Design Data-as-a-Service | Info-Tech Research Group

Lack of a consistent approach in accessing internal and external data within the organization and sharing data with third parties.
Data consumed by most organizations lacks proper data quality, data certification, standards tractability, and lineage.
Organizations are looking for guidance in terms of readily accessible data from others and data that can be shared with others or monetized.

Our Advice

Critical Insight

Despite data being everywhere, most organizations struggle to find accurate, trustworthy, and meaningful data when required.
Connecting to data should be as easy as connecting to the internet. This is achievable if all organizations start participating in the data marketplace ecosystem by leveraging a Data-as-a-Service (DaaS) framework.

Impact and Result

Data marketplaces facilitate data sharing between the data producer and the data consumer. The data product must be carefully designed to truly benefit in today’s connected data ecosystem.
Follow Info-Tech’s step-by-step approach to establish your DaaS framework:
1. Understand Data Ecosystem
2. Design Data Products
3. Establish DaaS framework

Design Data-as-a-Service Research & Tools

Start here – Read the Executive Brief

Read our concise Executive Brief to find out why you should design Data-as-a-Service (DaaS), review Info-Tech’s methodology, and understand the four ways we can support you in completing this project.

Design Data-as-a-Service – Executive Brief

1. Understand data ecosystem

Provide clear benefits of adopting the DaaS framework and solid rationale for moving towards a more connected data ecosystem and avoiding data silos.

2. Design data product

Leverage design thinking methodology and templates to document your most important data products.

3. Establish a DaaS framework

Capture internal and external data sources critical to data products success for the organization and document an end-to-end DaaS framework.

Member Testimonials

After each Info-Tech experience, we ask our members to quantify the real-time savings, monetary impact, and project improvements our research helped them achieve. See our top member experiences for this blueprint and what our clients have to say.

10.0/10

Overall Impact

$1,000

Average $ Saved

3

Average Days Saved

Client

Experience

Impact

$ Saved

Days Saved

Testimonial

Treasury Board of Canada Secretariat - Data and Digital Policy Sector

Guided Implementation

10/10

$1,000

3

Usman was able to provide me with advice and information I could understand and action into the work I am doing. Being new to the data space, Usman... Read More

About Info-Tech

Info-Tech Research Group is the world’s fastest-growing information technology research and advisory company, proudly serving over 30,000 IT professionals.

We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.

What Is a Blueprint?

A blueprint is designed to be a roadmap, containing a methodology and the tools and templates you need to solve your IT problems.

Each blueprint can be accompanied by a Guided Implementation that provides you access to our world-class analysts to help you get through the project.

Table of Contents

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Get the help you need in this 3-phase advisory process. You'll receive 8 touchpoints with our researchers, all included in your membership.

Guided Implementation 1: Understand data ecosystem

Call 1: Scope requirements, objectives, and your specific challenges.
Call 2: Assess current maturity.
Call 3: Discuss DaaS benefits and concepts.

Guided Implementation 2: Design data product

Call 1: Evaluate data product idea.
Call 2: Create data product design.

Guided Implementation 3: Establish a DaaS framework

Call 1: Map internal and external data.
Call 2: Document data service framework.
Call 3: Formalize data sharing agreements.

Author

Rajesh Parab

Contributors

Calvin Robinson, Data Architect, NASA
Jorden Thomas, Solution Architect, Databricks
Wouter Los, Owner, Los consulting
Izabela Edmunds, Architect, Mott Macdonald LLC.
Jodie Lunnon, Data Manager, Mott Macdonald LLC.
Krishna Mupparaju, CDO, Kentucky COT

Search Code: 94703
Last Revised: October 23, 2020

TAGS:

Data Product, Data Service, Data Marketplace, Data Broker, Data Silos, Data Ecosystem, Data Sharing, Data Contract, Data Agreement, Data Economy, Data Monetization, Data Value Chain, Data Democratization, Internet of Data, Data Consumer, Data Producer, Data Exchange, Data Exchange Agreement

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