Reliable analytics require good data quality
- Supplier data have duplicates and are not harmonized
- Material groups and categories are wrongly assigned or categorized as “other”
- Manual corrections are impossible due to the mass of data
Reliable analytics require good data quality
- Supplier data have duplicates and are not harmonized
- Material groups and categories are wrongly assigned or categorized as “other”
- Manual corrections are impossible due to the mass of data
Let the kiresult algorithms prepare your data
With the help of artificial intelligence, we organize your data records by categorizing and harmonization based on transactions.
Build the foundation for analysis and bring a clear structure to your data.
Let the kiresult algorithms prepare your data
With the help of artificial intelligence, we organize your data records by categorizing and harmonization based on transactions.
Build the foundation for analysis and bring a clear structure to your data.
Illustration of our data preparation


Illustration of our data preparation


Want to unlock your data potential?
Receive further information by e-mail.
We offer a free feasibility check, where we identify your data potential and develop initial ideas.
-
Initial call
In a first exchange we discuss your needs. We will contact you to find a suitable time.
-
Analysis
We check the quality of your data structures and derive suitable use cases for our algorithms.
-
First results
We present your identified potentials. Then we define next steps for implementation.
Want to unlock your data potential?
Receive further information by e-mail.
We offer a free feasibility check, where we identify your data potential and develop initial ideas.
-
Initial call
In a first exchange we discuss your needs. We will contact you to find a suitable time.
-
Analysis
We check the quality of your data structures and derive suitable use cases for our algorithms.
-
First results
We present your identified potentials. Then we define next steps for implementation.