The majority of prescriptive BDMMs follow a similar modus operandi in that the current situation is first assessed followed by phases plotting the path towards increased big data maturity. Examples are as follows:
[https://www.malartu.co/blog/2018/5/25/malartu-data-maturity-model The Malartu Data Maturity Model]
To better communicate how we think about creating value through data within an investment group, we have developed the Malartu Data Maturity Model (MDMM). The goal of the MDMM is three-fold:
* To provide a simple assessment tool for where your firm currently sits
* To guide milestones for implementing the Malartu data platform
* To avoid pitfalls in establishing data capabilities at your firm
The Malartu Data Maturity Model consists of four stages:
* Data Aware: Your data is organized in one place and there is a system in place to continue this aggregation
* Data Proficient: You have identified taxonomies and metadata to categorize data in meaningful ways
* Data Intelligent: You can do more than pinpoint historical trends, you can combine granular sources and begin to predict future outcomes
* Data Driven: Your business revolves around data, you can predict future outcomes and prescribe strategic initiatives.
=== Info-Tech Big Data Maturity Assessment Tool <ref>{{Cite web|url=https://www.infotech.com/research/ss/leverage-big-data-by-starting-small/it-big-data-maturity-assessment-tool|title=Big Data Maturity Assessment Tool|website=www.infotech.com|language=en|access-date=2017-05-21}}</ref> ===
