Data and Analytics

Data Strategy and Governance

Build a custom framework that allows you to harness your data.

What is Data Governance ?

Data governance is the collection of clearly defined policies, procedures, standards, processes, roles, and responsibilities that ensure the effective and efficient use of data in enabling an organization to achieve its goals. Essentially, an effective data governance strategy defines who can take what action, upon what data, in what situations, and using what methods.

Business drivers will shape the structure of an organization's data governance program, which will in turn inform the strategic, tactical, and operational roles and responsibilities required to carefully control the capture, storage, maintenance, consumption, and destruction of the data across the enterprise. For example, if a business driver in your data governance strategy is to ensure compliance with data privacy regulations, client data will need to be managed securely as it flows through your business. Retention requirements (i.e., history of who changed what information, when and how long you retain client data before destroying it) will be defined to ensure compliance with relevant government regulations, such as the California Consumer Privacy Act (CCPA).
Data governance is about data decision-making. The people, processes, and technology that support those decisions at an enterprise level ensure that data is secure, private, accurate, consistent, available, and usable. Every organization’s data governance program is uniquely tailored to fit the organization’s specific needs and situational demand; however, there are components that remain constant through various frameworks.

Why Data Governance is Important ?

In this age of digital transformation, having a data governance strategy that aligns with your long-term business goals is of paramount importance. Understanding and capitalizing upon your data with a governance plan is one of the best ways to stay ahead of the competition, whether your business is in healthcare, telecommunications, financial services, or any other industry.
As the volume and complexity of data increases exponentially, so does the gap in data management capabilities with the continued absence of data governance.
Brenden McGlinchey | Kenway Consulting
Data Governance Service Lead

Top-Tier Data Strategy Consultants

Develop a world-class data governance plan with our three-step strategy.

#1 Identifying High-Value Use Cases
We start by understanding how a data governance strategy can align with your business’s long-term goals, identifying where our services will be of most value.
#2 6-Part Assessment
After our initial evaluation, we assess your business’s data governance maturity across six important domains. The top priority use cases are discerned and used to create a roadmap for a data governance framework that addresses your organization’s most critical needs.
#3 Turning Plans into Actionables
After a plan is created, we partner with your business to turn this plan into results. From writing anchor and identifier policies, to implementing data governance tools and technologies, we utilize our vast pool of resources and experts to maximize the value of your data to benefit your business in both the short and long-term.
  • Identifying High-Value Use Cases

    We start by understanding how a data governance strategy can align with your business’s long-term goals, identifying where our services will be of most value.
  • 6-Part Assessment

    After our initial evaluation, we assess your business’s data governance maturity across six important domains. The top priority use cases are discerned and used to create a roadmap for a data governance framework that addresses your organization’s most critical needs.
  • Turning Plans into Actionables

    After a plan is created, we partner with your business to turn this plan into results. From writing anchor and identifier policies, to implementing data governance tools and technologies, we utilize our vast pool of resources and experts to maximize the value of your data to benefit your business in both the short and long-term.

Data Governance Pacesetter

Kenway has been named a "data governance pacesetter" by ALM | Law.com Compass Research
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Data Governance Resources

  • BLOG

    Active Data Governance: A Verb, Not A Noun
    The concept of data governance often evokes images of rigid structures, an ‘ivory tower’ of sorts, full of roadblocks and bureaucracy...
    READ MORE
  • CASE STUDY

    Data Governance: The Key to Successful Patient Engagement
    Patient engagement lies at the confluence of two dominant trends in U.S. healthcare...
    READ MORE
  • CASE STUDY

    Automated Data Governance: Why Data Contracts are Key
    Implementing data governance, and keeping it relevant as your data needs change, is an exercise in vigilance...
    READ MORE
BLOG

Active Data Governance: A Verb, Not A Noun

The concept of data governance often evokes images of rigid structures, an ‘ivory tower’ of sorts, full of roadblocks and bureaucracy...
READ MORE
CASE STUDY

Data Governance: The Key to Successful Patient Engagement

Patient engagement lies at the confluence of two dominant trends in U.S. healthcare...
READ MORE
CASE STUDY

Automated Data Governance: Why Data Contracts are Key

Implementing data governance, and keeping it relevant as your data needs change, is an exercise in vigilance...
READ MORE

Frequently Asked Questions 

Data governance is the high-level oversight providing the policies, rules, and structures controlling a business’ data. Data management is related but different, as it is characterized as the day-to-day execution of a good data governance plan.
A data governance framework is a plan that helps businesses capture large amounts of data and capitalize upon it by proper utilization.
Technology plays a large role in the implementation and successful execution of a data governance framework. Since a large proportion of data nowadays is digital, technology can play many varied roles in data governance.
Some of the many benefits of implementing a data governance framework include reducing the operational costs of managing data, mitigating risks that come with incomplete or inaccurate data, and  allowing you to adopt AI more seamlessly.

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