Data Governance Consulting Services and Solutions

Data is today’s most popular buzz word everywhere and moreover, the need of the hour!

Thanks to numerous sources, organizations and platforms that continuously collect, transmit, transfer, share and maintain data in their respective areas to make it easily available for target end-users. In this continuous data chain, security and maintenance happen to be the most concerning factors for most firms.

The concept of ‘Data Governance’ answers them!

Defining Data Governance

By definition, Data Governance is a program that enables organizations maintain high quality data throughout their data lifecycle, ensuring data security/protection, data availability, data consistency, data usability and data integrity.

As a subset of Data Governance, the Data Management holds accountability to effectively manage and drive data across the enterprise.

Stealthlabs Defining Data Qovernance
Stealthlabs How Data Governance Helps

How Data Governance Helps?

A Data Governance model merely brings people, process and technology to support consistent and effective handling of organizational data across the business chain.

With this strong aim at the core, the Data Governance implementation helps organizations:

  • Mitigate data risks
  • Achieve consistency and effective decision-making
  • Avoid regulatory risks
  • Attain Data Security
  • Implement robust data distribution policies
  • Witness data-driven value
  • Generate quality information
  • Optimize business and employee productivity
  • Eliminate redundancy and rework

Given these benefits, Data Governance can be your next business option for achieving completeness in your data journey.

Looking for Support?

A Data Governance model brings in a strategic shift across and operational levels, and should ideally be a continuous process aligned with every data-related projects at the enterprise level.

But this requires strong domain expertise, and we are right in front of you!

StealthLabs has been one of the early adopters of Data Governance services in the US IT consulting market, with strong technical domain expertise in data security and other data-related service offerings.

Our Identity and Data Management experts provide you with tailored solutions, bringing in consistency and uniformity across your data and processes. By filling the gaps, they boost the scalability of your IT landscape and add to your decision-making abilities.

Our Data Security team will review your existing privacy policies to ensure data protection for internal and external data. Moreover, our Compliance Advisory team will also check your compliance guidelines to avoid data compliance-related challenges.

We establish data-centric models that can drive your digital business and more such benefits are part of our Data Governance framework.

Our Data Governance Services model is comprised of:

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Enterprise-level Governance

Support effective data management and ensure organizational data complies with global regulations

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Process and Controls

Implement require processes and controls that support effective data management

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Holistic View

Post orchestration and management, present the entire data in a holistic view to the whole organization

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Quality Check

Identify measures and necessary implementation to ensure data quality and its continuous improvement

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Metadata Analysis

Perform a detailed metadata analysis for improved data efficiency and enhance process delivery

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Data Protection

Develop policies for data protection and establish processes for monitoring, remediation and reporting in line with regulations

For Data Governance implementation, we adopt a 6-step strategic roadmap including:

  • List Objectives
  • Perform Assessment
  • Define Standards
  • Develop Strategy
  • Identify Metrics
  • Plan Roll-out

StealthLabs Data Governance Services offer you following business benefits:

  • Data consistency
  • Improved data quality
  • Maximized data-driven decision-making
  • Improved business planning
  • Improved accountability
  • Improved understanding of data assets
  • Operational efficiency