Data Platform Assessment


Turn your data into value. Build AI solutions on top of an efficient data platform to improve and automate processes, increase revenue streams and mitigate business risks.

Data science has become a top priority for many industry leaders. There usually is an abundance of ideas on use cases and the value they could generate. However, no data science solutions can be built without a robust foundation. This foundation needs to support all departments of your organization as nowadays, data is too often scattered across the organization in an ad-hoc and inconsistent manner undermining the full potential of your solutions and harming their durability.

To fully exploit the opportunities data offers, this requires an efficient and well thought-out long-term data architecture for the full organization. Unlike what we often witness, this cannot be the responsibility of only business administration analysts.

This Data Platform Assessment will compare your data architecture with the industry best practices and give you an actionable roadmap to step-up your speed of innovation. This roadmap can include technologies such as Azure Synapse, Power BI, Azure Data Factory, etc. A major focus point during our assessment is the co-creation with the various stakeholders to identify the requirements, issues and constraints, so that we draft a roadmap tailored to your needs.

The approach we take is the following:

  1. Assess Assessment of the current state of your data platform and exploration of the data challenges. Identify the data platform processes together with the involved stakeholders, taking into account their requirements.

  2. Analyze Compare the current state with best practices and industry standards. Analyze industrialization of data solutions and data processes to assess the business opportunities and impact on the organization.

  3. Advise Draft an actionable strategy to level-up the data driven approach. Advise on improvement areas, transition path, operational model and the industrialization of data solutions according to best practices and industry standards. Decide on which technologies to use (Azure Synapse, Power BI, etc.).