EIS-Webinar-data.world-collab-2023-02-15.pptx

www.earley.com © 2023 Earley Information Science, Inc. All Rights Reserved.
WEBINAR
WEBINAR
SPEAKERS
DemystifyingKnowledgeGraphs
ApplicationsinDiscovery,ComplianceandGovernance
SETH EARLEY
CEO & FOUNDER
EARLEY INFORMATION
SCIENCE
THANK YOU
JUAN SEQUEDA
PRINCIPAL SCIENTIST
DATA.WORLD

Today’s Speakers
Seth Earley
Founder & CEO
Earley Information
Science
Seth@earley.com
https://www.linkedin.co
m/in/sethearley/
2
Juan Sequeda
Principal Scientist
data.world
Juan@data.world
https://www.linkedin.com/i
n/juansequeda/

Before We Get Started
WE ARE RECORDING SESSION WILL BE
50 MINUTES PLUS
10 MINUTES FOR
Q&A
YOUR INPUT IS
VALUED
Link to recording &
slides will be sent by
email after the webinar
Use the Q&A box to
submit questions
Participate in the polls
during the webinar
Feedback survey
afterward (~1.5 minutes)
Thank you to our media partners : CMSWire & Marketing AI Institute
3

Agenda
• Knowledge Graph Basics – Navigation vs. Classification
• Knowledge Graph Applications
• Data Governance Approaches
• Metrics Driven Decision Making
• Regulatory Compliance
• Getting started
4

Earley Information Science
5
Proven methodologies to organize information and data.
SELL MORE
PRODUCT
SERVICE CUSTOMERS
EFFICIENTLY
INNOVATE
FASTER
1994
YEAR FOUNDED.
Boston
HEADQUARTERED.
50+
SPECIALISTS & GROWING.

Seasoned team with
successful exits
→ Founded in 2015 as a Public
Benefit Corporation
→ $132.3M raised; Series C
funding announced April 2022
→ Venture investments led by
Goldman Sachs, Shasta
Ventures, Technology
Pioneers Fund
Innovative tech with
customers to match
→ 90+ customers
→ Finance, Insurance,
Healthcare, Professional
Services, Communications,
High Tech, Government
→ Strong patent portfolio: 56
patents issued/allowed, 23
additional pending
Committed to
collaborative data
work
→ Home to the world’s largest
open data catalog and
community
→ Co-created the Data
Manifesto and
DataPractices.org, now under
the Linux Foundation’s
stewardship
6

Poll
7
1. Initial investigation
2. PoC’s and small-scale pilots
3. Operationalized for departmental or functional
applications (search, knowledge management)
4. Enterprise-wide deployment
5. None of the above
Where are you in your knowledge graph journey?

www.earley.com © 2023 Earley Information Science, Inc. All Rights Reserved. 8
A Growing Imperative
• “By 2025, graph technologies will be used in 80% of data
and analytics innovations...”
• “Finding relationships in combinations of diverse data,
using graph techniques at scale, will form the foundation
of modern data and analytics.”

Knowledge Graph powered Data Catalog
“Invest in augmented data catalogs to inventory all types of
metadata assets along with their associated relationships in
a flexible data model on a graph.”
- Ehtisham Zaidi. Gartner D&A August 2022

Graph is the Fastest Growing DB
Category

Navigation versus Classification
11
Classification Hierarchies
• Allows for definition of “is-ness” (what is this thing?) and
“about-ness” (what is it about then that helps me tell them
apart?)
• Classification drives dynamic navigation via facets which
leverage is-ness and about-ness (What is this? A sweater. Tell
me about this sweater. It’s blue)
• Relationships between classification hierarchies defines the
ontology (Products for Processes, Processes for Industry, etc.)
Navigational Hierarchies
• What most people think of when they
hear the term “taxonomy”
• Core structure of organizing principles for
a collection of information
• Static navigational hierarchies
(navigational taxonomies) is a dated
approach for any but most rudimentary
sites
• Dynamically driven by classification
hierarchies
We are not talking about
navigational hierarchies
(sometimes called “business
taxonomies”) due to lack of
adherence to classification
rules
Taxonomy is not the same as navigation

Taxonomies to Ontologies and Knowledge Graphs
12
Classification
Hierarchies
Define Ontologies
Ontologies, when
connected to data sources
becomes a Knowledge
Graph the knowledge
scaffolding of the
enterprise
=> Connect to Data
=>
Knowledge Graph

How are Knowledge Graphs Used in the Enterprise?

Knowledge Graph Use Cases
Data catalog, management and
governance
• What data do I have and what is the business
context?
• How can I provide access to the people who
need the information?
• Who owns, manages and curates critical
information assets?
• How do I understand upstream and
downstream dependencies and impact of
changes?
• What are the bottlenecks in my data
landscape?
• What people and and business processes are
connected to the data?
Knowledge management and
retrieval
• How do I locate content and knowledge
resources about specific topic, customer
or process?
• How do I manage ownership and
knowledge lifecycles (ensuring
knowledge is accurate and up to date)?
• How do I get quick, relevant answers to
simple questions?
• How do I find the right people with
knowledge and expertise to solve a
problem?
14

What is every project’s answer to
application proliferation?
Another application!
“if we just had one place for everyone to go…”
“we can migrate to a central location…”
“we need migrate all of our content and data to a
repository where all of our people can find their stuff …”
15

Copyright © 2021 Earley Information Science, Inc. All Rights Reserved.
EIS ReferenceArchitecture
16
PERSONALIZED/CONTEXTUALIZED USER
EXPERIENCE
Context Aware Information Architecture
Ontology
Content Model Metadata
Structured
(Operational) Data Unstructured
(Big) Data
Information Infrastructure
Marketing
Data
User
Data
Product
Data
Historical
Data
Operating
Content
Information Management Platforms
PIM DAM CMS ECM CRM ERP
Customer
Personalization
Content
Publishing
Site
Merchandizing
Product Info.
Management
Digital
Commerce
Business
Intelligence
Knowledge
Management
Enterprise
Search
Content
Management
Digital
Workplace
OntologyEncodes
GraphDataTo
ProvideConsistent
Architecture

Poll
17
1. Immature - little focus on the value of data
2. Some data governance but not connected to
business value
3. Governance defined with projected value but lack
of buy in
4. Business partners with IT, recognizes value and
follows governance processes
5. None of the above
Where are you in your data governance journey?

IT’S GETTING HARDER, NOT EASIER TO BE DATA DRIVEN
More data than ever. Faster change. Greater competition.
Higher demands from customers, employees, leaders, and shareholders.
Yet we must become more data-driven. Compliant and governed.
Automated and efficient. Innovative. Empowered.
data analysts spend 80% of their
time looking for and preparing data,
and only 20% on actual data
analytics.
IDC
By 2024, modern privacy laws are
predicted to cover 75% of the
world’s population (up from around
25% today).
Gartner
97% of data engineers are frustrated
with their current role and 70% are
looking to leave in the next 12
months.
DataKitchen + data.world research
study
The average tenure of a chief data
officer is only 30 months.
MIT Sloan
83% of executives believe their
organization needs to be more data
driven now than pre-pandemic.
IDC
24% of executives say they’d
describe their companies as data-
driven in 2021, down from 37.8% in
2020.
Harvard Business Review
Productivity lost Compliance needs
Big goals, no time Tech team pain Changing world
Culture reality
check
18

The traditional model
20
Enterprise Information Management
Data
Governance
Data
Management
Making sure that
information is managed
properly
(Define, Enforce, Audit,
Control)
Managing and refining
data to achieve goals
(Implement, Operate,
Refine)
Governance Council IT & Data Operations
Data Steward Data Trustee Data Engineer
Data Architect DBAs
Data Consumers
Data Analysts Data Scientists
Business Decision
Makers
SMEs App Engineers Product Mgrs

CONFIDENTIAL datadotworld data.world
The Cloud Data Catalog

CONFIDENTIAL datadotworld data.world
The Cloud Data Catalog
Time to work together...

CONFIDENTIAL
Adopting Agile for Data Governance in real life…
People
All about the team work
Tools
Make your data supply chain
efficient with a DataOps
approach and picking the
right tools for the job
Process
How do you adapt design
thinking and proven agile
processes like Scrum to D&A
Measurement
You can’t improve what you
don’t measure. We’re data
people right?!?!
… and can work for all industries and verticals

24
data.world is the front
office for data & analytics
Data Consumer
aka Data Analyst,
Scientist & Decision
Makers
Data Producer
aka Data Engineer,
Architects &
Stewards
We are the single place to
coordinate & capture the
entire data & analytics
process & lifecycle at scale

CONFIDENTIAL
Data
People
Insights
Use Cases
Decisions
Data Products
Metrics
Dashboards
Business Questions
We need trust at scale. We need a map
It needs to be automatic, smart, and easy for everyone
What is the risk
What data
should I use
What dashboard
can I trust
Why did we do this
Why did it break
How can we save
money
How do I get
onboarded
Who do I talk to
Where can we simplify
What now
How can we make
money

CONFIDENTIAL
Data
People
Insights
Use Cases
Decisions
Data Products
Metrics
Dashboards
Business Questions
Knowledge graphs are the map
RDF & SPARQL are the TCP/IP of data interoperability
data.world is the only true standards & KG-based data catalog and governance
solution
<foaf:person>
<dct:table>
<dwec:metric>
<dwec:dashboard>
<dwec:BusinessQuestion
>
<dwec:comment>
<dwec:DataProduct>
<dwec:UseCase>
<dwec:Decision>
<dwec:usesData>

datadotworld data.world
The Cloud Data Catalog datadotworld data.world
The Cloud-Native Data Catalog
Agile Data Governance Process: the team
● Data Architects
● System Administrators, DBAs
● Data Engineers, Data Ops
● 3rd Parties
● Data Analysts, Business Analysts
● Data Scientists, ML Engineers
● BI/Reporting Teams
● Line of Business Professionals - Knowledge Workers
But these roles CANNOT be fixed by individual
Producer and Consumer roles shift based on use
case and circumstances which gives our
businesses FLEXIBILITY and the ability to be
DYNAMIC

Agile Data Governance Process: data and analytics stories
Develop a backlog
End user business value
is the driver
Catalog the Backlog of Business
Questions and Metrics, and
corresponding People asking for them
in your Data Catalog!

Collaborate
Release early
Peer review
Define/document
Contextualize
Link to policy
Clarify/refine
Agile Data Governance Process: kick it off
Capture knowledge
as work is done!

Agile Data Governance Process: collaborate and capture
Training
Evangelism
Community
Accessibility
Hands on

Agile Data Governance Process: work!
Development of “working insights”
Fast, safe enablement
of end users is the goal.

Agile Data Governance Process: iterate!

UsingMetrics&KPIstoFocusGovernance
Measuring here
(business outcomes)
Measuring here
(process indicators)
Enterprise Strategy
Business Unit Objectives
New Business Opportunities
Average Order Size Total Account Revenue
Business Processes Site Traffic Search Relevance
Search
Digital Content
Working & Measuring
here (content, IA,
taxonomy, search, data
fill, etc.) Web
Commmerce
CRM
Processes enable
objectives
L
I
N
K
A
G
E
Leads
Revenue Growth
Data supports
processes
Objectives align
with strategy
CEO: “How will this increase revenue?”
Conversion
Data Scorecards
Process Scorecards
Outcome Scorecards
CTR Fill Rate Data Quality etc.
Digital Team: “How do I know taxonomy / data / search is working?”
Copyright © 2023 Earley Information Science, Inc. All Rights Reserved. 33

LEARN CHOOSE PURCHASE USE PAY
SUPPORT
MARKETING SALES DISTRIBUTION SERVICE FINANCE
SUPPORT
Marketing
Communications
B2B/Channel
Partners
B2C/Retail
Fulfillment
Inventory
management
Product
performance
Billing & payment
Credit & collections
Help & complaints
Repair & returns
ENTERPRISE PROCESSES: DEPARTMENTS/FUNCTIONAL AREAS/ACCOUNTABILITIES
Technologies
Departments
Processes
Accountabilities
Marketing ops
Product marketing
Marketing comm
Digital marketing
Training
Retail/dealers
Web marketing
Channel management
Telemarketing
Sales support
Logistics
Installation
Activation
Service operations
Applications
Quality assurance
Finance
Billing operations
Credit & collections
Customer care
Executive escalations
Call center operations
• Bots (chat, helper,
virtual assistants)
• Event management
• Webinar tools
• Promotion
management
• Social media
• Marketing resource
management
virtual assistants)
• Ecommerce
• CRM
• Web content
management
• Sales management
• Marketing resource
management
virtual assistants)
• Inventory management
• Supply chain
• Logistics and distribution
• Point of sale and
systems
virtual assistants)
• Knowledge base
• Online documentation/
help systems
virtual assistants)
• Ecommerce
• CRM
• Billing system
• Web content
management
• ERP/accounting
• Credit card
authorizations/EFT
virtual assistants)
• CRM
• Knowledgebase/
unsupervised support
• Online documentation/
help systems
• Call center call tracking
• Trouble ticketing
Data/Technology Scorecards
Process Scorecards
Outcome Scorecards
Journey Stage
Copyright © 2023 Earley Information Science, Inc. All Rights Reserved. 34
CUSTOMER JOURNEY: LIFECYCLE/ENABLING TECHNOLOGIES

Knowledge Graphs for Regulatory
Compliance
Large number of laws, rules and regulatory entities
• Financial reporting
• Anti-money laundering (AML)
• Know-your-customer (KYC) procedures
• Risk management
Collect and manage large amounts of structured and unstructured data
• Customer information
• Transaction records
• Internal and external communications
Visual representation of relationships
• Customers, transactions, requirements, issues, activity, inquiries
• Noncompliant transactions, customers, processes, other violations
• Machine learning algorithms automate flagging
• Increased diligence with reduce staff burden

Regulatory Compliance Concept Map
36
CUSTOMER
Jurisdiction
Account Data Activities
REGULATORY
REQUIREMENTS
Know your
customer
Thresholds
Agency
Anti money
laundering
Financial
Reporting
BANK
Regulation
Rules
Risk Category
Compliance
Status

Regulatory Compliance Concept Map
37
CUSTOMER
Jurisdiction
Account Data
Transaction
Records
Activities
REGULATORY
REQUIREMENTS
Know your
customer
Thresholds
Agency
Anti money
laundering
Risk
Management
Financial
Reporting
BANK
Compliance
Status
Regulation
Rules
Counter Parties
Risk
Management
Risk Category
Position
Trade
Operational
Reports
Product
Compliance
Status

Getting Started – Target Outcomes, Processes and
Data
38
1. Define desired measurable business outcomes and objectives – what
business objectives are most important to stakeholders?
2. Identify core supporting processes – what processes support the
business objective?
3. Identify data sources that drive processes – what data is needed to
support the business process?
4. Identify data quality, completeness and alignment baselines – what is
the quality and completeness of critical data?

Getting Started – Sponsor, Process Owners,
Stewards
39
1. Identify outcome, process and data owners
2. Align decision making body or steering committee with existing
organizational governance bodies – how are decisions made and
resources allocated?
3. Identify executive sponsor for initiative – who cares about the
outcome?
4. Define communications plan – what’s in it for them?
5. Plan change management – make the punishment fit the crime

Q&A
40

Additional Reading
41
From Earley Information Science
Knowledge Graphs, a Tool to Support
Successful Digital Transformation
Programs
https://www.earley.com/insights/knowledge-
graphs-a-tool-to-support-successful-digital-
transformation-programs
How Do Knowledge Graphs Address The
Challenges Facing Enterprises In An Age
of Accelerated Change?
https://www.earley.com/insights/how-do-
knowledge-graphs-address-challenges-
facing-enterprises-age-accelerated-change
From data.world
The Agile Data Governance
Playbook
https://data.world/reports-and-
tools/agile-data-governance-
playbook/

Earley AI Podcast
42
Listen to the Earley AI Podcast to explore
what's emerging in technology, data science,
and enterprise applications for artificial
intelligence and machine learning and how to
get from early-stage AI projects to fully mature
applications.
Found wherever you listen to podcasts,
including…
Henrik Hahn,
Chief Digital Officer,
Evonik
Dr. Mark Maybury, former CTO
at Stanley, Black & Decker
RECENT EPISODES

CONFIDENTIAL
The data catalog for your modern data
stack
An honest, no BS data podcast.
Honest, no-BS, non-salesy conversation
about enterprise data management and
analytics.
It’s a 60-minute podcast elixir containing everything
interesting about data and metadata management,
DataOps, knowledge graphs, and more.
4.8
Top 2.5% of Global Podcast Listenership*
*Listennotes.com

CONTACT US
CONTACT US
44
Thank you for your time. We’d love to hear from you!
For
Earley Information Science
www.earley.com
Seth Earley
Seth@earley.com
For
data.world
data.world
Juan Sequeda
Juan@data.world

Thanks!
45

EIS-Webinar-data.world-collab-2023-02-15.pptx

More Related Content

Similar to EIS-Webinar-data.world-collab-2023-02-15.pptx

More from Earley Information Science

Recently uploaded

EIS-Webinar-data.world-collab-2023-02-15.pptx