DAS Slides: Emerging Trends in Data Architecture — What’s the Next Big Thing?

Copyright Global Data Strategy, Ltd. 2021
Emerging Trends in Data Architecture —
What’s the Next Big Thing?
Donna Burbank
Global Data Strategy, Ltd.
January 28th, 2021

Emerging Trends
in Data Architecture –
What’s the Next Big Thing?
Ibby Rahmani – Director of Product Marketing
1/28/2021

2 | © 2021 Alation, Inc. – All Rights Reserved.
The Catalog is the Platform™
Agenda
• Cloud Transformation
• Data Fabric
• Data Catalog

Next Big Things
Cloud Transformation Data Fabric

Cloud Transformation

Cloud Transformation is Still a Priority
The Benefits
are Compelling
• 80% reduction in server
cost by adopting cloud-
native technology
• 50% reduction
in production environment
cost
• The faster a company can
build & ship value to its
customers, the more likely
it is to succeed
Cloud is
a Priority
• By 2022, 75% of all databases
will be deployed or migrated
to a cloud platform
• 30% of all IT budgets
are allocated to cloud
computing
• 66% of enterprises
already have a central cloud
team or a cloud center of
excellence
Cloud Transformation
is Not Easy
Based on IDG’s 2020 Cloud Computing Survey
In a 2020 cloud
computing survey, only
38% of respondents said
they are mostly or all
(9%) in cloud today

Cloud Transformation: Challenges
Challenges
Successful cloud strategies
start with data
Understanding business impact
is critical for data migration
Users need a single view
of the data
Ideal
Solution
Helps identify critical data
assets to move
Helps understand
impact & communicate
it with the consumer
Provides consolidated view
of hybrid, multi-cloud data
assets
Driving adoption after
the migration
Don’t know
where to start
Don’t understand the
impact of a migration

Alation Accelerates the Cloud Transformation Journey
Planning Migration Adoption
Alation
Capability
• Know which data to move
• Know which data is unused – don’t move
it
• Identify top business users and the data
and reports they use
• Leverage an orderly process to track and
manage migration
• Transparent development and cutover
between IT, Business Users and Project
Leadership
• Communicate changing data environment
using Alation
• Alation drives adoption by bringing more
non-technical users to the DW
• Alation drives adoption and trust in the
new system
• Alation manages changing infrastructure
with TrustCheck
Impact
Time • Faster project start • Significantly faster migration • Rapid user adoption
Risk
• Reduced project risk and faster business
signoff
• Reduced project delivery risk • Increased user population
Cost
• Reduced IT costs • Reduced costs for compute, storage & IT
resources
• Accelerate sunsetting of expensive legacy
system

New Challenges: Cloud
Mixed Sources
• Relational
• Data Lake
• Cloud
Mixed Applications
• Traditional vs Modern
application
• Business Intelligence, Data
Integration,
Data Quality, Privacy,
Lineage, ….
Limited Resources
• People
• Expertise
• Budget

Data Fabric is the Future of Data
Management
Data fabric is a design concept that informs and
automates the design, deployment and use of
integrated and reusable data objects regardless of
deployment platforms or architectural approaches
• Not a single technology
• Not a simple collection of tools
• Requires existing & emerging data management
technologies
Emerging Technologies: Data Fabric Is the Future of Data Management - Gartner

Data Catalog Provides the Foundation for a
Data Fabric
Metadata management tools are
crucial for a dynamic data fabric
design, and therefore, partnerships
with data catalog vendors that can
extract metadata from multiple
sources
Data Consumers
Published Data Catalog and Data Engineering
Orchestration and DataOps
Data Preparation and Data Delivery Layer
Insights and Recommendation Engine
Active Metadata Knowledge Graph
Persistence Layer Enriched with Semantics
Augmented Data Catalog
Data Sources
Emerging Technologies: Data Fabric Is the Future of Data Management - Gartner (Dec -2020)

What is a Data Catalog?
• A repository of metadata on information sources across
an organization
- Search & discovery
- Data governance & curation
- Collaboration & analysis
• Catalogs a broad range of information assets
- Data sets, tables, articles, reports, queries, visualizations, conversations
• Includes common functionality such as:
Answers these
core questions:
How to find information?
Can it be used?
Should it be used?
How should it be used?
Business Glossary Lineage Catalog Pages Search

The Alation Data Catalog
“Alation started the ML Data Catalog trend.”
-Forrester Wave, Machine Learning Data Catalogs, 2018
The platform for data
intelligence solutions including:
• digital transformation
• data governance
• analyst productivity
• cloud transformation
• privacy, risk & compliance
What is the
Alation Data Catalog?
Gartner
4x MQ Leader
Magic Quadrant
for Metadata
Management
2017 - 2020
Forrester
2x Leader
Machine Learning
Data Catalogs
2018, 2020
Top Vendor
4 Years in a Row
Dresner Advisory Services
Data Catalog Market Study
2020
IDC
Leader
Worldwide Data
Catalog Software
2020 Vendor
Assessment

Thank You

Global Data Strategy, Ltd. 2021 www.globaldatastrategy.com
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
• With technological innovation and change occurring at an
ever-increasing rate, it’s hard to keep track of what’s hype
and what can provide practical value for your organization.
• This webinar will discuss the results of a recent
DATAVERSITY survey on emerging trends in data
architecture, along with practical commentary and advice.
4
Content is based on research from a 2020 DATAVERSITY survey
on “Trends in Data Management”.
Free Download at:
https://globaldatastrategy.com/resources/white-papers/
OR
https://content.dataversity.net/DV2020DataManagementRP_DownloadWP.html

What is Data Management?
The DAMA Data Management Body of Knowledge (DMBOK), defines data architecture as the following:
“Data Management is the development, execution, and supervision of plans, policies, programs, and
practices that deliver, control, protect, and enhance the value of data and information assets
throughout their lifecycles.”
5
DMBOK1 Definition
1 DMBOK: Data Management Body of Knowledge, www.dama.org

What is Data Management?
Survey respondents also provided a range of relevant definitions including:
• “Data Management treats our data as a corporate asset so that it is reliable, protected, and the
highest quality, enabling informed, accurate, and confident decisions.”
• “Data Management describes a technology-enabled discipline in which business and IT work
together to ensure the uniformity, accuracy, stewardship, semantic consistency, and accountability
of the enterprise’s official shared data assets.”
• “Data Management spans mostly the technical side of Data Governance, including Data Modeling,
Data Architecture, Data Quality, Data Integration, Metadata Management, and Master Data
Management (MDM).”
6
Survey Respondents Provided a Range of Views

What is Architecture
The DAMA Data Management Body of Knowledge (DMBOK), defines data
architecture as the following:
• “Data Architecture is fundamental to data management. Because most
organizations have more data than individual people can comprehend, it is
necessary to represent organizational data at different levels of
abstraction so that it can be understood and management can make
decisions about it.
• … Data Architecture artifacts include specifications used to describe
existing state, define data requirements, guide data integration, and
control data assets as put forth in data strategy. “
7
Data Management and Data Architecture are Related Disciplines

Top Business Goals and Drivers
Top Data-Driven Initiatives
• 78% gaining insights through reporting &
analytics (slight increase from 2019)
• 68% are looking to save costs and increase
efficiency (flat YoY from 2019)
• 64% see digital transformation as a key driver
for data management (increase of 11% from 2019)
8
Digital Transformation is a growing business driver for organizations

COVID-19 has Accelerated Data-Driven Digital Transformation
9

10
D) DATA MANAGEMENT

11
D) DATA MANAGEMENT

Real World Examples of Data-driven Digital Transformation
12
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.

Business Intelligence & Analytics
Business Intelligence & Analytics are key to gaining
business insight.
• 78% of respondents indicated that reporting and
analytics were key drivers for data management.
• 72% are implementing business intelligence
• 69% have a data warehouse in place
• 26% are using a data lake in conjunction with a
data warehouse
13
Business Intelligence & Analytics provide Business Insight

Data Management Initiatives – What’s Hot
• Analytics and Reporting continue to lead the
business drivers for data management.
• Top Initiatives include:
• Business Intelligence & Reporting (72%)
• Data Warehouse (69%)
• Data Security (60%)
• Data Governance (53%)
• Data Architecture (45%)
14
Gaining Business Insight through Analytics and Reporting continues to be a main business driver for today’s organizations.

Data Management Initiatives – What’s Not
• Equally interesting are the areas that decreased
from 2019
• Self Service Data Preparation (down 39%)
• Big Data (down 27%)
• Document Management (down 36%)
• Overall, however all categories showed a
decrease, showing more subdued efforts
overall.
• The smallest decreases were in Data Science
(down 6%) and Data Governance (down 8%).
15
All initiatives showed a softening, with the smallest decreases on areas that give insights into trusted data.

Looking Ahead – Future Plans Require a Strategic View
16
A successful Data Strategy
relies heavily on Data
Architecture and Data
Governance

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

Data Management is Increasingly a C-Level Concern
18
• Successful data management requires
involvement from a wide range of roles across
the organization, particularly business roles.
• Increasingly, C-level executives have a strong
interest in data management
• Notably, the role of the Chief Data Officer
(CDO) saw an increase of nearly 10 percent.

Technology Trends – the Basics Prevail, but Options Exist
• While a wide range of technologies are in use,
relational data stores make up the majority of
usage.
• Top data sources or platforms include:
• 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”
19
Organizations are using multiple tools for a “fit for purpose” approach with Relational Databases leading the use cases.

A Cautious Approach to the Future
• 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…
20
Relational Databases are the main focus for the next 1-2, indicating a “back to basics” approach

Looking Back
21
How Well did 2020 Match
2019’s Predications?

Top 5 Predictions for 2020
22
1. The blurring of “Business” and “IT” roles will continue
2. The blurring of “Data Management” and “Business” will continue
(e.g. Digital Transformation, Industry 4.0)
3. Organizations will rely on a matrixed set of data-centric tools and technologies
(e.g. relational, NoSQL, graph, etc.)
4. Data governance and ethics will have an increased role in business operations
5. Analytics and BI will continue to be a strong driver, with an evolving focus more towards
AI and predictive analytics, rather than simple descriptive analytics/reporting.

Looking Ahead
23
What’s the next Big
Thing for 2021 and
Beyond?

Top 5 Predictions for 2021
24
1. A focus on foundations will continue as organizations see a need for quality data as a
foundation for business insights.
2. Organizations who have built their data foundation during the economic downturn
will reap substantial benefits during the subsequent economic rebound.
3. Business insights from data will continue to be a driver, with a stronger focus on
advanced techniques such as data science and advanced analytics.
4. Data Governance will continue to play a strong role, with a concomitant increase in
related initiatives such as master data management, metadata management, etc.
5. Investment in Data Management will continue, with an emergence of new
technology players supporting increased demand for tools such as data catalog, data
quality, cloud data platforms, etc.

3
Summary – Emerging Trends in Data Architecture
• The economic downturn as a result of the
COVID-19 pandemic has driven a return to
foundations in data management.
• Business insights and analytics continue to
be a driver as organizations seek to use data
as a strategic differentiator
• A wide range of roles, particularly business
roles need to be involved in a successful
data management initiative
• While a wide range of tools and
technologies are available, relational
databases continue to be a foundation of
organizational data 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.
26
Data-Driven Business Transformation
Business Strategy
Aligned With
Data Strategy
Visit www.globaldatastrategy.com for more information

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
27
This Year’s Lineup

White Paper: Trends in Data Management
• Download from www.globaldatastrategy.com
• Under ‘Whitepapers’
• Also available on Dataversity.net
28
Free Download

Questions?
Thoughts? Ideas?
29

DAS Slides: Emerging Trends in Data Architecture — What’s the Next Big Thing?

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