Content deleted Content added
m →TDWI big data maturity model: Clean up/General fixes, typo(s) fixed: decision making → decision-making |
Citation bot (talk | contribs) Altered title. Added authors 1-1. | Use this bot. Report bugs. | Suggested by Dominic3203 | Category:Big data | #UCB_Category 6/64 |
||
| (One intermediate revision by one other user not shown) | |||
Line 12:
The stages or phases in BDMMs depict the various ways in which data can be used in an organization and is one of the key tools to set direction and monitor the health of an organization's big data programs.<ref name=":2">{{Cite journal|last=El-Darwiche |display-authors=etal |date=2014|title=Big Data Maturity: An action plan for policymakers and executives|journal=World Economic Forum}}</ref><ref name=":3">{{Cite web|url=http://www.radcliffeadvisory.com/research/download.php?file=RAS_BD_MatMod.pdf|title=Leverage a Big Data Maturity model to build your big data roadmap|date=2014|access-date=2017-05-21|archive-url=https://web.archive.org/web/20170802005853/http://www.radcliffeadvisory.com/research/download.php?file=RAS_BD_MatMod.pdf|archive-date=2017-08-02|url-status=dead}}</ref>
An underlying assumption is that a high level of big data maturity correlates with an increase in revenue and reduction in operational expense. However, reaching the highest level of maturity involves major investments over many years.<ref name=":0">{{Cite journal|last=Halper|first=Fern|date=2016|title=A Guide to Achieving Big Data Analytics Maturity|journal=TDWI Benchmark Guide}}</ref> Only a few companies are considered to be at a "mature" stage of big data and analytics.<ref>{{Cite web |date=December 15, 2023 |title=How to summit "data maturity mountain" and make data your superpower |url=https://www.fastcompany.com/90998039/how-to-summit-data-maturity-mountain-and-make-data-your-superpower |access-date=October 8, 2024 |website=Fast Company |author1=Altair }}</ref> These include internet-based companies (such as [[LinkedIn]], [[Facebook]], and [[Amazon.com|Amazon]]) and other non-Internet-based companies, including financial institutions (fraud analysis, real-time customer messaging and behavioral modeling) and retail organizations ([[Clickstream|click-stream]] analytics together with self-service analytics for teams).<ref name=":0" />
== Categories ==
| |||