Phases of a master data project
1. Free data audit
- You provide a representative extract of your master data
- We evaluate the data quality according to defined quality criteria and create a data profile for you
- The data profile provides you with analyses of the properties of your master data: Completeness, uniformity, duplicates (selection), enrichment potential, initial evaluation of the product category key (if available)
- You decide on further cooperation
Request your free data audit
2. Data analysis
- Quality evaluation of all master data based on statistical analyses and quality criteria (e.g., completeness, timeliness, accuracy, uniformity)
- Creation of a data cockpit for result visualization
- Development of an action plan for cleanup, classification, and enrichment
3. Data cleansing
- Identification of inaccurate data records
- Similarity check on data duplicates
- Conversion of the original customer data into a normalized intermediate format (data normalization)
- Consolidation and completion of incomplete data sets (data fusion)
4. Data classification
- Taxonomy on request (eCl@ss, CPV, UNSPSC or individual)
- Semi-automated classification approach - statistical and algorithm-based analysis methods
- Manual plausibility check and feedback-based classification process
5. Data enrichment
- Extraction of existing characteristics and attributes
- Targeted supplement of missing data sets
- Harmonization of enriched and extracted data sets
- Creation of the final import file
