Product Data Lake went live last month. Nevertheless, we are already planning the next big things in this cloud service for sharing product data. One of them is exactly things. Let me explain.
Product data is usually data about a product model, for example a certain brand and model of a pair of jeans, a certain brand and model of a drilling machine or a certain brand and model of a refrigerator. Handling product data on the model level within business ecosystems is hard enough and the initial reason of being for Product Data Lake.
However, we are increasingly required to handle data about each instance of a product model. Some use cases I have come across are:
- Serialization, which is numbering and tracking of each physical product. We know that from having a serial number on our laptops and another example is how medicine packs now will be required to be serialized to prevent fraud as described in the post Spectre vs James Bond and the Unique Product Identifier.
- Asset management. Asset is kind of the fourth domain in Master Data Management (MDM) besides party, product and location as touched in the post Where is the Asset. Also Gartner, the analyst firm, usually in theory (and also soon in practice in their magic quadrants) classifies product and asset together as thing opposite to party. Anyway, in asset management you handle each physical instance of the product model.
- Internet of Things (IoT) is, according to Wikipedia, the internetworking of physical devices, vehicles (also referred to as “connected devices” and “smart devices”), buildings and other items—embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data.
Fulfilling the promise of IoT, and the connected term Industry 4.0, certainly requires common understood master data from the product model over serialization and asset management as reported in the post Data Quality 3.0 as a stepping-stone on the path to Industry 4.0.
Liliendahl on Data Quality 