We appreciate your shared interest and passion for data telling a story, producing answers with information, and making it easier to understand, find, and re-use the data tsunami we live in. Dip your learning toes into what Google, Amazon, Netflix and many others have discovered it to be a “game changer”. Many more are fast followers!
This is an interactive training webinar on how and why a journey to becoming Data-Centric is the way to future proof information management for the enterprise. The training will give students and faculty a concentrated view into Semantic capabilities, practical learnings of Knowledge Graph application and “hands on” use of Ontology “best practices”. Our full day virtual training program will consist of eight 50-minute sessions with a 10-minute breaks every hour. There will be an hour allotted for lunch – your responsibility.
To increase engagement throughout the training, we ask that you have your video camera on, that you participate in exercises and help to direct the conversation with questions to better understand how you’re absorbing the material. As a preferred prerequisite, we’ll be supplying a quick read introduction to this topic that will give a jump start for facilitating a smoother learning transition. This background reading is not essential but will serve as a contextually relevant pre-learning exercise.
We highly encourage the preliminary self-learning as it will accelerate your appreciation for the data-centric paradigm shift that is taking place as a result of digital transformation. Join the Data-Centric Revolution!
If the one-day training has motivated you to the next tier of learning, it would be a pleasure to have you join us for our annual Data-Centric Architecture forum. Click here for details & registration.
When is it?
January 31, 2021 from 9 am – 5 pm MT
You will connect to the training webinar using Zoom, details will be sent prior to the event.
The course “Becoming Data Centric” gave me a quantum step up in my understanding of how to use the data-centric concepts. The structure of the course allowed for lots of informal discussion and interaction, and participants were encouraged to bring questions. The time went quickly as we went step by step through hands-on exercises to get the feel of how to construct an ontology, use an inference engine, and do queries across multiple graphs created by people in the class. In addition, the course prep and follow-up material are excellent. If you are interested in turning the powerful data-centric theory into transformational practice, take this course.
– Phil Blackwood, AT&T, Enterprise Architect
What is Data-Centric & Why Should You Care?
- Our definition, and the key enabling technology.
- Who is already Data-Centric
- What routes are there to get there?
- What are the economics of data-centric?
- Triples as the fundamental unit of graph databases.
- URIs and their role in Global Identifiers and self-joining data structures.
Sparql & Triple stores
- The different types of graph databases and in particular RDF triple stores
- How triples are created from text?
- How to query a triple store?
- What is a sparql end point?
- Examples of basic queries
Classes and Properties
- Intro to Protégé
- lightweight ontology modeling with classes and properties.
- Example of very simple inferencing
- Introduction and hands on with a few simple restrictions and Boolean class definitions
- Hands on with Protégé.
SPARQL Meta Queries
- How to conduct directed exploration in a triple store?
- How to think about your problem space?
- How to plan a project and where to start?
I came into the “Becoming Data-Centric Training” with a good knowledge of RDF and semantic principles but was pleased to gain a much deeper insight into the theory, tools, and publicly available datasets in this class. Dave’s approach in taking the larger conceptual framework for data-centric design, paired with the hands-on execution of this framework in sample problems was very helpful in solidifying my understanding. I recommend this course to anyone who works with data, as my eyes were truly opened to the future of data as a first-class citizen - where applications simply provide a viewport to the data, as opposed to the current standard for middle and front-tier logic that often discounts the true value that is the facts and data.
-Jay Wall, Director of Partner Enablement, Fluree PBC
Phil Blackwood worked at AT&T as a Lead Systems Engineer and Enterprise Architect for over 30 years, mainly in the areas of service ordering and network management. His current focus is on advocating for data-centric architecture transformation. Phil has a Ph.D. in Pure Mathematics from the University of Virginia and likes to find simple solutions to complex problems. In his spare time, Phil enjoys being outdoors and actively promotes clean energy and action on climate change.
Dave McComb is the President and co-founder of Semantic Arts. He and his team of consultants help enterprises uncover the meaning in the data from their information systems. Semantic Arts guide and coach organizations through implementation “best practices” of Data-Centric principles by leveraging Ontology and Semantic Knowledge Graph capabilities. Dave is also the author of “The Data-Centric Revolution”, “Software Wasteland” and “Semantics in Business Systems”. For 20 years, Semantic Arts has helped firms of all sizes in this endeavor, including Proctor & Gamble, Goldman Sachs, Schneider-Electric, Lexis Nexis, Dun & Bradstreet, and Morgan Stanley. Prior to Semantic Arts, Dave co-founded Velocity Healthcare, where he developed and patented the first fully model driven architecture. Prior to that, he was a part of the problem.