DAS Slides: Building a Data Strategy — Practical Steps for Aligning with Business Goals

Copyright Global Data Strategy, Ltd. 2021
Building a Data Strategy – Practical Steps for
Aligning with Business Goals
Donna Burbank
Global Data Strategy, Ltd.
February 25th, 2021
Follow on Twitter @donnaburbank
Twitter Event hashtag: #DAStrategies

© 2020 QlikTech International AB. All rights reserved.
Data Architecture
Strategies
February 25, 2021
Dan Potter
Vice President, Product Marketing

2
Evolving Requirements
CLOUD APPLICATION
DEVELOPMENT
DATA WAREHOUSE
MODERNIZATION
NEXT GENERATION
ANALYTICS
Drivers Legacy app modernization; faster
development; higher scalability
with lower cost
Reduce cost and complexity of
legacy EDW; greater agility to
meet diverse business needs
Analyze broader set of data; AI/ML
and IoT analytics; real-time
analytic apps (e.g. fraud)
Requirements Real-time data replication from
on-prem systems
Replace manual ETL scripting
with automation
Analytic-ready data structures
which are catalogued for easy
consumption

3
Evolving Data Architectures
DATA LAKE
Data
Sources
Queries / ML /
Analytics
Data
Lakehouse
Data
Sources
DATA LAKE
Queries / ML /
Analytics
Data
Warehouse
Data
Sources
Queries /
Analytics
Data
Warehouse
DATA LAKE
Data
Sources
Queries / ML /
Analytics
Data
Lakehouse
Evolving Data Architectures

4
Data Warehouse Automation
Streaming Data Pipeline Automation
Design, Manage & Monitor
Modernize and Automate Data Integration
CDC Streaming
Azure
Synapse
Amazon
Redshift
Managed Data Lake Creation
Generate
Change Data
Streams
Deliver
To Clouds,
Lakes…
Refine &
Merge
For Analytics,
AI/ML, Data
Science…
AI/ML
Analytics
Data
Science
Model
Commit
Conform
Consume
Catalog
Shop, Prepare & Provision
Catalog
RDBMS
Data Warehouse
Files
Mainframe
SAAS
APPS
SAP
Amazon RDS Azure SQL DB
Google Cloud SQL

5
Data Warehouse Automation
Streaming Data Pipeline Automation
Design, Manage & Monitor
Modernize and Automate Data Integration
CDC Streaming
Azure
SQL DW
Amazon
Redshift
Managed Data Lake Creation
Generate
Change Data
Streams
Deliver
To Clouds,
Lakes…
Refine &
Merge
For Analytics,
AI/ML, Data
Science…
AI/ML
Analytics
Data
Science
Model
Commit
Conform
Consume
Catalog
Catalog
RDBMS
Data Warehouse
Files
Mainframe
SAAS
APPS
SAP
Amazon RDS Azure SQL DB
Google Cloud SQL
Real-Time
Automate
Govern
Provision
Universal

6
The Only Constant is Change

Global Data Strategy, Ltd. 2021
Donna Burbank
2
Donna is a recognised industry expert in
information management with over 20 years
of experience in data strategy, information
management, 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
information 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, USA.
Follow on Twitter @donnaburbank
@GlobalDataStrat
Twitter Event hashtag: #DAStrategies

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
• Developing a Data Strategy for your organization can seem like a daunting task.
• The opportunity in getting it right can be significant, however, as data drives many of the key
initiatives in today’s marketplace from digital transformation, to marketing, to customer
centricity, population health, and more.
• This webinar will help de-mystify data strategy and 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

Business and Technical/Data Roles are Merging
6
As Data & Digital Transformation grow, there is a blurring between business and tech roles

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
7

What is a Data Strategy?
8
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

Data-Driven Business
Data-Driven Business is an impetus
for data management
• 70% of respondents feel that their organization
sees data as a strategic asset*.
• 68% are looking to save costs and increase
efficiency
• 64% see digital transformation as a key driver
for data management (increase of 11% from 2019)
9
Data Management is the foundation of the Data-Driven Business
* based on research from a 2019 DATAVERSITY survey on “Trends in Data Management” by Donna Burbank and Michelle McKnight
** based on research from a 2020 DATAVERSITY survey on “Trends in Data Management” by Donna Burbank and Michelle McKnight

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
Data Strategy Relies on a Solid Data Architecture

Current State
Assessment
Business Goals &
Strategy
Implementation
Roadmap
Proposed
Future State
A Structured Approach to Data Strategy
Communication & Evangelism
Business Motivation & Drivers Actionable Roadmap with “Quick Wins”
Aligning Strategic Data Initiatives
KPIs and
Metrics
Organizational Structure &
Governance Framework
Architecture & Technology
Recommendations
Technology Landscape Overview
Roles, Skills &
Responsibilities
Processes &
Procedures
Data Management Maturity
Assessment
www.globaldatastrategy.com

“Offense” vs. “Defense”
• Focused on Creating Opportunity
• Improving Profitability
• Increasing Revenue
• Improving Customer Satisfaction
• Competitive Advantage
14
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?

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

16
Donna Burbank
101 Main ST
Boulder, CO 80302
Credit Co
101 Wall ST
New York, NY
Monthly Balance, $1,9871
Due Date: 07/09/2020
Limited Time Offer!
Enroll Now!
▪ Autopay complete
▪ We’ve increased your credit limit
based on recent purchase history….

17
Donna Burbank
101 Main ST
Boulder, CO 80302
Credit Co
101 Wall ST
New York, NY
Monthly Balance, $1,9871
Due Date: 07/09/2020
Limited Time Offer!
Enroll Now!
Wasted
mailing costs
▪ Autopay complete
▪ We’ve increased your credit limit
based on recent purchase history….
Data-driven Digital
Transformation
… powered by master
data
Lost revenue
opportunity
from campaign
Loss of
Brand Trust
Resolved with

The Importance of KPIs
• Most businesses set strategic goals they desire to achieve, and measure these goals against
Key Performance Indicators (KPIs).
• These KPIs provide a concrete, objective way to measure progress towards these goals
18
“You Can’t Manage What You Can’t Measure”
• We need to do the same with data assets.
• % Complete
• % Accuracy
• Timeliness
• ROI
• Cost Savings
• Organizations typically have a number of
KPIs to manage financial assets.
• Revenue Projections
• Budget Goals & Limits
• Expense Ratio, etc.

Measuring Data Improvements
• Data Quality KPIs & Measures can be aligned with concrete business drivers
• Helps prioritize efforts
• Basis for showing benefits and results
• For example, if we ensure that email address are 100% complete and 90% accurate, our marketing campaign
effectiveness can increase by 20%.
19
Aligning Data Quality Metrics with Business Improvements
KPI Current Target Status Business Benefits Type
Number of duplicate
customer records
2,000,000 1,000 • Correct # of customers for sales estimations
• Better single view of customer for integrated social
media campaign
• Reduce cost of physical mailing by $20K
• Cost savings
• Brand Reputation
• Marketing Innovation
Incorrect Salutation
(Mr, Ms, Dr. etc.)
5,000 1,000 •Customer satisfaction & Brand reputation harmed by
incorrect salutation.
•Targeted marketing campaigns by gender.
• Brand Reputation
• Campaign Effectiveness
Incorrect address/location 10,000 500 • Lower return rate on physical mailings
• Better targeted marketing by region.
• Cost Savings
• Campaign Effectiveness
Missing Sales Rep Assigned 500 100 • Ability for Sales to execute on customer leads
• Revenue growth
• Sales Effectiveness
Business Driver: Improving Customer Data for Marketing Launch Campaign

Improvements to Core Business
• It’s often beneficial to turn your “back of the
envelope” calculations into a formal financial
projection.
• Benefits
• One time: sale of a data set, research
grant, etc.
• Recurring: staff productivity, ongoing
revenue, reduction in ongoing costs, etc.
• Costs:
• One time: software or hardware
purchase, initial training costs, etc.
• Recurring: software subscription or
maintenance, staff salary, etc.
• Consider Capital Expenditure (Capex) vs.
Operational Expenditure (Opex)
• Cloud subscriptions can generally be
considered Opex.
• Speak with Finance to see what is beneficial
to them – they often have unique priorities
per industry.
20
Part of your job is Finance!

Developers
Managers
Enterprise Data Management
Part of a Data Strategy is Defining Fit for Purpose Solutions
Operational Data Reporting & Analytics Master & Reference Data Metadata
CRM
Customer X orders
Product Y at 2pm on
Oct 24, 2017 Sales
CRM
ERP
Customer
Care
IoT
Customer X calls
Support at 1pm on
Nov 1, 2017
Inventory consists of x
number of Product X
components on Oct
24, 2017
Supply
Chain
Customer turns on
foot warmer at 11pm
on Oct 30, 2017
Product
Team
Customer
CRM
& other
systems
DW
What were total
sales for Product X
in 2016 by region?
Lake
Operational Reporting
Enterprise Historical Reporting
Analytics & Discovery
What variables
most influence
customer repeat
purchases?
Limited Personal Use
Limited ad hoc analysis
for small data sets.
Not recommended
for enterprise data
management.
UCM
UPM
“Golden Record” for Customer,
Product, etc.
Mary Smith lives on 101 Main ST,
Detroit, MI and has been a
customer since 2011
Product 720 has a product code
of SS720 & a suggested retail
price of $11,000 USD.
Business & Technical Context &
Descriptions
ELT
How many support
calls are currently
open?
Analytics
Team
Managers
Reference Data
Hierarchies
The Sales management reporting
hierarchy is structured as follows.
Valid Return Codes are “X, Y, & Z”
State Codes include MA, MD MI …
Applications
DW Etc
DW Etc
DW Etc
Business
Glossary How is Total Sales
calculated?
What is a Qualified
Lead?
Business
Users
Data
Models
How do we uniquely
identify a customer?
Can a customer have
more than 1 email?
Data
Dictionary
What is this DW table
used for?
The standard length for
customer ID is CHAR(12)
Developers
Data
Lineage
How was this field
calculated?
What will break
downstream if I make a
change?
Developers
Developers
Business
Users
Access

Current Platform Adoption
• While a wide range of technologies are in use,
relational data stores make up the majority of
usage.
• Relational on-premise database: 75%
• Spreadsheets: 71%
• Packaged applications: 59%
• Relational cloud-based database: 51%
• Most organizations are using a multi-platform
approach for a “fit for purpose” paradigm.
• It’s “both and”, not “either or”
22
Organizations are using multiple tools for a “fit for purpose” approach with Relational Databases leading the use cases.

Future Platform Adoption
• Future Trends point to continued focus on
relational databases, with usage shifting to the
Cloud
• Top Initiatives planned in 1-2 years include:
• Relational cloud-based databases: 54%
• Relational on-premise databases: 47%
• Packaged applications (e.g., ERP, CRM, etc.): 42%
• Spreadsheets: 35%
• And Spreadsheets continue to be a “data
platform”…sigh…
23
Future plans still feature relational databases, with a higher focus on Cloud Adoption, and a wider mix of technologies.

Setting Priorities: Priority Grid
High Benefits – Low Difficulty
PRIORITY
1
Low Benefits – High Difficulty
PRIORITY
4
High Benefits – High Difficulty
PRIORITY
2
Low Benefits – Low Difficulty
PRIORITY
3
LEVEL OF DIFFICULTY
BENEFITS
24
• Priorities based on Benefits vs. Level of Difficulty can often be easily determined via a
workshop activity using a Priority Grid.

Mapping Organizational Capability
• Organizational Capability, Organizational Structure, and Roles are key to any Data Strategy
25
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
Part of your job is
Organizational Change!

Evangelism & Outreach
• Key to long-term success is continued evangelism & outreach
• Communicate, communicate, communicate!
• Training & education
• Newsletters
• Webinars
• “Branding” & Collateral
• 1:1 Briefings
• “Lunch & Learns”
• Conference presentations
• Service Catalogues
• Etc.
Part of your job is
Marketing!

Find Advocates Across the Organization
• It’s key to find champions for your data strategy effort across the business
• Both “business” and “IT”
• From Senior level executives as champions to Field staff as supporters
• In making the case for funding or buy-in, it’s helpful to have someone else tell your story
• Can marketing advocate the case for change to improve campaigns
• … Or sales discuss the potential increases in revenue
• …. Or Engineering point out the increases in efficiency and quality
27
While we may want to take the
“credit” for the data strategy, it is often
most successful when other people
have embraced it as their own.

Defining an Actionable Roadmap
• Show quick-wins, while building to a
longer-term goal
• Balance Business Priorities with Data
Management Maturity
• Focus on projects that benefit multiple
stakeholders
• Mix core architecture with “new shiny
things”
Maximize the Benefit to the Organization
Initiatives H1 ‘21 H2 ‘21 H2 '18 H2 '18
Strategy Development
Governance Lineage for
Privacy Rules
Business Glossary
- Customer Data focus
Data Warehouse
Customer Analytics Pilot –
Social Media integration
Open Data Publication
IoT Integration
Ongoing Communication & Collaboration
Customer Product Location
Integrated
Customer View
Marketing
Sales
Customer Support
Executive Team
Key Stakeholders

Building Blocks to an Effective Roadmap
29
Why? Who?
How? What?
When?
• What are the key business drivers?
• Think both “Offense” & “Defense”
• What business benefit will be achieved?
• Who are the key stakeholders who will benefit?
• Who are the Data Stewards who can be
“discovered” in the organization?
• Who might be your Executive Champions?
• How will Data be Integrated and Stored?
• How will you organize the Data Governance
team(s)?
• Will Governance be Hierarchical, Federated?
Collaborative or Standards-Driven?
• What data needs to be prioritized?
• 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?

Summary
30
• Aligning Data Strategy & Data Architecture with business drivers & goals is key to success
• The blurring of “Data” and “Business” will continue
• Adapt your data architecture for both innovative & legacy technologies
• Design core KPIs and metrics to track business value & success
• Organizational Change is as important as technical change
• Develop a practical roadmap that balances “quick wins” with long-term foundational
architecture

About Global Data Strategy, Ltd
• Global Data Strategy is an international information management consulting company that
specializes in the alignment of business drivers with data-centric technology.
• Our passion is data, and helping organizations enrich their business opportunities through data and
information.
• Our core values center around providing solutions that are:
• Business-Driven: We put the needs of your business first, before we look at any technology solution.
• Clear & Relevant: We provide clear explanations using real-world examples.
• Customized & Right-Sized: Our implementations are based on the unique needs of your organization’s
size, corporate culture, and geography.
• High Quality & Technically Precise: We pride ourselves in excellence of execution, with years of
technical expertise in the industry.
31
Data-Driven Business Transformation
Business Strategy
Aligned With
Data Strategy
Visit www.globaldatastrategy.com for more information

White Paper: Trends in Data Management
• Download from www.globaldatastrategy.com
• Under ‘Whitepapers’
• Also available on Dataversity.net
32
Free Download

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
33
This Year’s Lineup

Global Data Strategy, Ltd. 2021 www.globaldatastrategy.com
Questions?
Thoughts? Ideas?
34

DAS Slides: Building a Data Strategy — Practical Steps for Aligning with Business Goals

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Similar to DAS Slides: Building a Data Strategy — Practical Steps for Aligning with Business Goals

Similar to DAS Slides: Building a Data Strategy — Practical Steps for Aligning with Business Goals (20)

More from DATAVERSITY

More from DATAVERSITY (20)

Recently uploaded

Recently uploaded (20)

DAS Slides: Building a Data Strategy — Practical Steps for Aligning with Business Goals