fostering strong business relationships.
Controlled Data Democratization
Robust data governance brings control to data democratization. It enables your personnel to access the data they need more easily, while ensuring its use does not compromise security or integrity.
Eight Keys to Data Governance

Data governance is not the domain of a single department. It is vital for every division of your organization. To successfully propel data governance best practices into action, it is important to focus on the following key aspects.

Data Discovery

The process of finding, understanding, and organizing data assets within an organization. Discovery offers a complete overview of where data is stored, its description, and information about its purpose and ownership.
Data Lineage

Provides insight into the data journey throughout its lifecycle, tracking its origins, transformations, dependencies, and final destination. It helps in comprehending the movement and evolution of data within the system.
Data Quality

Ensures accuracy, consistency, reliability, and relevance of data for its intended purpose. Effective management of data quality helps prevent errors down the line, and guarantees reliable insights for business.
Data Glossary

Acts as a centralized dictionary that helps define and catalog terms and entities related to data. It ensures uniformity in data terminology, making it easy for everyone in the organization to stay on the same page.
Data Security

Enables organizations to lay the groundwork for managing, controlling, and restricting access to monitored data assets. It establishes security policies, ensures adherence to those policies, and protects sensitive data.
Data Modeling

Focuses on designing, building, and implementing structured data frameworks and representations. Its goal is to set up data contracts and closely monitor compliance, to ensure data consistency and reliability.
Data Cost

Deals with the economic aspects of data storage, data processing, data transfer, and more. It assists organizations in managing and optimizing the costs associated with their data infrastructure at all levels.
Master Data

Master Data Management is crucial for operational efficiency and decision-making. It involves managing reference data, which organizes and standardizes other data entities through lists and hierarchies.

Reflecting on the evolution and growing complexity of data environments, it is clear that data governance is more than just a set of policies or security measures. It is a dynamic strategy aimed at ensuring data integrity, usability, and value across an organization. This comprehensive approach becomes even more crucial as we consider the diverse and sophisticated challenges in today's data governance landscape.

Provectus provides a cutting-edge data governance framework that enables
enterprises to unlock the value of data across all eight aspects,

Data Governance at Provectus

The practice of data governance at Provectus is much more than just a set of policies and security measures. It is a dynamic and proactive strategy for ensuring the integrity, usability, and at-scale value of data across your organization.

Data Governance Challenges We Address

The Provectus framework for data governance addresses major challenges that impede an organization's ability to utilize a modern data stack in ever-evolving business and technology environments.

A constantly growing number of data sources and data products that enterprises have to use in operations
An increased workload for engineers due to the diversity and volume of data that needs to be managed
A greater variety, volume, and variability of data, available at earlier stages of company development

The cloud presents vast opportunities for effectively addressing data governance challenges and accelerating development and decision-making. While businesses should embrace the cloud, they must also acknowledge and adapt to its unique challenges with innovative approaches, skills, and tools.

The advancement of AI/ML, particularly Generative AI, underscores data as
a key business differentiator, elevating the significance of data governance
in the cloud.

Data Governance Solutions We Offer

Data governance serves as a catalyst for achieving data- and AI-driven objectives, executing competitive strategies, and creating business
value at scale. We provide a suite of solutions tailored to assist organizations at various stages of their data maturity journey.

Data Strategy Development

Provectus categorizes its data strategy approach
into three distinct segments:

Data Transformation: Enhancing data platforms and advancing data maturity.


Data Expansion: Broadening data platform capabilities and maturing processes in data management.


Data Modernization: Transitioning from traditional to modern cloud-based data infrastructures.

With over 13 years of expertise, Provectus guides businesses through every stage, each requiring tailored approaches — from preserving governance during modernization to introducing innovative tools in transformation, and broadening features in expansion. 

The end goal is an AI-driven intelligent data platform, enabling smarter, more strategic operations through advanced solutions like Command Centers, Control Towers, and Digital Twins.

Data Governance Foundation

Provectus takes a comprehensive approach to imbuing data governance into
every project, focusing on processes, people, and tools:

Processes: Tailored for each organization, our process management involves stakeholder agreement, clear responsibility chains, and custom strategies for different stages of data strategy — modernization, transformation, and expansion. Key aspects include integrating experts early, training, maintaining governance standards, adjusting to new requirements, and expanding governance as the business grows.


People: We emphasize the connection between policy-makers, business implementers, and technical executors. With extensive experience in data and AI-driven solutions, we help streamline processes, develop data strategies, and implement governance practices. Our expertise spans five integrated practices: Data, Machine Learning, Data Quality, DevOps, and General Application Development.


Tools: Provectus is dynamic and unbiased in tool selection, focusing on the best fit for business challenges. We have developed tools like Open Data Discovery (ODD), Kafka UI, Swiss Army Kube, and Data Quality Gate, and contribute to platforms like Great Expectations and Feast.

Provectus's approach is marked by customizability, strategic alignment with business goals, and a commitment to open-source contributions.

Data Governance Practice Assessment

Organizations struggling on their data governance journey may need to re-
assess their strategy. Provectus can conduct such assessments, helping to set
up the correct processes, train staff, and implement the right tools.


  • Assessment of data (data inventory and categorization)
  • Exploring the mapping and migration strategy, figuring out data transformations
  • Looking into data discovery and observability components
  • Checking data integrity and data quality after migration, looking for silos, and ensuring continuous monitoring
  • Ensuring that a feedback loop is in place, setting up mechanisms for feedback incorporation
  • Assuring adherence to data governance principles and best practices
  • In AI/ML use cases: Data cleaning routine, Feature store work, Version control, ML pipeline integration, and Monitoring & Maintenance
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  • Data Stewards — implement and check organizational policies, oversee data quality and categorization, check for data relevance and consistency
  • Data Architects — handle the data modeling work
  • Data Engineers — manage data migrations and data transformations (processing, integration, etc.)
  • Data Quality Engineers — ensure the accuracy, consistency, and reliability of data
  • Data Scientists — engineer features, and adapt and align data for ML models
  • AI/ML Engineers — design, build, train, and fine-tune systems using the data
  • MLOps Engineers — integration of data components, ML pipelines, user applications, and more.
  • DevOps & IT — help with the integration and utilization of a modern data stack, handling various technical challenges
  • Business Analysts — offer insights on specific features and the overall performance of the system
  • End-users & Stakeholders — provide feedback for the system
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  • Cloud services from AWS, Microsoft Azure, GCP, Snowflake, Databricks, etc.
  • Third-party, open-source solutions and tools for every aspect of the data governance   maturity journey (e.g. Open Data Discovery ODD for data discovery, data glossary, data lineage, data quality and data modeling)
  • MLOps platforms like MLflow, Kubeflow, and Provectus MLOps Platform

The Data Governance Charter serves as a blueprint for effective data governance, outlining roles, principles, and decision-making
frameworks. It offers a roadmap for achieving aligned, transparent, and efficient data governance.

Data Governance for AI/ML

As an AI-first consultancy, Provectus places significant emphasis on data
governance in every AI/ML project, ranging from the development of AI
applications tailored to specific use cases, to ML infrastructure development,
and extensive AI transformations.

Our approach includes the following:

  • Consideration of data governance is integrated into every AI/ML Transformation Canvas
  • We prioritize security, ethical integrity, and unbiased approaches in AI/ML applications
  • For specialized AI/ML solutions such as Retrieval-Augmented Generation (RAG) systems, key elements include managed routing, zero and few-shot prompting, data quality enrichment, and leveraging Knowledge Graphs.

Our Data Governance for RAG encompasses all eight key elements of data success in enterprises, ensuring that your AI/ML projects
are built on a solid, reliable data foundation that helps differentiate your business among the competition.

Managed Services for Data

Any data initiative, whether it is migrating to the cloud, establishing a BI &
Analytics department, or adopting AI/ML, is a continuous process that requires
ongoing support. Provectus offers a comprehensive suite of Managed Services
that cover every aspect of the data journey.

Managed Infrastructure: Our service simplifies cloud infrastructure management for your applications, ensuring top-notch performance, security, and cost-efficiency.


Production Support: We ensure optimal performance and reliability for your applications in production environments, minimizing potential disruptions.


Managed Data Platform: Our service streamlines the management of your data platform, guaranteeing unparalleled performance, robust security, and economical solutions.

Provectus Data Governance Framework
Provectus implements a unique data governance framework that helps us integrate data governance best practices into each initiative across modernization, transformation and expansion. Addressing all technical aspects of data governance, we enhance clarity, security and efficiency.
Open Data Discovery (ODD) exemplifies Provectus’ commitment to filling gaps in data governance solutions. Launched in 2021 as an open-source tool, ODD quickly evolved beyond its initial discovery function to such data governance components as Data Lineage, Data Quality, and Data Glossaries. We are on track to include Data Modeling, Data Security, Data Cost, and Master Data, effectively covering the full spectrum of Data Governance needs.