My new website and blog is BeyondPLM. The original post is here.
PLM is certainly dealing with lots of data about products: design, engineering, lifecycle data, manufacturing, processes. When/If you speak to PLM software providers and some big customers you can hear term “Data Warehouse”. DW term is not coming originally from PLM domain and related more to the general purpose databases and data management field.
This is a very commonly used definition of Data Warehouse from Wikipedia:
A data warehouse is a repository of an organization’s electronically stored data, designed to facilitate reporting and analysis [1]. This definition of the data warehouse focuses on data storage. However, the means to retrieve and analyze data, to extract, transform and load data, and to manage thedata dictionary are also considered essential components of a data warehousing system. Many references to data warehousing use this broader context. Thus, an expanded definition for data warehousing includes business intelligence tools, tools to extract, transform and load data into the repository, and tools to manage and retrieve metadata.
Data Warehouse Technologies
The technologies for data warehouse most commonly are coming from database and data vendors related domains. There are multiple methodologies and techniques to organize data and make available. The most known in this field are bottom up and top down design for data warehouse. Most of the data warehouse methodologies are focusing on fast data retrieval opposite to transactional databases. With all bright insight made around the data warehouse, their implementations are very expensive and, in my view, data warehousing technologies are under significant pressure to drop cost and improve the agility of implementations. You can often find multiple data-related implementations that may correspond to data warehousing , such as Business Intelligence, Data Integrations, etc. The newest trends in Business Intelligence are stating that Data Warehousing is ruined and the future BI technologies will bring better solutions in this space. Recently, I had a chance to read a very interesting write up made by TEC – Are Data Warehouses as Dead as the Dodo?, which is exploring a promising future of new BI technologies to replace data warehousing need.
PLM and Data Warehouse
I think, PLM is often using “Data Warehouse” term to underline the power of PLM technologies to manage big amounts of product data. In my view, PLM platforms never took serious steps in the implementation of actual data warehousing. Nevertheless, large PLM implementations done for big aero- and auto- OEMs contain a significant amount of product data that need to be available across the multiple departments and synchronized with multiple applications. You can find an interesting story about Boeing and Airbus PLM data warehousing implementation can be found on TechniGraphics web site. At the time of writing this blog, I could download this paper from the following link. Some interesting numbers from this document- the Boeing Dreamliner data warehouse contains about 16TB of data. PLM needs to deal with large amounts of data. To handle it efficiently seems to be a very interesting problem.
What is my conclusion today? Large PLM implementations need to handle a significant amount of data. Today, DMU implementations are requiring to bring multiple elements of design data to handle analysis and validation of complex products. There are many other product-data related problems that often remained unsolved because of technological complexity. What is the technology available to solve this problem? Is it future HD PLM from Siemens? Or maybe Project Lightning from PTC? Time will show…
Best, Oleg
