Building a Data Strategy – Practical Steps for Aligning with Business Goals

Copyright Global Data Strategy, Ltd. 2023
Building a Data Strategy:
Practical Steps for Aligning with Business Goals
Donna Burbank
Global Data Strategy, Ltd.
February 23, 2023

Unlocking Trapped Value with Data
The meeting place for companies, technologies and data
Dan Eline, Senior Director of Platform Planning & Solutions

Artificial
Intelligence
Autonomous
Vehicles
Custom Manufacturing
and 3D Printing
Internet of Things and
Connected Devices
Robots &
Drones
Social Media &
Platforms
Dig Data
Analytics and
Cloud
Source: World Economic Forum, with Accenture, “Digital Transformation Initiative”
7 Technologies
2
© 2022 Digital Realty Trust® Inc.

Source: Seagate, “The Digitization of the World – From Edge to Core”; Digital Realty Market Intelligence, Data Gravity Index 1.5
4ZB
2010 2015 2020 2025
0
20
40
60
80
100
120
140
160
180
200
58ZB
18ZB
175ZB
CAGR = 535%
Zetabytes
Data is
Growing
3

13
Questions
7,295
Participants
23
Countries
9
Industries
$100M - $1B+
Company Size by Revenue
Source: Global Data Insights Survey, 2022 Report, Digital Realty 2022; Digital Realty Market Intelligence
End User
Data Priorities
4

Data-First
Strategy
Wins
76%
plan to use data
to improve
customer
experience and
build new digital
products
Data
Distribution is
Increasing
72%
plan to add new
business
locations in the
next two years
Data
is
Localizing
78%
maintain local
copies of
customer data
for business and
compliance
purposes
Data
Latency
Matters
77%
identified data
latency specific
performance
requirements
Data Needs
Global
Meeting Place
84%
need global
coverage and
secure data
exchange from
a single DC
provider
Source: Global Data Insights Survey, 2022 Report, Digital Realty 2022; Digital Realty Market Intelligence
Key
Takeaways
5

CENTERS
OF DATA
MULTI-TENANT
DATA CENTERS
Public Private Shared
Cloud & IT
Providers
Enterprises
Connectivity
Providers
Telemetry Via
Data Gravity
Index
Source: Digital Realty Market Intelligence, Data Gravity Index 1.5
6

USE CASES
ADD NEW
MARKETS
EVOLVE
ON-RAMPS
CLOUD & CONTENT PROVIDERs
REWIRE THE
NETWORK
OPTIMIZE DATA
EXCHANGE
ENTERPRISES & HYBRID IT PROVIDERS
IMPLEMENT
HYBRID
CONTROLS
CONNECTIVITY PROVIDERS
APPLICATIONS, PLATFORMS & CAPACITY
IN THE CLOUD
USERS, DEVICES, THINGS
AT THE EDGE
CONNECTED DATA COMMUNITIES
CENTERS
OF DATA
MULTI-TENANT
DATA CENTERS
The Meeting Place
BUILD HYBRID
NETWORK
OFFERINGS
ADD NEW
MANAGED
SERVICES
ADD
POINTS OF
PRESENCE
BUILD
HYBRID
OFFERINGS
Source: Digital Realty Market Intelligence, Data Gravity Index 1.5
7

Thank you
Resources
• Explore PlatformDIGITAL
• Visit the Data Gravity Insights Hub
• Download the Global Data Insights Survey
§ Presenter Name
§ 15/09/22

Confidential. © 2023 Monte Carlo Data, Inc.
Unlocking the Power of Your Data
Data Observability
Shane Murray
February
23rd,
2023

Confidential. © 2023 Monte Carlo Data, Inc. 2
Shane Murray
Field CTO @ Monte Carlo (2022-)
SVP Data & Insights @ The New York Times (2013-2021)
$236m in funding by backers of the world’s best enterprise companies,
including Accel, GGV, Redpoint, ICONIQ, and IVP
Creator of the Data Observability category

Why is data downtime a problem?
3
Canʼt know when
data is bad or who
to ask for help
Canʼt predict
all the ways
data will break
Canʼt see
downstream
Data producers
(source systems)
Data platform
(warehouses, lakes)
Data consumers
(BI tools, data products)

How we started:
Manual tests were the only means to ensuring data quality
4
90%
10%
Typical
distribution of
data incidents
Testing Detected by downstream data consumers
Common tests
■ Column must have 0% nulls
■ Transaction price must be >$0
■ …and other predictable anomalies
Why testing falls short
■ Canʼt test what you canʼt predict
■ Canʼt see downstream
■ Direct queries become costly
■ Data and stack are constantly changing
■ Doesnʼt scale

Consequences of data downtime range from trivial to existential
5
~70
high severity events each year per
every 1k tables 1
30-50%
data engineering time
spent on fire drills 2
12-27%
avg. annual revenue lost for
companies resulting from
poor data quality 3
1. Benchmark data based on Monte Carlo customer production deployments
2. Monte Carlo market research and customer-reported benchmarks
3. Experian Data Quality; MC research via Wakefield Research Survey

Data downtime looks similar at all companies
6
■ Is this data up-to-date?
■ Why does this data size look oﬀ?
■ Isnʼt this value suspiciously high?
■ Why are there so many nulls?
■ Why do we have duplicate IDs?
■ What reports will I break with this schema update?
■ Why are there 0s on tiles that usually show 100s?
…
DATA
OBSERVABILITY
PILLARS
Freshness
Volume
Schema
Quality
Lineage

What is Data Observability?
7
Prevent
■ Auto-generated and on-demand
insights
■ Schema change notifications
■ Automated circuit breakers
Detect
■ ML-powered anomaly detection
■ Rule-based detection
■ Targeted alerts to impacted owners
& downstream users
Resolve
■ Automated field-level lineage
■ Impact radius assessment
■ Code, data, and operational
diagnostics
DATA OBSERVABILITY PILLARS
Freshness | Volume | Quality | Schema | Lineage

Observability equips your team with automated monitoring
across 100% of production tables and critical fields
Freshness, volume & schema monitoring
on all production tables
1
Data warehouse,
lake, or lakehouse
Data quality monitoring
for critical fields
% null, median, p20-p80, and 20+ metrics
2
Custom rules & tests
for critical tables & fields
3
Powered
by
ML
8

Automated table- & field-level lineage
Triage, find root cause, and manage incident workflows
9
Triage incidents
Find root cause
Manage workflows

Confidential. © 2023 Monte Carlo Data, Inc. 10
https://www.montecarlodata.com/oreilly-data-quality-fundamentals-early-release/
OʼReillyʼs
Data Quality
Fundamentals
Learn what it takes to build more reliable
data pipelines at scale.

Thank you
smurray@montecarlodata.com
11

Global Data Strategy, Ltd. 2023
Donna Burbank
2
Donna is a recognised industry expert in data
management with over 25 years of
experience in data strategy, data governance,
data modeling, metadata management, and
enterprise architecture. Her background is
multi-faceted across consulting, product
development, product management, brand
strategy, marketing, and business leadership.
She is currently the Managing Director at
Global Data Strategy, Ltd., an international
data management consulting company that
specializes in the alignment of business
drivers with data-centric technology.
In past roles, she has served in key brand
strategy and product management roles at CA
Technologies and Embarcadero Technologies
for several of the leading data management
products in the market.
As an active contributor to the data
management community, she is a long time
DAMA International member, Past President
and Advisor to the DAMA Rocky Mountain
chapter, and was awarded the Excellence in
Data Management Award from DAMA
International.
She has worked with dozens of Fortune 500
companies worldwide in the Americas,
Europe, Asia, and Africa and speaks regularly
at industry conferences. She has co-authored
several books and is a regular contributor to
industry publications. She can be reached at
donna.burbank@globaldatastrategy.com
Donna is based in Boulder, Colorado, US.

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 Mesh or Data Mess? Separating the Reality from the Hype
• April Master Data Management - Aligning Data, Process, and Governance
• May How do Data Governance & Data Architecture Support Each Other?
• June Why You Need Data Management – Getting Executive Buy-In
• July Artificial Intelligence and Machine Learning – Building the Right Architectural Foundation
• August Data Quality Best Practices (with Nigel Turner)
• September Best Practices in Metadata Management
• October Designing Data for Business Intelligence & Analytics – Where the Star Schema Fits in a
Modern Data Architecture
• December Enterprise Architecture vs. Data Architecture
3
This Year’s Lineup

What We’ll Cover Today
• Developing a Data Strategy for your organization can seem
like a daunting task – but it’s worth the effort.
• Getting your Data Strategy right can provide significant
value, as data drives many of the key initiatives in today’s
marketplace, from digital transformation to marketing,
customer centricity, population health, and more.
• This webinar will help demystify Data Strategy and its
relationship to Data Architecture and will provide concrete,
practical ways to get started.
4

The Rise of the Data-Driven Business
Data, more than ever, is seen as a key business asset and strategic differentiator.
5

The Role of the Data Professional
in the Data-Driven Business
• 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
6

What is a Data Strategy?
7
Strategy:
1. the art of devising or employing plans
or stratagems toward a goal
2. an adaptation or complex of adaptations (as
of behavior, metabolism, or structure) that
serves or appears to serve an important
function in achieving evolutionary success
3. the science and art of military command
exercised to meet the enemy in combat under
advantageous conditions
Strategy vs. Management
- Source Merriam Webster
Management:
1. judicious use of means to accomplish an end
2. the act or art of managing : the conducting or
supervising of something (such as a business)
- Source Merriam Webster

But What is “It”, Really?
• Many people are overwhelmed with the concept of building a Data Strategy – it can seem like a
massive and overarching task.
• On a very tactical level, many wonder what format it should be in – Word Document, PowerPoint
presentation, Interpretive Dance? ☺
• While many formats can be effective, a visual presentation often has the most impact. Key
sections of the strategy should include:
• Business Alignment – case for change and value proposition
• Current State Analysis
• Future State Recommendations
• Roadmap and Next Steps
• Projected ROI and Benefit
8

Data is Driving the Future of the Global Economy
• “For most of the history of business,
the world’s leading companies have
been industrially-focused…
• …But today’s business reality is very
different. We live in a world of bytes –
and for the first time technology and
commerce have collided in a way that
makes data far more valuable than
physical, tangible objects.
• The best place to see this is in how the
market values businesses.” 1
9
Product
Focus
Data
Focus
The World Economic Forum sees today’s economy as driven by Data, not Goods & Services
1 Oct 15, 2018, World Economic Forum, “These are the 8 major forces shaping the future of the global economy”

Business Optimization vs. Business Transformation
10
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?

Business & Data Strategy – the Interdependency
11
Data
Strategy
Informs & Guides
Informs & Guides
Business
Strategy

A Successful Data Strategy links Business Goals with Technology Solutions
Level 1
“Top-Down” alignment with
business priorities
Level 5
“Bottom-Up” management &
inventory of data sources
Level 2
Managing the people, process,
policies & culture around data
Level 4
Coordinating & integrating
disparate data sources
Level 3
Leveraging data for strategic
advantage
Aligning Business Strategy with Data Strategy

“Offense” vs. “Defense”
• Focused on Creating Opportunity
• Improving Profitability
• Increasing Revenue
• Improving Customer Satisfaction
• Competitive Advantage
13
Which style of data strategy fits your organization?
Offense Defense
• Focused on Reducing Risk
• Compliance & Regulation
• Avoiding Audits or Fines
• Fraud Detection
• Security & Privacy
On which end of the spectrum is your organization?

Look for Business Value “Levers”
• Identify areas that will derive the highest business value by
addressing.
• Is this supporting the new marketing campaign for a high visibility
product launch?
• Or are you “re-arranging the deck chairs on the Titanic” – i.e.
focusing valuable time and effort no low-value activities
• As with any areas of the business that have value, it is helpful to
build a model or architectural design around the key areas of
business value.
Identify “Quick Wins”
Load
Effort
Fulcrum
Identify areas where data can be the fulcrum.

Making the Business Case
15
While Business Cases and ROI Calculations can be complex, they generally fall into 4 categories:
• Wasted Labor costs due to
manual efforts
(Data cleansing, manual integration,
etc.)
• Inefficient business processes
for data management
(Product Master Data process)
• Data quality cost avoidance
(Wasted mailings sent to wrong
address)
Decreasing Costs
• Price Optimization through
Analytics
• Improved Marketing Campaigns
through Quality Customer Data
• Data-Driven Recommendation
Engines to enhance the sales
cycle.
• Better Grant writing through
data-driven needs analysis
• Industry regulations
(GDPR, HIPAA, BCBS 239, Spice,
HIPAA, etc.)
• Product Traceability
(Food lineage from farm/catch)
• Litigation due to Data Breach
• Health and Safety Audit
• Customer Satisfaction
• Brand Trust
• Social Media Voice of Consumer
• Loyalty & ‘Stickiness’
Increasing Revenue Reducing Risk Protecting Reputation

Include the Risk of Doing Nothing
16
• There is significant cost and risk in the status
quo
• Doing nothing often has a higher cost than
investing in data management.
• Make sure to include the “do nothing”
option in your analysis.

Data Strategy Relies on Data Architecture & Governance
17
A successful Data Strategy
relies heavily on Data
Architecture and Data
Governance
Based on research from a 2020 DATAVERSITY survey on “Trends in Data Management” by Donna Burbank and Michelle Knight

Tools &
Platforms
Applying a Structured Data Governance Framework
Vision & Strategy
Organization &
People
Processes &
Workflows
Data Management
& Measures
Culture & Communication
Copyright Global Data Strategy, Ltd. 2022
A structured Data Governance Framework helps align business and IT for long-term success.

Mapping Organizational Capability
• Organizational Capability, Organizational Structure, and Roles are key to any Data Strategy
19
Aligning to Organizational Capabilities
e.g. From Plan to Production to Sales & Distribution
Designing Org Structures for Data-Centric Efforts
e.g. Aligning Data Governance to Individual Culture

0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00%
XML
Media files (videos, photos, etc.)
Non-relational cloud-based database (document, key/value etc.)
JSON
Legacy systems (e.g. Mainframe, COBOL, etc.)
Cloud object storage (including cloud data lakes)
Packaged applications (e.g. ERP, CRM, etc.)
Relational cloud-based database
Spreadsheets
Relational on-premises database
Data Architecture: Top 10 Data Platforms & Sources - 2022
20
Which of the Following Data Sources or Platforms are you Using Today?
(Select all that apply)

Data Architecture: Top 10 Data Platforms & Sources – 2023-24
21
0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00%
Graph database
JSON
Real-time/streaming database
Non-relational cloud-based database (document, key/value…
Spreadsheets
Don’t know
Packaged applications (e.g. ERP, CRM, etc.)
Relational on-premises database
Cloud object storage (including cloud data lakes)
Relational cloud-based database
Which of the Following Data Sources or Platforms are you planning on using in the next 1-2 years?
(Select all that apply)

Building Trusted Data Sets
• Successfully building trusted data sets
requires a full range of data management
disciplines
What does it take to build Trusted Data Sets?
Trusted
Data
Data Architecture
Data Quality
Privacy &
Security
Metadata
Management
Data
Governance
Trusted Data

The Critical Role of Data Architecture & Governance
23
A high-level data architecture provides the roadmap for data strategy & associated governance.
Business data model
What data do we prioritize? Where is this data used?
Business process models
Where is this data stored?
Data architecture diagram
What rules apply to this data?
Business rules & policy
What is the quality of the data?
Data quality dashboard
Business Glossary
This architecture provides a guide for small, targeted projects for business value to add additional detail.
What data best
supports our Brokers?
What data best supports
our Customers?
What data can we use to
best Price our Policies?
Home Auto
Commercial
What external data can we use
for business advantage?

Building Blocks to an Effective Roadmap
24
Why? Who?
How? What?
When?
What are the key business drivers?
Think both “Offense” & “Defense”
Who are the key stakeholders who will benefit?
Who are the Data Stewards who can be
“discovered” in the organization?
How will you organize the Data Governance team(s)?
What Data Architecture will you put into place?
What data needs to be managed?
Is this structured or unstructured?
Real-time or batch?
In which platforms or systems?
When will you roll this out?
What is the timing and cadence or actions and
deliverables?
Are there other key initiatives it’s important to align
with?

Why: Aligning with the Organizational Vision
• Key to any Data Strategy and Roadmap is aligning with
the organization’s vision.
• Ways to find out more about the organization’s
direction:
• Annual Report
• Company Updates
• Team and Project Updates
• News releases
• Project plans
• Particularly for planning a roadmap, it is important to
understand the company’s plans & trajectory
• Is the organization cautious or aggressive in its future
state?
• Are there events that you should align your strategy
around? e.g. Product Launch, Corporate Audit, School
Semester start, etc.

Tell the Story – Explain Vision and the Journey to Get There
26
• Storytelling and vision-building is a key part to any
strategy.
• Build a sense of excitement
• Provide a vision for what the future will look like
• Show the journey and the effort required
• Explain the steps to achieve the journey
• Clarify everyone’s role in the journey – where do they fit,
and what skills do they need?

Assess Organizational Maturity
Global Data Strategy’s Data Management Maturity Assessment
• Perform a realistic maturity assessment of the
organization’s data management capabilities:
• Current state by discipline
• Future Goals
• Gaps that need to be filled

Find Your “Quick Wins”
28
• It’s important to show early value
for the Data Strategy effort
• … and continue to deliver
iterative value over time.

What is a “Quick Win” Project?
29
Quick Win Project: A “Quick Win” Project is a project that shows early value while at the same
time building towards a long term goal. A successful “quick win”:
• Aligns with business objectives and solves a high-value business problem or
• Creates a proof of concept for a high-value business opportunity.
• Sets a solid foundation for future efforts
• Acts as a “light bulb moment” for key stakeholders to understand the value of data-centric activities.

A “Quick Win” is Not a “Quick Fix”
30
A Quick Win is not a sloppy, “quick fix” that
will not scale for future use.
A Quick Win is well-planned first step to
build a strong foundation for future efforts.
NO YES

Setting Priorities: Priority Grid
High Benefits – Low Difficulty
Low Benefits – High Difficulty
High Benefits – High Difficulty
Low Benefits – Low Difficulty
Level of Difficulty
Benefits
31
Priorities based on Benefits vs. Level of Difficulty can often be easily determined via a workshop
activity using a Priority Grid.

A Roadmap is Not a Laundry List
• A common error is to create a roadmap that reads like
a “Laundry List” of activities
• Create “themes” for each stage that tie into the vision
• Call-out “quick wins” and value for each activity
• Consider the WIIFM – what do key stakeholders care about?
32

Implementation Roadmap
• Define your roadmap with key activities timed to align with key business initiatives.
• Align with necessary staffing and training.
33
Define Roadmap & Staffing for Executing the Strategy
Implementation Roadmap for Key Activities by Functional Area
Staffing & Training Recommendations

‘ Culture eats
strategy for
breakfast.’
Peter Drucker,
Management
Strategist &
Consultant
34

Organizational Culture and Organizational Change Management
Organizational Culture:
“Organizational culture is the personality of the
organization”. 1
35
1 https://managementhelp.org/organizations/culture.htm
This Photo by Unknown Author is licensed under CC BY
This Photo by Unknown Author is licensed under CC BY-NC
Organizational Change Management:
Organizational change refers to the actions
in which a company or business alters a
major component of its organization, such
as its culture, the underlying technologies or
infrastructure it uses to operate, or its
internal processes.
Organizational change management is the
method of leveraging change to bring about
a successful resolution. - Harvard Business School

REINFORCEMENT
The Change Journey
Emotions play a key role underpinning each phase
AWARENESS MOTIVATION KNOWLEDGE
This is new!
Other people are excited
about it – maybe it can
help me, too.
This is new!
This is interesting – I’m
starting to understand how
it can help me.
This is new!
I’m seeing the value of
this over time – how did I
ever work without this?
COMMUNICATION ! COMMUNICATION! COMMUNICATION! COMMUNICATION!
• Alignment with
Business Value
• Vision & Roadmap
• Etc.
• WIIFM
• Testimonials
• Swag, slogans,
• Etc.
• Launch Awareness
• Trainings
• Coaching
• Certifications
• Etc.
• Ongoing
Communication Plan
• ROI & Value over time
• Success Stories
• Etc.
This is new!
This is new! Should I be
concerned?
36

Organizational Change Happens at Three Levels
An organizational move to a future state requires individuals to reach their own future state
INDIVIDUAL
ORGANIZATION
PROJECT
Enable people’s success by
supporting them through the
dimensions of change
Increase outcomes and ROI by
integrating activities into the
project plan that help prepare,
manage, and reinforce change
and results in adoption and
usage
Affect culture changes in the
enterprise by embedding
Change Management into
every Data Governance
initiative
“IN WHAT WAYS ARE MY
CURRENT RESPONSIBILITIES
AFFECTED”?
“The achievements of an organization are the results
of the combined effort of each individual”.
Vince Lombardi
“HOW DO WE SUCCESSFULLY
ACHIEVE LARGE SCALE
TRANSFORMATION”?
“WHO ARE THE IMPACTED
GROUPS AND HOW DO WE
SUPPORT THEM”?
Reference PROSCI for
methodology content
Data
Governance
directly impacts
the culture of
an organization
37

Garnering Excitement - Engage Marketing & Branding
• It’s beneficial to engage with your internal Marketing organization and/or an external agency
• Include a number of activities and materials in your communication and marketing plan. Here are
a few ideas:
38
• Video Testimonial from users/stakeholders
• Executive sponsor video
• Lunch and learn sessions
• Roadshows
• Training sessions
• Newsletters
• Website for data initiative
• Data initiative slogan
• “Swag” – t-shirts, stickers, mugs, etc.
• Posters
• Badges and awards
Avoid Data Jargon – use
Business Language!

Resistance Management: Causes for and Approaches to
Addressing resistance management
• Resistance prevention
• Change management applied early – at
the onset of every project
• Proactive resistance management
• Anticipation and early identification of
likely resistance so it can be addressed and
eliminated upfront
• Reactive resistance management
• Applying a set of tactics when resistance
becomes enduring and persistent
What looks like resistance is often a lack of direction
Typical Root Causes
Employees: Lack of awareness if why the
changes are happening and “WIIFM”. Comfort
with the status quo and fear of the unknown.
Executives: Disconnected with their strategy,
financial objectives or compensation
Middle Management: Lack of awareness, loss
of authority or control, and overload of current
responsibilities
39

Parting Thought – Culture Change in Your Organization
What do you think is the biggest
fear of change that you’ll face?
40
What would be the biggest
excitement/opportunity driver?

Summary
• Aligning Data Strategy with business drivers &
goals is key to success
• Orchestrate the people, process, technology, &
culture required through a robust Data
Governance program.
• Define a right-sized Data Architecture to manage
technological change
• Your roadmap should tell a story and show an
evolution from the current state.
• Define “quick wins” as well as long-term value
• Culture building and organizational change are
critical to success

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 Mesh or Data Mess? Separating the Reality from the Hype
• April Master Data Management - Aligning Data, Process, and Governance
• May How do Data Governance & Data Architecture Support Each Other?
• June Why You Need Data Management – Getting Executive Buy-In
• July Artificial Intelligence and Machine Learning – Building the Right Architectural Foundation
• August Data Quality Best Practices (with Nigel Turner)
• September Best Practices in Metadata Management
• October Designing Data for Business Intelligence & Analytics – Where the Star Schema Fits in a
Modern Data Architecture
• December Enterprise Architecture vs. Data Architecture
42
Join Us Next Month

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?
44

Building a Data Strategy – Practical Steps for Aligning with Business Goals

More Related Content

What's hot

Similar to Building a Data Strategy – Practical Steps for Aligning with Business Goals

More from DATAVERSITY

Recently uploaded

Building a Data Strategy – Practical Steps for Aligning with Business Goals