The Big Data Maturity Model

Posted by
Faton Gjuka
  |  October 05, 2016

Today, the big data market is showing a vibrant momentum as many companies transform into data-driven entities. Massive data growth is a key driver of the big data related technologies, infrastructure, and services. The Big Data Maturity Model applies a “hierarchy of needs” to global businesses’ aspirations to develop technology platforms as well as business processes. Regardless of where your business lands on the evolutionary scale of big data maturity, the key is to maximize potential at each stage and build on these tangible milestones to get to the next level on the big data maturity spectrum. The following stages offer companies a glimpse into where their business sits on the big data maturity scale, and offer insights to help these businesses graduate to the next level of big data maturity.

Discover stage

Companies found in this evaluation stage are just beginning to research, review, and understand what big data is and its potential to positively impact their business At the enterprise level, this business is beginning to realize it will need to accommodate growing big data storage requirements in order to keep pace with current technology. To graduate from this stage, it’s important for key stakeholders to understand how data-driven insights can realize use cases previously out of reach. Getting to the next level also requires seeing big data as more than just visualization or business intelligence.

Startup stage

Businesses in this phase continue to learn and understand what big data entails.  They take initial steps to design, plan and provision an initial cluster. Domain experts review analytical use cases and obtain the appropriate data to support these use cases. At the enterprise level, businesses plan and architect its big data requirements realizing the use cases and analytics that can be applied.

Tactical adoption stage

Companies in this space understand the value proposition of big data, but are just now learning what big data offers on a more tactical level. No strategic level planning or implementation has occurred at this stage. At the enterprise level, these companies realize that big data requirements are growing and are now looking at how to profit from data as an asset.

Strategic integration stage

In this stage, businesses understand and have implemented big data solutions.  An enterprise at this juncture is realizing returns and positive ROI on the value proposition, with the majority of its use cases already developed and implemented.  At the enterprise level, businesses fully realize its big data goals including big data analytics as well as predictive analytics.

The company seems ready to address the increasing demand for handling large volumes of data. A vast number of the company employees are fully equipped with skills and practical experience in managing big data platforms. The level of implementation follows the corporate guidelines and industry best practices. As if not enough, big data systems are up and running on different projects with continuous use cases being explored and implemented when the need arises.

Optimization stage

At this level, enterprises possess a visionary and optimized understanding of big data, and are maximizing it to realize full benefits. At the enterprise level, businesses are now fully transformed into a “predictive enterprise” where businesses predict instead of react to customer needs.   

The Big Data Maturity model helps your organization determine 1) where it currently lands on the Big Data Maturity spectrum, and 2) take steps to get to the next level. From initial discovery and start-up to more tactical adoption, strategic integration, and finally, optimization, on what level does your organization view itself? What’s clear is that your business has the power to grow and build on its big data initiatives toward a much more effective big data approach, if it has the will.

Source: 5-Stages of Big Data Maturity by Steve Thompson

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