ovaledge-new-logo
BOOK A DEMO
Group 6033

DATA GOVERNANCE

Take an Outcome-Focused Approach to Measurable Success

Initiate data governance with high-priority outcomes and and increase scope as demand grows.

Book A Demo
Hero_V2 1

TRUSTED BY CUTTING EDGE COMPANIES TO GOVERN THEIR DATA

unnamed (8)
Untitled (2000 × 1000 px) (51)
Untitled (2000 × 1000 px) (54)
J&J Logo
Farmers Insurance
globe
getty
Naranja Logo

Our Distinctive Approach

Follow a four step approach that is filled with unique differentiators.

1. Establish a Governance Framework

2. Build & Curate Your Catalog

3. Establish Controls & Workflows

4. Enable Consumption & Collaboration

Group (5)
Group (6)
Vector (18)
Group (7)

Set outcomes based on client context and priorities, assign roles and responsibilities, identify activities to implement the set outcomes, & establish measurements.

Smartly scope your Data Catalog curation based on your prioritized outcomes. There are three different curation options to choose from, depending upon your unique context.

Initiate processes and controls to maintain an up-to-date catalog and progress outcomes.

Ensure you can consume data without fear of violating data policies and collaborate in-platform to gather locally-obtained knowledge from subject matter experts.

Our Distinctive Approach

Follow a four step approach that is filled with unique differentiators.

1. Establish a Governance Framework

Group (5)

Set outcomes based on client context and priorities, assign roles and responsibilities, identify activities to implement the set outcomes, & establish measurements.

2. Build & Curate Your Catalog

Group (6)

Smartly scope your Data Catalog curation based on your prioritized outcomes. There are three different curation options to choose from, depending upon your unique context.

3. Establish Controls & Workflows

Vector (18)

Initiate processes and controls to maintain an up-to-date catalog and progress outcomes.

4. Enable Consumption & Collaboration

Group (7)

Ensure you can consume data without fear of violating data policies and collaborate in-platform to gather locally-obtained knowledge from subject matter experts.

1. Establish a Governance Framework

Build a customized data governance program based upon your context and priorities.

2.1
Prioritize Outcomes

Prioritize from a comprehensive set of outcomes:

  • Data Quality & Trust
  • Regulatory Compliance
  • Privacy Compliance
  • Data Literacy
  • Productivity Improvement
  • Data Access & Security
Define Roles & Responsibilities

Establish clear ownership, stewardship, and accountability for all the data in your company.

Identify Activities

Scope your activities based on your priorities, bandwidth, and data context. Key activities to consider:

  • Lineage
  • Relationships
  • Locally Obtained Knowledge
  • Business Glossary
  • Classification
  • Policies
  • Quality Rules
  • Anomaly Detection
Determine KPIs

Ensure the program’s success by establishing key metrics to measure progress and drive continuous improvement.

Hourly expert consulting services are provided to guide you throughout the entire process.

2. Build & Curate Your Data Catalog

Smartly scope your data catalog curation: Decide what to curate where.

OvalEdge offers proprietary tools to assist curation scoping.

Choose from Best-Practice Options

3.1

Consumption-Led Curation

Consumption-led curation is suitable for companies who are new to digital transformation and may not have a fully formed data governance program.

Consumption-Led Curation

Crowdsource curation by collaboratively asking questions, documenting answers, and prioritizing assets through popularity measurements.

3.2

CDE-Led
Curation

CDE-led curation is ideal for companies reporting to regulatory agencies where finding, classifying, and protecting CDEs is crucial.

CDE-Led
Curation

Curate critical data assets by analyzing the data ecosystem to find critical data elements (CDEs).

3.3

Consolidation-Led Curation

This strategy accommodates existing data governance programs migrating from a legacy tool to a data catalog.

Consolidation-Led Curation

Consolidate existing curation efforts by formalizing existing, disparate curation into one data catalog.

3. Establish Controls & Workflows

Progress outcomes and maintain an up-to-date catalog through automating processes and establishing controls. The following are only three examples of many throughout the OvalEdge application:

Data Product Development

For a reliable, single source of truth, utilize workflows to keep the data catalog up to date automatically amidst company developments.

Build Lineage 1 (1)

Data Quality Improvement Lifecycle

Monitor data quality over the course of its lifecycle from the moment a quality issue is reported by a data consumer to the end of its remediation.

 

Identify > Prioritize > Analyze > Improve > Control

Centralize Data 1 (1)

Data Access Requests

Expedite data access requests through customizable workflows that route access requests to the correct parties.

Build Lineage 1 (3)

OvalEdge has built-in controls and integrations with various source systems/tools - like JIRA, ServiceNow, and PoweBI - to ensure support for any processes you implement.

4. Consume & Collaborate

Leverage these features to consume data without fear of violating data policies. Collaborate in-platform to gather locally-obtained knowledge from subject matter experts.

  • Data Catalog
  • Browser Extension
  • AskEdgi
  • Query Sheet

The data catalog is the pillar of the platform that enables metadata curation, searchability, and collaboration.

Data Discovery 1

The Chrome browser extension enables our users to gain easy access to their governed business information while outside of the OvalEdge Data Governance platform.

Browser Extension 1

AskEdgi is your in-platform assistant who answers questions based on the metadata available in your instance of OvalEdge.

AskEdgi 1

OvalEdge’s Query Sheet module facilitates ad hoc analysis from the source system using drag-and-drop functionality for non-technical users.

Query Sheet 1

Hear From Our Customers

"OvalEdge stands out for its holistic approach, providing everything from business glossary to data lineage, all seamlessly integrated. The auto-lineage feature saves us months of work, enabling us to quickly understand data flows and address issues at the source. OvalEdge allows us to standardize and govern our data efficiently, even with a small team, supporting our growth while reducing errors and improving data quality."

Sergei Vandalov

Senior Manager, Data Governance & Analytics at Bedrock

Read More

“Previously, obtaining access to data was a lengthy and manual process with email and Slack communications that could take weeks. With OvalEdge in place, this process was streamlined, enabling access to be granted in just minutes to over 45,000 employees.”

Project Manager

Read More

Featured Resources

Guide

Data Governance Platform Comparison Guide

Whitepaper

Implementing Data Governance: A Practical Guide

Webinar

Data Governance Frameworks

Blog

Finding the Right Data Governance Tool in 2025

Whitepaper

Building a Business Case for Data Governance

Webinar

Data Governance in Banking

Blog

See the entire backlog of OvalEdge blogs

Frequently asked questions

Do you have any questions about data governance?

What is a data governance framework and how do you establish one?

A data governance framework essentially is the plan for how to implement data governance within the organization. It details, in writing, processes and procedures, roles and responsibilities, and the roadmap. The following components help define a well-rounded data governance framework:

  • Why: Create a charter document that outlines responsibilities and boundaries of data governance activities that align with the organization’s priorities. 
  • What: Define the core components and functionalities data governance will provide as a service to the organization. 
  • Who: Formalize roles and responsibilities as they relate to data governance.
  • How: Define the processes and procedures that will facilitate the goals defined in the charter document.
  • When: Create a roadmap based on the data governance framework to stay on track.
How can organizations build a data governance program tailored to their context and priorities?

It’s important to note that a fully fledged and optimized data governance program takes time. That’s where smart scoping helps. Prioritize your data governance program based on what is achievable with your current capacity and focus on the outcomes your organization needs to drive your roadmap. Most data governance initiatives struggle because the scope of the initiative is greater than the bandwidth required to implement it.

Why is clear ownership important in a data governance program?

The data governance program will not survive without clear ownership. While it might sound dramatic, assigning owners and stewards gives subject matter experts the opportunity to contribute to the shared knowledge of the organization through their participation in data governance.

Why is maintaining an up-to-date data catalog important?

To answer the question with another question: Why have a data catalog that is searchable by users when the information available isn’t current? If the data catalog is to be a single source of truth that empowers data-driven decision-making, it must be up-to-date.

What types of controls can be used to maintain a data catalog?

Automation plays a significant role in maintaining a data catalog such as scheduling crawling and profiling. More complex jobs can be created to optimize workflows needed to stay up-to-date.

Why is it important to collaborate in-platform for data governance?

A single source of truth doesn’t appear overnight! Collaborating to answer questions enriches the data catalog as other users can view the history of in-platform discussion for a data object and gain further insights from subject matter experts. If extra information is uncovered through the collaboration features, it can even be added to the data object’s metadata.

How can organizations ensure data consumption without violating data policies?

Data policies are enforceable through a combination of measures within the data governance platform. Here are just a few examples of how OvalEdge helps implement data policies within the platform:

  • Configurable AI models allow you to quickly find and classify PII and other sensitive data across the entire data ecosystem, and it learns as recommendations are accepted and rejected.
  • Role based access controls ensures only those with the proper role can view certain data assets.
  • Robust access requests and workflows creates a streamlined process that includes how long someone is granted access.
What role do data policies play in enabling secure data consumption?​​

Data policies allow for high data discoverability within the data catalog. Users can still search and view the available metadata, and a user can request access to the data if they do not have the correct permissions to view it. Configured access requests ensure the right person(s) are notified who can assess for a valid business reason and grant access.

Are you ready to discover your competitive edge?

Book A Demo