Pragmatic, fast and robust

Data discovery

We run a data discovery to identify the state of your data governance with a robust and fully documented approach for improving your data management knowledge areas.

What is a data discovery? How long does it run for? What outcome can we expect?

Data discovery phase

What do we do first?

  • We run a data discovery project to identify the state of your data governance.
  • First, we assess the scope of work and agree on a timeline to deliver the data discovery report.
  • We get to know your knowledge areas in data management and underlying organisational data issues.
  • We get to know your people, the roles and departments in charge of data assets and technology.

What we deliver after discovery?

  • The current state of your knowledge areas include the state of your data infrastructure, master data, data quality or data security.
  • The current underlying organisational data issues affecting people and procedures.
  • The list of priorities to implement major improvements throughout your knowledge areas.
  • The list of benefits for all major improvements.
What happens at successful completion of a data discovery?

Data projects focused on knowledge areas

After a successful completion of a data discovery phase, we deliver a presentation and you get a list of knowledge areas improvements. It takes the stakeholders a few weeks to reach consensus on chosen implementation priorities. Datatunnel has a flexible project management approach and we choose for result-driven tasks which consists of a set of projects and subprojects activities.

What project deliverables can you expect from our knowledge areas? How clean is your enterprise data? Your business units might be at an intermediate level to connect their data through a data warehouse or share it under a business intelligence platform. Some of our customers require identifying the enterprise data sources or re-designing existing data models. Our customers decide what data management knowledge areas will offer immediate benefits. We recommend first, then you decide.

A few examples of project deliverables are:

  • A health check of your data governance approach.
  • A data quality methodology to correct your enterprise data.
  • A data modelling project to manage your SQL and NoSQL data.
  • The implementation of a secured data API that offers enterprise data to various frontends.
  • A high-velocity data infrastructure to search your enterprise data.
  • A machine learning system to detect patterns or anomalies in your data.

Project deliverables vary based on our customer priorities. You choose which projects offer immediate benefits.

How do we team up?

We work together

Prior to starting a data project, we identify specific responsibilities and together we appoint relevant roles.

Various business, data, development and IT roles work together in a variety of data management knowledge areas.

Any missing skills are provided with the support of our subject matter experts.

The whole team works towards a common goal and we ensure that every team member is well trained in their role.

The meaning of retaining and sharing knowledge

We transfer our best data practices

Various tools and procedures will connect your enterprise data.

After running a data discovery of a knowledge area, we share our findings with facts and metrics.

We work with you to assess costs and benefits and on the design of the data solution.

We compare best practices and alternative approaches in relation to tool criteria and share with the business, data and IT teams what works best in your company environment and culture.