Data Conception

Your basis for successful project realisation.

Design processes, data structures and data models before you start your data project. Whether migration project, data governance, creation of a unique customer ID or a group-wide business partner - benefit from our expertise in data conception for your individual project.

Customized data design for ‘thinking in data’

Data conception is an integral part of data management. It centres on the planning and design of data structures and data models. Ideally, it takes place in the run-up to customer data management projects such as data migration, data governance or data quality initiatives.

When implementing such projects, traditional project management thinking is no longer sufficient. Rather, it is about a new ‘thinking in data’. Having prepared a data concept is the prerequisite for this. It provides answers to these questions:

Contents

What is the initial situation with the source data (ACTUAL)?
How should the data be structured in the future (TARGET)?
What will the future data model look like?
How do I transfer the data into this new data model?

For which processes or applications is the data required?
Which data flows already exist and which need to be created?
Which data fields need to be linked?

"As experts in customer master data, we get the most out of your data and help you understand your customers."

Sebastian Krebs, Head of Customer Success at Uniserv

"As experts in customer master data, we get the most out of your data and help you understand your customers."

Sebastian Krebs, Head of Customer Success at Uniserv

Data conception for your specific challenges

For example, you are faced with the task of migrating data to a new system or setting up data governance, creating a unique customer ID or setting up a group-wide business partner. Or you have another customer data or data quality project ahead of you. This means a lot of change, especially in terms of processes, data streams and data. How do you proceed?

Exactly! Your first step is making a data concept. This means you have an initial state and a target state. You need to consider what is already in place and how you can make the transition to the target state. To do this, many different strands of action need to be linked to form a whole. For example, business processes that are currently in use need to be recorded. It is also important to understand which departments are involved and where which data is required.

A sales department, for example, is interested in sales figures, purchase histories and credit ratings. A finance department, on the other hand, needs payment data and the relevant contact persons. These different views of one and the same data record and the different data requirements make the complexity clear. Precise work is therefore urgently required. The Uniserv process model for data conception is designed precisely for this purpose. It structures your data conception. It ensures that you do not forget anything important and always maintain an overview.

Measure data quality - 5 tips for more transparency

When it comes to the quality of your own data, there is often nothing more than a vague gut feeling. So how do you make it all measurable?

Read the Uniserv business whitepaper 'Measurable data quality' to find out how you can switch from gut feeling to transparency when it comes to data quality and put it to the test.