Preconfigured templates, Auto Assignment of Class & Characteristics, ISO 8000 and UNSPSC compliant
Data Quality
Data Quality Management is aimed to automate the process of standardization, cleansing & management of unstructured / free text data by utilizing ASA (Auto Structured Algorithms) built on PiLogs taxonomy and the catalog repositories of master data records.
About Data Quality
Analyze the source data content for completeness, consistency, redundancy, standardization, richness, etc
Auto Assignment of Class & Characteristics from the PiLog's Taxonomy to each record
Extract the characteristic values & UOM's from the source descriptions for each record
Extract reference data from the source descriptions such as Part#/Model#/Drawing#/Mnfr/Vendor etc for each record
Bulk review of materials (QC Tools & DQ Assessment)
Auto mapping of source data with PiLog repositories & other reliable sources
The PiLog Master Data Project Management is used for cleansing and structuring of a material master is a highly specialized field, requiring the use of international standards, such as eOTD, USC, EAN, ISO 8000 etc.
Effective cleansing and structuring of a material master consistent and correct application of these standards in large volumes of data requires specialized processes, methodologies and software tools.
The material master forms the basis for a myriad of business objectives. PiLog understands the complex task of translating selected business objectives into master data requirements and subsequently designing a project that is focused on delivering optimal results in a cost effective way
Data Cleansing
How Confident Are You in Your Data’s Accuracy?
If inconsistent, redundant, or inaccurate data is holding your business back, it’s time for a change. Experience the power of iDQM —automated, standardized, and ISO-compliant.
