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Difference between revisions of "Big Data Maturity Model (BDMM)"

(Big Data Maturity Models (BDMM) are the artifacts used to measure Big Data maturity. These models help organizations to create structure around their Big Data capabilities and to identify where to start.)
 
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A Maturity Model is a continuum of capability from the lowest, or beginner, to the highest, or expert level. A maturity model is used to assess current capability, help create a plan of action to improve capability, and monitor progress along the continuum.
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A Maturity [[Model]] is a continuum of capability from the lowest, or beginner, to the highest, or expert level. A maturity model is used to assess current capability, help create a plan of action to improve capability, and monitor progress along the continuum.
  
Big Data Maturity Models (BDMM) are the artifacts used to measure Big Data maturity. These models help organizations to create structure around their Big Data capabilities and to identify where to start. They provide tools that assist organizations to define goals around their big data program and to communicate their big data vision to the entire organization. BDMMs also provide a methodology to measure and monitor the state of a company’s big data capability, the effort required to complete their current stage or phase of maturity and to progress to the next stage. Additionally, BDMMs measure and manage the speed of both the progress and adoption of big data programs in the organization.<ref>What is Big Data Maturity Model? [https://en.wikipedia.org/wiki/Big_Data_Maturity_Model Wikipedia]</ref>
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Big [[Data]] Maturity Models (BDMM) are the artifacts used to measure [[Big Data]] maturity. These models help organizations to create structure around their Big Data capabilities and to identify where to start. They provide tools that assist organizations to define [[goals]] around their big data program and to communicate their big data [[vision]] to the entire [[organization]]. BDMMs also provide a [[methodology]] to measure and monitor the state of a company’s big data capability, the effort required to complete their current stage or phase of maturity and to progress to the next stage. Additionally, BDMMs measure and manage the speed of both the progress and adoption of big data programs in the organization.<ref>What is Big Data Maturity Model? [https://en.wikipedia.org/wiki/Big_Data_Maturity_Model Wikipedia]</ref>
  
  

Revision as of 14:01, 6 February 2021

A Maturity Model is a continuum of capability from the lowest, or beginner, to the highest, or expert level. A maturity model is used to assess current capability, help create a plan of action to improve capability, and monitor progress along the continuum.

Big Data Maturity Models (BDMM) are the artifacts used to measure Big Data maturity. These models help organizations to create structure around their Big Data capabilities and to identify where to start. They provide tools that assist organizations to define goals around their big data program and to communicate their big data vision to the entire organization. BDMMs also provide a methodology to measure and monitor the state of a company’s big data capability, the effort required to complete their current stage or phase of maturity and to progress to the next stage. Additionally, BDMMs measure and manage the speed of both the progress and adoption of big data programs in the organization.[1]


See Also

Big Data
Capability Maturity Model (CMM)


References

  1. What is Big Data Maturity Model? Wikipedia