This course provides an introduction and application to the principles and practices of developing information architecture (IA).
The course will present and demonstrate IA and its connection to knowledge management (KM) and enterprise content management (ECM), with additional advanced topics where IA is making an impact, such as big data analytics).
Have you ever experienced a situation when you just can’t find that document in your content management system or a specific job aid, standard operating procedure, or knowledge article in your knowledge repository?
Maybe you’re using a system or website where the navigation and labeling don’t match what you do or how you perform your job. Or worse, your organization has different names for the same or similar content and you are not sure you found, or are using, the correct content.
Perhaps your organization is beginning a big data analytics initiative and you need to prepare (curate) your content so that tools such as IBM Watson™, Hadoop™, Spark™, and MongoDB™ will be effective at analyzing your unstructured data.
A proven cure for these issues is to implement an information architecture (IA) that will:
- Drive a user-centric taxonomy, metadata, and associated keywords to enable consistent labeling, organization, categorization, and “findability” of your content.
- Enable big data analytics to exploit relationships and synergies between your data and facilitate your organization’s ability to make decisions utilizing the full spectrum of your big data sources.
- Content managers needing to grow in the field of IA and ECM
- User Interface/Experience Designers of CM tools and KM tools (such as eGain, Oracle KM, IBM, and SharePoint)
- Search analysts and information classification specialists
- Content curators working with big data analytics and IoT
- Anyone with a library science background or records management background wanting to understand more about IA
- Information Architecture principles: content modeling, building taxonomies, understanding metadata development, and use
- Conducting the card sort
- Search engine optimization (SEO)
- IA and the user experience
- Content governance principles and practices
- Incorporating IA in your knowledge
- Management and enterprise content
- Management strategies
- IA in big data analytics
- Upon completion of the course, participants will be able to:
- Understand the principles of IA
- Understand how to develop and apply content model, taxonomy, and metadata schema
- Understand the use and application of metadata
- Understand the principles of card sorting and how to conduct a card sort
- Understand how IA plays a key role in search and the overall user experience
- Understand how to apply IA to KM and ECM strategy
- Understanding content governance and its role in IA
- Understand how to apply IA to curate content for big data analytics
There are four ways to take this class. Please choose an option below for more details.