

- Description
- A conference in a lecture hall
- Source
- NASA · original page
- Licence
- PD Public domain
Analytics — TDWI
Where does an organization stand in its use of analytics and BI, and why do so many teams get stuck halfway?
At a glance
- 5 stages, from nascent to mature.
- A chasm between early adoption and corporate adoption.
- 5 categories: organization, infrastructure, data, analytics, governance.
Profile#
- Organization
- TDWI (formerly The Data Warehousing Institute)
- Purpose
- Place the organization's maturity in its use of analytics and data
- Scale
- 5 stages: Nascent, Pre-adoption, Early adoption, Corporate adoption, Mature / visionary
- Dimensions
- Five categories in the TDWI maturity assessment: organization, infrastructure, data management, analytics, governance
- Particularity
- A “chasm” would separate early adoption from corporate adoption
- Access
- TDWI publications and online assessment; some resources are reserved for members
Why this matrix matters in my field#
This model speaks the language of BI and the data warehouse: it describes how an organization moves from isolated spreadsheets to analytics integrated into its processes. For a BI team, it helps explain why a project that succeeds in one department does not spread on its own: scaling up is an organizational change, not just a technological one.
The maturity scale#
The first three stages reproduce the descriptions published by TDWI. The last two are reworded; consult the TDWI publications for the reference version.
Nascent#
No analytics, apart from the spreadsheet. A culture not driven by data: decisions rely on intuition. A few people glimpse the value.
Pre-adoption#
The organization does its homework. One or more departments invest in an isolated BI tool or decision-support database. The value of analysis for decision-making starts to be perceived.
Early adoption#
Tools and methods are put in place; people think about data management, reports, dashboards. A frequently long transition, with a “chasm” to cross: skills, resistance, ability to act on the analyses.
Corporate adoption#
Analytics is operationalized in business processes and reaches a growing number of users: it can transform the way the organization works.
Mature / visionary#
Analytics is a strategic competency, integrated into decisions and innovation; the data culture is established and continuously improved.
The dimensions assessed#
The five categories of the TDWI maturity assessment:
Organization#
Strategy, sponsors, skills, culture and team organization.
Infrastructure#
Technical platforms, storage, processing, tools.
Data management#
Integration, quality, modeling, data access.
Analytics#
Types of analyses performed, methods, distribution and use.
Governance#
Rules, responsibilities, security and compliance.
How to use it#
- Assess each category separately: infrastructure may be ahead of the organization, or the reverse.
- Identify the stage of the largest number of departments, not that of the best team.
- Spot what blocks scaling up: skills, sponsor, governance, shared platform.
- Build a roadmap of use cases that help cross the chasm.
Limitations and precautions#
- The model has had several variants (analytics, big data); specify the version used.
- The stage describes trends, not measurable thresholds.
- An organization can be “mature” in one use and “nascent” in another.
Sources and verification#
- TDWI — official website — publishing organization
- Wikipedia — Big data maturity model — summary of stages and categories