top of page

What we do

Enterprise wide processes, roles and technology for using data.

Why

Data is everywhere.
Typically scattered across different systems and departments.

Most organisations experience problems with data. There is not enough data, or too much data, not the right data, they can not trust data, can not make use of data, don't know which data there is or where it lives.

Most also see potential in data,
 it can be useful but legal compliance, storage issues and usability problems are real.   

Disorder is costly. We'll help you sort out the mess. 

Data bubbles
Data Governance

Our projects involve checklists, templates and routines for the individual, as well as large enterprise activities such as architecture and change management. It can be a matter of developing products or services to sell more or to increase internal process efficiency.
 

No matter the nature of your business case, if it involves data, Data Governance is essential.

What

Data Governance is about formalizing and implementing enterprise wide processes, roles and technology for using data. There are many aspects of Data Governance and some of particular importance.

Discovery
You should know your data. Which data you have, where it is stored and how to find it.

Security
You need to have practices implemented to protect data from unauthorized access, disclosure, alteration, and destruction.

Quality
High quality data is key for all of your business and use cases. There should be only one version of the "truth".

Ownership
Ownership of data and data models is essential to ensure consistency across the organisation.

Usability

Your data should be available for your business or use case, big or small. Adding to that, solutions should be easy to use.

How

Data Governance initiatives typically involve three stages: understand, plan and implement. These stages are often non-linear and iterative, which means they may be run in parallel or be repeated as needed.

Stage 1: understand

This stage is about understanding what to achieve and why. This along with analyzing the current Data Governance situation.

In this stage we identify and describe:

  • Business case, context and culture

  • Legal requirements and internal policies

  • Stakeholders and target groups

  • Data entities, flows and models

  • Architecture, tools and integrations

  • Dependencies 

Think BIG but start small. Many organisations are too unspecific in defining their business case.

Stage 2: plan

This stage is about planning the solutionwhat does the wanted Data Governance situation look like when it comes to processes, roles and technology.

In this stage we define and visualize:

  • Scope

  • Risks and cost

  • Data entities, flows and models

  • Architecture and integrations

  • Tools, buy or build?

  • Roles, processes and culture

  • Time and material

  • Success metrics

Use visualization to describe data and talk human. Data Governance lingo can be confusing.

Stage 3: implement

  • Implement tools and integrations

  • Provide support and training

  • Drive adoption and operations

  • Communicate change 

  • Monitor impact

This stage is about making the solution into reality.

Go for iterative and incremental implementation with fast progress and continuous demos.

bottom of page