Enterprise Information Architecture: Empowering AI in the Digital Workplace

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Search is an essential component of the digital workplace. The Digital Workplace is an ecosystem of information that is managed in multiple systems, exposed in multiple experiences, and needs to meet the needs of a wide range of users. This information drives decision-making, analytics, and knowledge sharing across the organization. When your information architecture, taxonomies, and metadata are implemented across the enterprise, the power of AI driven search is unlocked.

Technology

Gary Carlson
GARY CARLSON
Principal & Co-Founder,
Factor
EMPOWERING AI IN THE DIGITAL WORKPLACE
• Experience
Large scale enterprise information management, taxonomies,
metadata projects
• Industries
E-commerce, manufacturing, life sciences
• Interest
Organizational change in complex information environments
The intersection of search, AI, KM, etc with taxonomies, ontologies,
and knowledge graphs

ABOUT FACTOR
Factor is an Enterprise Information
Architecture, UX and Taxonomy
Consultancy.
We help customers gain control of their
information ecosystems by unifying
content and information across
business units, processes and
technologies.
This improves outcomes, data quality
and facilitates easier implementation of
Search, AI, Analytics, Knowledge
Management, and experiences

Enterprise Information Architecture
supports unified definition of
information across …
Systems Processes Workflows

Enterprise
Multiple ● Systems
● Organizational units
● Personas
● Workflows
● Interfaces
● Regulatory and Compliance
requirements

●18+ technology systems in the
marketing stack
●$2B+ annual marketing spend
Fortune 50 Technology
Manufacturing Company

● Unable to assess effectiveness of
marketing campaigns without
‘mob’ of people
● Data was unreliable despite
spending tens of millions of
dollars on best of breed
technology marketing stack
● Extremely difficult to drive
analytics across campaigns or
systems
● No central repository for
modeling campaign definitions.
Fortune 50 Technology
Manufacturing Company

What we found:
“A drunken bowl of
spaghetti”
Fortune 50 Technology
Manufacturing Company

What we built
Systems at Play Information Model
Campaign
Industry
Geography
Audience
Location
Funnel Stage
Target
Expiration Date
Taxonomies Metadata
Collaboration
On-site search
MDM
CRM
DAM 1
DAM 2
Personalization
Analytics
Google Analytics
Community
Management
Tag Management
Jira
.com CMS
TV
SEO
Media
Email
Data Lake
PIM
Ad Server
Demand Management
Platform

What is an Information Layer?
● It’s how you define your content, data, and other
information assets.
● It’s the information that gets implemented in your
technical layer and expressed in your experience
layer.
● It drives your customer experience, your digital
marketing, operational efficiency, business
analytics, and more.
● A unified information layer allows your
organization to align around one voice and a
common vocabulary.

How we built it
Business
Goals
UX Assessment
Competitive Assessment
User Research
Taxonomy & Metadata
Assessment
Analytics Assessment
Content Assessment
Governance/Workflow
Assessment
Technical Systems
Assessment
Evaluate current
state, capabilities and
pain points
Map Existing
Information Assets
and Analytics
Technologies,
Systems and Tools

Results
● Increased data quality within and across systems
● Ability to build and expand Search and AI
● Better and more timely information for business decisions
● Easier and faster onboarding of new systems, business units, and
acquisitions
● Transparency and governance

Enterprise IA Directly Transfers to
Search and AI
Everything that goes into building
an enterprise information
architecture model has a direct
impact on AI powered search
● Clean and consistent data within
and across systems
● Information better aligned with
organizational goals
● Governance and maintenance

Lucidworks Fusion Directly Supports
Enterprise IA
A virtuous cycle. Core Fusion
functionality provides key insights
into the strength and health of
information. These insights, when
incorporated into the information
layer help increase the overall health
and quality of your information.
● Entity Extraction
● Search Analytics
● Clustering and category identification
● Machine Learning
● Recommendations
● Document classification
● Testing
● Head / Tail analysis

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The microservices honeymoon is over. When starting a new project or revamping a legacy monolith, teams started looking for alternatives to microservices. The Modular Monolith, or 'Modulith', is an architecture that reaps the benefits of (vertical) functional decoupling without the high costs associated with separate deployments. This talk will delve into the advantages and challenges of this progressive architecture, beginning with exploring the concept of a 'module', its internal structure, public API, and inter-module communication patterns. Supported by spring-modulith, the talk provides practical guidance on addressing the main challenges of a Modultith Architecture: finding and guarding module boundaries, data decoupling, and integration module-testing. You should not miss this talk if you are a software architect or tech lead seeking practical, scalable solutions. About the author With two decades of experience, Victor is a Java Champion working as a trainer for top companies in Europe. Five thousands developers in 120 companies attended his workshops, so he gets to debate every week the challenges that various projects struggle with. In return, Victor summarizes key points from these workshops in conference talks and online meetups for the European Software Crafters, the world’s largest developer community around architecture, refactoring, and testing. Discover how Victor can help you on victorrentea.ro : company training catalog, consultancy and YouTube playlists.

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Enterprise Information Architecture: Empowering AI in the Digital Workplace

2. Gary Carlson GARY CARLSON Principal & Co-Founder, Factor EMPOWERING AI IN THE DIGITAL WORKPLACE • Experience Large scale enterprise information management, taxonomies, metadata projects • Industries E-commerce, manufacturing, life sciences • Interest Organizational change in complex information environments The intersection of search, AI, KM, etc with taxonomies, ontologies, and knowledge graphs

3. ABOUT FACTOR Factor is an Enterprise Information Architecture, UX and Taxonomy Consultancy. We help customers gain control of their information ecosystems by unifying content and information across business units, processes and technologies. This improves outcomes, data quality and facilitates easier implementation of Search, AI, Analytics, Knowledge Management, and experiences

4. Enterprise Information Architecture supports unified definition of information across … Systems Processes Workflows

5. Enterprise Multiple ● Systems ● Organizational units ● Personas ● Workflows ● Interfaces ● Regulatory and Compliance requirements

6. Let us tell you a story...

7. ●18+ technology systems in the marketing stack ●$2B+ annual marketing spend Fortune 50 Technology Manufacturing Company

8. ● Unable to assess effectiveness of marketing campaigns without ‘mob’ of people ● Data was unreliable despite spending tens of millions of dollars on best of breed technology marketing stack ● Extremely difficult to drive analytics across campaigns or systems ● No central repository for modeling campaign definitions. Fortune 50 Technology Manufacturing Company

9. What we found: “A drunken bowl of spaghetti” Fortune 50 Technology Manufacturing Company

10. What we built Systems at Play Information Model Campaign Industry Geography Audience Location Funnel Stage Target Expiration Date Taxonomies Metadata Collaboration On-site search MDM CRM DAM 1 DAM 2 Personalization Analytics Google Analytics Community Management Tag Management Jira .com CMS TV SEO Media Email Data Lake PIM Ad Server Demand Management Platform

11. What is an Information Layer? ● It’s how you define your content, data, and other information assets. ● It’s the information that gets implemented in your technical layer and expressed in your experience layer. ● It drives your customer experience, your digital marketing, operational efficiency, business analytics, and more. ● A unified information layer allows your organization to align around one voice and a common vocabulary.

12. How we built it Business Goals UX Assessment Competitive Assessment User Research Taxonomy & Metadata Assessment Analytics Assessment Content Assessment Governance/Workflow Assessment Technical Systems Assessment Evaluate current state, capabilities and pain points Map Existing Information Assets and Analytics Technologies, Systems and Tools

13. Results ● Increased data quality within and across systems ● Ability to build and expand Search and AI ● Better and more timely information for business decisions ● Easier and faster onboarding of new systems, business units, and acquisitions ● Transparency and governance

14. Enterprise IA Directly Transfers to Search and AI Everything that goes into building an enterprise information architecture model has a direct impact on AI powered search ● Clean and consistent data within and across systems ● Information better aligned with organizational goals ● Governance and maintenance

15. Lucidworks Fusion Directly Supports Enterprise IA A virtuous cycle. Core Fusion functionality provides key insights into the strength and health of information. These insights, when incorporated into the information layer help increase the overall health and quality of your information. ● Entity Extraction ● Search Analytics ● Clustering and category identification ● Machine Learning ● Recommendations ● Document classification ● Testing ● Head / Tail analysis

16. Questions?

17. THANK YOU

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