Data Architecture Strategies: Data Architecture for Digital Transformation

Copyright Global Data Strategy, Ltd. 2021
Data Architecture for Digital Transformation
Donna Burbank
Global Data Strategy, Ltd.
December 7th, 2021
Follow on Twitter @donnaburbank
Twitter Event hashtag: #DAStrategies

Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2021. All rights reserved.
The Modern Database For Enterprise
Applications
Rick Jacobs | Technical Marketing Manager

AGENDA
Agenda
1
2
3
4
Overview
Why Couchbase
Couchbase Cloud
Use Cases

Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2021. All rights reserved. 3
Develop Efficiently
• Simplify & accelerate development
• Tap my skills (SDKs & SQL)
• Support best practices
• Avoid data sprawl
Deliver Great Experiences
• Personalized & responsive
• Anywhere & everywhere
• Real time info & inventory
• Ensuring dependable
transactions
Deploy Effectively
• Support hybrid clouds, Edge, 5G
• 100% uptime & global scale
• Flexible management options
• Cost effective
What Our Customers Tell Us: Modern Application Requirements

Modern Database Requirements Have Changed Too
Couchbase
Modern Demands (NoSQL)
• Massive data and users
• Scale & performance to match
• Flexibility for agile development
• Microservices architecture
• Web, mobile & IoT experiences
Legacy Demands (Relational)
• Small number of users
• Built to run on a single server
• Transactions, consistency,
ACID properties, integrity
• Storage efficiency
“The amount of data created over the next 3 years will be more than the data created over the past 30 years.” May 2020

Couchbase | NoEQUAL
Develop Faster
• Integrated platform capabilities
• SQL for JSON
• JSON documents & dynamic data structures
Deploy Everywhere
• How ever you choose to cloud
• Wherever data is needed
• Workload isolation and optimization
Performance at any scale
• Horizontal scaling
• High availability and reliability
• Memory first architecture

Why Capella (Couchbase Cloud)
Empowering Developer
Better
• Unlock team productivity with
self-service access to database
• Enable Agile development with unified
management console
• Enhance availability, security &
reliability with built-in best practices
Faster
• Accelerate development of responsive
web applications
• Enable increased security and
performance with flexible
deployment options
• Manage growth with on-demand
scaling
• Simple project, cluster and user
management
Unlock Business Agility
Cheaper
• Offload time-consuming and costly
operational tasks with always on-support
• Reduce costs by eliminating the need for
costly monitoring and configuration
software
• Flexible offerings to meeting your
business needs
• Leverage reserved instance pricing from
your CSP
Streamline Operations and Costs

BI & Big Data
Document Store
Frontend/Backend Cache
Mobile & Edge
Helping Customers Across Uses Cases & Business Goals
BI & Big Data
Document Store
Frontend/Backend
Mobile & Edge
Real-time
Analytics
Personalization
Token
Management
Mobile
Application
Product Catalog
Transaction
Processing
Fraud Detection
Risk Analysis
Customer 360
Legacy
Offloading
Field Service
Enablement
Edge
Computin
g
Business Goals
• Increase customer
satisfaction
• Faster time to market
• Drive loyalty, increase
revenues
• Increase cost savings
• Lower total cost of ownership
• Reduce cart abandonment

Proven Mission Critical Applications by Industry Leaders
Retail & E-
Commerce
Travel &
Hospitality Telecom Gaming
Financial
Services Healthcare
Media &
Entertainment Industrial IoT
3 of the Top 10
eCommerce
Companies
6 of the Top 10
Broadcast Companies
3 of the Top 3
GDS
Companies
6 of the Top 10
Online Casino
Gaming Companies
3 of the Top 3
Credit Reporting
Companies
3 Fortune 500
Healthcare
Companies
2 of the Top 2
IoT
Platforms

Thank you

Enabling Connected Data Communities™

IDENTIFIED THE PROBLEM CRACKED THE CODE BUILT THE FORECAST
New York’s
Data Gravity
Score
79.61 London’s
Data
Gravity
Score
167.05
Tokyo’s
Data
Gravity
Score
80.32
DATA CREATION LIFECYCLE
CREATE PROCESS
AGGREGATE ANALYZE
FORMULA
2020 2024
FORECAST
We studied infrastructure patterns occurring on PlatformDIGITAL®,
and identified Data Gravity* as the next critical industry challenge
Learn more at www.digitalrealty.com/platform-digital/data-gravity-index *Digital Realty Market Intelligence & Analytics, The Data Gravity Index DGxTM, Vol. 1.5 | 2

Data
Gravit
y
Index
™
STRUCTURED &
UNSTRUCTURED
STORAGE
Data Gravity Index
DGx™
I
digitalrealty.com
INTERACTIONS &
TRANSACTIONS
Continuous Data Creation Lifecycle Underpins Data Gravity
Enterprises serve an increasing number of users
and endpoints that are creating and exchanging
data
By 2022, more than 50% of enterprise data will
be created outside the data center or cloud1
PEOPLE &
THINGS
DATA
CREATION
DATA
PROCESSING
DATA
AGGREGATION & EXCHANGE
DATA
ENRICHMENT
Fig. 4. Data Creation Lifecycle; Data Gravity Index, Dec.
2020
1.Gartner, Infrastructure is Everywhere, ID #G00384194
2.Digital Realty Market Intelligence & Analytics, Dec. 2020
3.Digital Realty Market Intelligence & Analytics, Dec. 2020
4.Gartner, 100 Data and Analytics Predictions Through 2024, ID #G00721868
Files and messages invoke concurrent
interactions and transactions between users
and machines
By 2024, G2000 Enterprises in these 53 metros
will be required to add nearly 30 more
petaFLOPs (pFLOPS) to process new digital
workflows2
Enterprise Data has to be gathered and
formatted for presentation, exchange and
compliant storage
By 2024, across these 53 metros, G2000
Enterprises will be adding storage at a
combined rate of 622 terabytes per second for
aggregation & exchange3
Analytics, Machine Learning and AI
enable enterprises to embed workflow
intelligence
By 2022, 65% of CIOs will incorporate AI into
their ERP strategies to gain competitive
advantage4
ANALYTICS &
ENRICHMENT
| 3

PEOPLE,
LOCATIONS &
THINGS
APPLICATIONS,
PLATFORMS
& CAPACITY IN THE
CLOUD
AT THE
EDGE
CLOUD INTERCONNECTION CENTERS OF DATA DISTRIBUTION POINT OF PRESENCE
Public Cloud Hosted Services
(SAAS, PAAS, IAAS)
Cloud Bare Metal
Cloud On-ramps
Physical / Virtual Connectivity
SD-WAN Connectivity
Private Hosted Services
Ecosystem Connectivity
Distributed Bare Metal
Distributed IT Services
CDN, Security & IT Controls
SD-WAN Access Connectivity
Network Access
On-premise Hosted Services
Local Bare Metal
VALUE
CHAIN
FUNCTION/
SERVICES
HYBRID IT
Combining an interconnection fabric with varying infrastructure enables PlatformDIGITAL to be the meeting place of hybrid IT globally
Integrating Core, Cloud and Edge in a Single Platform - PlatformDIGITAL
| 4

Pervasive Datacenter Architecture (PDx™)
Solve Data Gravity
Bring users, things,
applications, clouds and
networks to the data at
centers of data exchange
| 5

IDENTIFY PARTICIPANTS
PLAN ZONES
DEPLOY FOOTPRINTS
MAP WORKLOADS
A Proven Approach
In 4 Steps
Pervasive
Datacenter
Architecture (PDx™)
Step by step approach to
plan and deploy centers of
data exchange and solve
data gravity.
| 6

Download the
Index
1 2 3
Map your
Data
Schedule a
SME Workshop
Take Action
digitalrealty.com/platform-digital/data-gravity-index
| 7

Global Data Strategy, Ltd. 2021
Donna Burbank
2
• Recognized industry expert in information
management with over 25 years of
experience in data strategy, information
management, data modeling, metadata
management, and enterprise architecture
• Managing Director at Global Data Strategy,
Ltd., an international information
management consulting company that
specializes in the alignment of business
drivers with data-centric technology
• Worked with dozens of Fortune 500
companies worldwide in the Americas,
Europe, Asia, and Africa and speaks
regularly at industry conferences
• Excellence in Data Management Award
from DAMA International
• Past President and Advisor to the DAMA
Rocky Mountain chapter
• Co-author of several books on data
management
• Regular contributor to industry
publications
• She can be reached at
donna.burbank@globaldatastrategy.com
Donna is based in Boulder, Colorado, US
Follow on Twitter @donnaburbank
@GlobalDataStrat

DATAVERSITY Data Architecture Strategies
• January Emerging Trends in Data Architecture – What’s the Next Big Thing?
• February Building a Data Strategy - Practical Steps for Aligning with Business Goals
• March Data Modeling Case Study – Business Data Modeling at Kiewit
• April Master Data Management – Aligning Data, Process, and Governance
• May Data Architecture, Solution Architecture, Platform Architecture – What’s the Difference?
• June Enterprise Architecture vs. Data Architecture
• July Best Practices in Metadata Management
• August Data Quality Best Practices (with guest Nigel Turner)
• September Data Modeling Techniques
• October Data Governance: Aligning Technical & Business Approaches
• December Data Architecture for Digital Transformation
3
This Year’s Lineup

What We’ll Cover Today
4
• Digital Transformation is a top priority for many organizations, and a successful digital journey
requires a strong data foundation.
• Creating this digital transformation requires a number of core data management capabilities such as
MDM, data quality, data architecture, and more.
• At the same time, combining these foundational data management approaches with other innovative
techniques can help drive organizational change as well as technological transformation.
• This webinar will provide practical steps for creating a data foundation for effective digital
transformation.

Digital Transformation is a Key Driver for Data Management
64% of organizations see digital transformation
as a key driver for data management
(increase of 11% from 2020)
5
Digital Transformation is a growing business driver for organizations
From Trends in Data Management A 2021 DATAVERSITY® Report, by Donna Burbank and Michelle Knight

What is Digital
Transformation?
• Digital transformation can refer to anything from IT modernization (for
example, cloud computing), to digital optimization, to the invention of
new digital business models.
• The term is widely used in public-sector organizations to refer to modest
initiatives such as putting services online or legacy modernization. Thus,
the term is more like “digitization” than “digital business transformation.”
- Gartner Information Technology Glossary
6

Business Optimization vs. Business Transformation
7
Digital Transformation is transforming business
Business Optimization
Becoming a Data-Driven Company
• Improving Efficiency
• Reduce Redundancy
• Eliminate Manual Effort
• Growing Revenue
• Improved Marketing Campaigns
• Data-driven Product Development
• Etc.
Business Transformation
Becoming a Data Company
• New Business Models
• Data is the product
• Monetization of information
• Digital Transformation
• New Business Models
• Data is the Business
• Etc.
How do we do what we do
better?
How do we do something
different?

COVID-19 has Accelerated Data-Driven Digital Transformation
8
D) DATA MANAGEMENT

Real World Examples of Data-driven Digital Transformation
9
The COVID-19 Pandemic made Digital Transformation a sudden reality for many organizations.
Below are a few examples of organizations whose strong data foundation allowed them to
rapidly shift to a digital model.
Non-profit Social Services
• Moved to a telehealth model
within weeks
• Built a data-driven culture of
decision-making based on COVID
response dashboards
International Bank
• Migrated paper-based processes
to data-driven, digital workflow
• Grew data-driven culture
through shared dashboards
(e.g. work from home response,
COVID response, etc.)
In-Person Events
• Used “down time” to increase
investment in customer
segmentation.
• Developed data-driven culture
via dashboards supporting online
services & customer profiles.

Data Monetization & Digital Transformation
Improvements to Core
Business
There are several ways to optimize growth through data
New Business Models
New Products and Services
• Optimize Revenue
• Improved marketing campaigns
• Customer Segmentation
• Pricing Optimization
• Etc.
• Minimize Costs
• Staff & Operational Efficiency
• Supply Chain Optimization
• Reduce Risk
• Regulatory Compliance
• Audit & Litigation Risk
• Smart City Initiatives: IoT
Monetization, Footfall Analytics, etc.
• Peer to Peer Ride Sharing: e.g. Uber,
Lyft, etc. are all based on data
• Social Networking Sites: Facebook,
Linkedin, etc. are all based on data
relationships.
• …and more
• Embedded Analytics Products: Selling
analytical tools key customer for
industry benchmarking, etc.
• Smart Metering: Allowing customers to
optimize their own energy usage
through value-added services.
• Revenue from Data Sets: Who may
have use for your data for other
purposes? Weather, transportation, etc.
• …and more….

Minimizing Costs
• Minimizing Costs – this is often the easiest to show
• Reduction in Wasted Labor Costs: How much human capital is wasted due to poor data quality,
lack of data access, redundant data efforts, etc.?
• E.g. Mary spends 10 hours per week cleaning data before each marketing campaign.
• Calculate Mary’s hourly rate x # hours per week x # weeks -> $50/hr x 10 x 46 = $23,000 per year
• Improving Inefficient Business Processes: Can Supply Chain be made more efficient with a
standardized set of material master data?
• E.g. Efficiency gains of 2% can be achieved resulting in $X of savings.
• Cost Avoidance: Would improving address data quality reduce the number of returned mailings?
• E.g. Cost of each mailing x # returned x # times per year. -> $1 per mailing x 500 returned per week x
50 weeks of mailing = $25,000 per year
12
Minimizing Costs

Optimizing Revenue
• Optimizing Revenue – How can better data improve business efficiency and profitability?
• Reduction in Costs or Inefficiencies: In some cases the benefits are simply the removal of the costs and inefficiencies from the
previous slide.
• Improved Business Performance: But more interesting is the ways data can be used to improve business effectiveness:
• Marketing Campaigns: Improved contact data (email, address, etc.) can improve marketing, but what new data sources can be
used? Social Media? Weather Data? Other?
• Advanced Analytics: How can analytics be used to improve the business, e.g. Price Optimization, Customer Segmentation, etc.
• New Data-Driven Applications: How can data and new data-driven technologies (e.g. AI) be used to improve the business, e.g.)
• Chat Bots: To streamline customer service
• Recommendation Engines: To enhance the sales cycle.
• New Revenue Streams: Can data be used for new revenue streams, e.g.
• Grant Funding: Data-driven analysis is often a key aspect of grant writing.
• Leveraging IP: Is there data that your company owns that can be monetized for research, marketing, etc.?
13
Optimizing Revenue

Reducing Risk
• Reducing Risk – Risk avoidance is a key aspect of any business. How can data and governance be used to minimize risk?
• Regulation: Industry regulations drive many data governance efforts including GDPR, HIPAA, BCBS 239, Spice, HIPAA, etc, etc.
• Product Traceability: Many food producers offer data-driven lineage showing the source of their food materials (e.g. fish catch).
• Health and Safety: Ensuring the health and safety of both customers and employees is critical.
• Employee: Data driven applications can help monitor employee health and safety activities (e.g. speeding).
• Customer: Is nutritional or allergen information correctly shown on menus? Does this information link to the actual food
source in the supply chain?
• Audit & Fines: Which industry regulations result in audit or fines? Has the organization been fined in the past? Can this be
quantified?
• Litigation: Has litigation occurred in the past due to data errors? What were the monetary sums?
14
Reducing Risk

Digital Transformation via Master Data Management
15
A brick and mortar retail store was
looking to expand its services online.
But its inventory management and
product catalog were based on paper (!)
and spreadsheets.
By automating their inventory management and
product catalog through Master Data
Management, they were able to move their catalog
online and significantly
(1) increase revenue and
(2) expand their market into new regions.

Cloud Hosting Model to Support Digital Transformation
16
A consumer retail company
was looking for a way to
support its growing volume
of online sales.
Consumer Demand was very
cyclical, spiking during the
December holiday shopping
season and flattening the
rest of the year.
Moving to a Cloud database
hosting model supported this
sales cycle, as they were able to
expand storage and processing
during peak times (only).

New Products & Services
• There are a large number of ways that new products and services can be created based on data.
The options will be unique to your company, but some examples include:
• Embedded Analytics Products: Selling analytical tools key customer for industry benchmarking, etc.
• Customer usage patterns: For large customers, showing purchasing across sites to help optimize their
business. Comparing with industry benchmarks, etc.
• Smart Metering: Allowing customers to optimize their own energy usage through value-added services.
• Revenue from Data Sets: Who may have use for your data for other purposes? Weather, transportation,
etc.
• A meteorology company selling weather data to retailers, engineering companies, etc
• Nonprofit selling anonymized demographic data to universities for research
• A shipping company has road geolocation data for rural areas – sold to manufacturing and delivery
companies in similar regions.
• Etc. – what data do you have that could be interesting/profitable to others?
18
Using Data for Strategic Advantage

Consumer Energy Company
• For the consumer energy sector Big Data and Smart Meters are transforming the ways of doing business
and interacting with customers.
• Moving away from traditional data use cases of metering & billing.
• Smart meters allow customers to be in control of their energy usage.
• Control over energy usage with connected systems
• Custom Energy Reports & Usage
• Smart Billing based on usage times
• As energy usage declines, data is becoming the true business asset for this energy company.
• While the Big Data Opportunity is crucial, equally important are the traditional data sources
• Data Quality critical for operational and analytic data
• Data Governance critical for analyzing data in relation to business processes & roles
• With high volumes of data, critical data elements prioritized
Business Transformation through Data Quality and Identifying Critical
Data Elements

Data Definitions & Process Maps
www.globaldatastrategy.com
What is a Student? e.g. Online vs. On-campus

New Business Models
• Perhaps the most exciting monetization opportunities are completely new ways of doing business
that are now possible using data or unique combinations of data.
• Smart City Initiatives:
• IoT – e.g. Smart Parking systems – find available parking via your smart phone
• Footfall Analytics – understand pedestrian traffic patterns.
• Peer to Peer Ride Sharing: e.g. Uber, Lyft, etc. are all based on data
• Social Networking Sites: Facebook, Linkedin, etc. are all based on data relationships.
• Smart Buildings: Embedded sensors help detect materials failure.
• Smart Farming: IoT, connected devices, etc.
• …and more
22
New ways of doing business as a result of data

New Business Models
• Ridesharing companies like Uber and Lyft were able to disrupt the traditional taxi industry
through creative integration and usage of data.
23
Peer to Peer Ride Sharing – disrupting the transportation industry
GPS Data – tracking
drivers and riders
Airline arrival data– to predict
user volume & set pricing.
Algorithms – Setting pricing,
matching drivers, etc.
User Rating System –
Crowdsourced feedback loop.
Etc…– and more... Data is
their business…

International Telecom Company
• An international telecom company was looking to leverage data as a corporate asset.
• Data is seen as their most strategic asset and corporate focus
• Telecommunications is a secondary goal – becoming a commodity
• While data was used to improve their core business
• New Product & Service Development: Data is Anonymized & sent to digital arm for new product and
development. Data-driven prototyping – using analytics to see what products are working best and used most
• Operational Performance & Maintenance: Network Optimization, Integrating call failure information and
location information with survey data.
• Etc.
• The larger opportunity was new data monetization opportunities, e.g.
• Geospatial data and Footfall Analytics: Resell/leverage anonymized data for:
• Retail: how are consumers navigating store layouts?
• City Planners: What are pedestrian traffic patterns at rush hour?
• Internally: How are employees travelling between buildings?
Do we need a new lunch room?
Business Transformation to “Becoming a Data Company” via IoT and Big Data

Today’s Business Environment is Ripe for the
Business-Savvy Data Professional
• In the current environment of data-driven business, Data Professionals have an
opportunity to have a “seat at the table”
• Finding new opportunities to leverage data for business benefit
• Creating efficiencies & business process optimization
• Integrating data from disparate sources for new business insights
• Supporting organizational change
25

Summary
• Digital Transformation requires a strong data
foundation.
• The “basics” such as master data
management, metadata management, etc.
are a core part of Digital Transformation
• Digital Transformation can help drive data
monetization and profitability

Who We Are: Business-Focused Data Strategy
Maximize the Organizational Value of Your Data Investment
In today’s business environment, showing rapid time to value for
any technical investment is critical.
But technology and data can be complex. At Global Data Strategy,
we help demystify technical complexity to help you:
• Demonstrate the ROI and business value of data to your
management
• Build a data strategy at your pace to match your unique culture
and organizational style.
• Create an actionable roadmap for “quick wins”, which building
towards a long-term scalable architecture.
Global Data Strategy’s shares experience from some of the largest
international organizations scaled to the pace of your unique team.
www.globaldatastrategy.com
Global Data Strategy has worked with organizations globally in the
following industries:
Finance · Retail · Social Services · Health Care · Education · Manufacturing
· Government · Public Utilities · Construction · Media & Entertainment ·
Insurance …. and more

Global Data Strategy, Ltd. 2021 www.globaldatastrategy.com
Questions?
Thoughts? Ideas?
28

Data Architecture Strategies: Data Architecture for Digital Transformation

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Similar to Data Architecture Strategies: Data Architecture for Digital Transformation

Similar to Data Architecture Strategies: Data Architecture for Digital Transformation (20)

More from DATAVERSITY

More from DATAVERSITY (20)

Recently uploaded

Recently uploaded (20)

Data Architecture Strategies: Data Architecture for Digital Transformation