Do you remember the time when Knowledge Management was popular? I’m old enough to remember that… Just to grab some history, navigate to KM topic in Wikipedia for a refresher:
KM efforts have a long history, to include on-the-job discussions, formal apprenticeship, discussion forums, corporate libraries, professional training and mentoring programs. In terms of the enterprise, early collections of case studies recognized the importance of knowledge management dimensions of strategy, process, and measurement (Morey, Maybury & Thuraisingham 2002). Key lessons learned included: people and the cultural norms which influence their behaviors are the most critical resources for successful knowledge creation, dissemination, and application; cognitive, social, and organizational learning processes are essential to the success of a knowledge management strategy; and measurement, benchmarking, and incentives are essential to accelerate the learning process and to drive cultural change. In short, knowledge management programs can yield impressive benefits to individuals and organizations if they are purposeful, concrete, and action-oriented.
The KM topic has always been an interesting one, and also, a complicated one. Not many companies have succeeded to bring it to the form of business and actionable practices. However, things are going to change, and in a very interesting perspective. Navigate to the following CNET news item: Google plans major revamp for search engine. Google is embarking into something they call semantic search. The following passage is interesting:
The plan for the revamp isn’t necessarily to swap out the current keyword-search system but rather to provide more relevant results. This process will work by using technology called “semantic search.” With semantic searches, people’s searches will be better matched with “entities”–or people, places and things–which the company has been building over the past two years, reports the Journal. Google is basically building an infrastructure layer or a knowledge graph that would underlie many aspects of Google, a spokesperson told CNET. The idea is to make more possibilities with search using these entities.
Knowledge Graph. This is where things get interesting. Let’s leave aside, for the moment, Google’s business reasons. Data is becoming more complicated. For the last 3-4 years the complexity of data in the internet has increased significantly. To keep up with the complexity, Google started exposing “semantic pipes” to handle the relationships and dependencies among data. It is related to the acquisition of Metaweb a few years ago, which was supposed to provide more “semantic data” about the web to Google.
You may be wondering how these things are related to Inforbix and product data. This is how: complexity! The level of product data complexity is very high. To keep up and serve product data applications with relevant information Inforbix built a platform that helps extract, process and integrate product data coming from multiple data sources. Think about it as a knowledge graph of product data, aka “linked product data.”
In my view, the future of data management is moving from single data to a network of data. Knowledge graphs are one of the elements of these data networks. They help one understand important data relationships and dependencies. As a result, it enables better decision making. I leave you with a screen shot of an Inforbix data snippet that, like a Knowledge graph, collects all the related elements from the desired data network, in this case, a SolidWorks drawing with links to important data dependencies.
pic courtesy digitalart / FreeDigitalPhotos.net