Data Assessment -
Raise Your Data Treasure

• Goals and effectiveness:
  Where should AI have a measurable impact and what tacit assumptions about databases are already in the business case? It is about definable effectiveness instead of an endless list of features.
• Data origins and breakpoints:
  Where does data diverge (interfaces, manual intermediate statuses, responsibility)? You provide a self-assessment of quality, timeliness and usability where it affects your planned applications, with a view to the next decision.
• Priority of the projects:
  Which use cases have the highest urgency and where do you suspect the biggest blockade, technically, organizationally or professionally?

It is not an architectural drawing, but a concise, coherent initial assessment:

• a situational picture of how your AI readiness, data quality and scalability statements fit together,
• prioritized directions for action instead of a generic "improve data quality" list and
• a proposal for sensible follow-up steps (such as a results workshop, accompanied individual measures or clarification of a data stream first).

In line with the step-by-step logic under Data Quality & Scaling for AI.

• We do not build any interfaces and do not retrieve any data from your production systems; the evaluation is based on the information you provide.
• The check is not a substitute for auditor-proof proof of compliance, a formal data quality audit against standards or an architecture review of existing lakehouse installations.
• You receive guidance for planning and discussions, no guaranteed KPI plan and no firmly dated delivery object "Gold Layer ready", because the appropriate scope often only becomes apparent when you delve deeper.

The check takes about fifteen minutes, or more depending on how thoroughly you complete it.

No. Terms such as Data Lakehouse or Data Intelligence only help to categorize possible subsequent steps, not to check them in advance.

This is precisely when the initial assessment is worthwhile. You can clarify and implement in greater depth in the workshop or in accompanied measures.

No. The data assessment is more broadly concerned with data-driven use cases and potential. The Data Readiness Check focuses on AI readiness, data quality and scalability as part of this data quality offering under Make Smart.

Because a reliable initial assessment is a fair start and often shows which in-depth service is the next best thing.

By submitting this form, you consent to the storage and processing of your personal data and the Data Readiness Check chat history by doubleSlash Net-Business GmbH. All information on data protection can be found in our Data Protection Declaration.